Kinetica On-Premises Documentation on Kinetica Docs

Quick Start Guide + SQL GPT

Mon, 01 Jan 0001 00:00:00 +0000

Install Kinetica There are several different options for installing Kinetica on-premises or in the cloud (Azure or AWS). However, to get started within minutes (and for free) we recommend either of the following two routes: Kinetica Cloud Free: This is a free managed version with 10 GB of storage, which is hosted in the cloud. Follow the instructions for Kinetica Cloud Free to create an account and launch Kinetica.

Quick Start Guide + SQL GPT

Mon, 01 Jan 0001 00:00:00 +0000

Backhaul Routing in Python

Mon, 01 Jan 0001 00:00:00 +0000

The following is a complete example, using the Python API, of solving a graph created with Seattle road network data for a backhaul routing problem via the /solve/graph endpoint. For more information on Network Graphs & Solvers, see Network Graphs & Solvers Concepts. Prerequisites Python API Installation Data File Script Detail Constants Graph Creation Backhaul Routing Download & Run Prerequisites The prerequisites for running the backhaul routing solve graph example are listed below:

Backhaul Routing in Python

Mon, 01 Jan 0001 00:00:00 +0000

C++ Developer Guide

Mon, 01 Jan 0001 00:00:00 +0000

The following guide provides step-by-step instructions to get started writing C++ applications using Kinetica. This guide demonstrates only a small set of the available API. A detailed description of the complete interface is available under C++ API Reference. API Download The source code for the C++ API is available for download from the GitHub repository kineticadb/kinetica-api-cpp. Follow the instructions in the included README file to build the API library.

C++ Developer Guide

Mon, 01 Jan 0001 00:00:00 +0000

Fitting Road Network Data to a Graph

Mon, 01 Jan 0001 00:00:00 +0000

The following guide provides step-by-step instructions to get started with fitting existing road network data to a graph. Since edges in graphs can only be composed of two nodes, the weight (or cost to travel) for complex WKT LINESTRINGs (e.g., more than two points) that typically define road networks must be assigned consistently to the segments composing the LINESTRING, as noted under Weights. There are two methods for calculating and assigning weights to a graph with edges derived from large WKT LINESTRINGs:

Fitting Road Network Data to a Graph

Mon, 01 Jan 0001 00:00:00 +0000

Generate Isochrones

Mon, 01 Jan 0001 00:00:00 +0000

The following is a complete example, using the Python API, of generating images containing isochrones via the /visualize/isochrone and /wms endpoints using an existing graph. Prerequisites Python API Installation PyPI Git Data File Script Detail Connections Constants Graph Creation Visualizing Isochrones Visualizing Isochrones Using WMS Download & Run Prerequisites The prerequisites for running the isochrones example are listed below: Graph server enabled Python API Isochrones example script DC Shape data CSV file Python API Installation The native Kinetica Python API is accessible through the following means:

Generate Isochrones

Mon, 01 Jan 0001 00:00:00 +0000

Graph Solvers with REST

Mon, 01 Jan 0001 00:00:00 +0000

The following guide provides step-by-step instructions to get started with using the Network Graphs & Solvers in Kinetica. This guide demonstrates some key graph concepts as well as how to create and solve a graph using the Kinetica REST API. Prerequisites Data File Using the REST API Key Information and Concepts Data Graph Concepts Tutorial via REST Client Create Graph Solve the Graph (Shortest Path) Solve the Graph (Multiple Routing) Download & Run Prerequisites D.

Graph Solvers with REST

Mon, 01 Jan 0001 00:00:00 +0000

Graph Solvers with UI

Mon, 01 Jan 0001 00:00:00 +0000

The following guide provides step-by-step instructions to get started with using the Network Graphs & Solvers in Kinetica. This guide demonstrates some key graph concepts as well as how to create and solve a graph using the Workbench Data Explorer and Workbook. Prerequisites Data File Key Information and Concepts Data Graph Concepts Tutorial via GUI Create Schema Create Graph Solve the Graph (Shortest Path) Solve the Graph (Multiple Routing) Prerequisites D.

Graph Solvers with UI

Mon, 01 Jan 0001 00:00:00 +0000

The following guide provides step-by-step instructions to get started with using the Network Graphs & Solvers in Kinetica. This guide demonstrates some key graph concepts as well as how to create and solve a graph using the GAdmin graph GUI. Prerequisites Data File Key Information and Concepts Data Graph Concepts Tutorial via GUI Create Schema Create Graph Solve the Graph (Shortest Path) Solve the Graph (Multiple Routing) Prerequisites D.C. Shape data file Access to GAdmin Data File The tutorial makes use of the dc_shape dataset, which can be ingested from the {{< download "/examples/data/dc_shape.

Introduction to Kinetica Graph

Mon, 01 Jan 0001 00:00:00 +0000

In this video series, Hari Subhash walks through graphs in Kinetica, from high-level concepts to practical examples.

Introduction to Kinetica Graph

Mon, 01 Jan 0001 00:00:00 +0000

In this video series, Hari Subhash walks through graphs in Kinetica, from high-level concepts to practical examples.

Java Developer Guide

Mon, 01 Jan 0001 00:00:00 +0000

The following guide provides step-by-step instructions to get started writing Java applications using Kinetica. This guide demonstrates only a small set of the available API. A detailed description of the complete interface is available under Java API Reference. Prerequisites Data File API Download Maven Download Manual Download File Hierarchy Connecting to the Database Creating a Schema Creating a Type Creating a Table Inserting Data Key/Value Record In-Line Record CSV Retrieving Data Updating Records Deleting Records Alter Table Indexes Dictionary Encoding Filters Aggregates Joins Projections Union, Intersect, & Except Download & Run Prerequisites Data File The tutorial java file makes reference to a data file in the current directory.

Java Developer Guide

Mon, 01 Jan 0001 00:00:00 +0000

JavaScript Developer Guide

Mon, 01 Jan 0001 00:00:00 +0000

The following guide provides step-by-step instructions to get started writing JavaScript applications using Kinetica. This guide demonstrates only a small set of the available API. A detailed description of the complete interface is available under JavaScript API Reference. API Download The source code for the JavaScript API is available for download from the GitHub repository kineticadb/kinetica-api-javascript. Follow the instructions in the included README file to use the API library.

JavaScript Developer Guide

Mon, 01 Jan 0001 00:00:00 +0000

JupyterLab Tutorial

Mon, 01 Jan 0001 00:00:00 +0000

Introduction Prerequisites Docker Install Setting Permissions Entering the License Key Pulling the Image Managing the Container Starting Using Stopping Exploring the Environment JupyterLab Contents Mounted Volumes Example Notebooks SVD Recommender and Visualization Example KJIO Utility Library Conclusion References Introduction JupyterLab is an integrated environment that can streamline the development of Python code and Machine Learning (ML) models in Kinetica. Jupyter notebooks integrate code execution, debugging, documentation, and visualization in a single document for consumption by multiple audiences.

JupyterLab Tutorial

Mon, 01 Jan 0001 00:00:00 +0000

Map Matching with Python

Mon, 01 Jan 0001 00:00:00 +0000

The following is a complete example, using the Python API, of matching GPS sample data to road network data via the /match/graph endpoint. For more information on Network Graphs & Solvers, see Network Graphs & Solvers Concepts. Prerequisites Python API Installation Data Files Script Detail Constants Graph Creation Matching the Graph without Fold-over Filtering Matching the Graph with Fold-over Filtering Download & Run Prerequisites The prerequisites for running the match graph example are listed below:

Map Matching with Python

Mon, 01 Jan 0001 00:00:00 +0000

Multiple Routing in Python

Mon, 01 Jan 0001 00:00:00 +0000

The following is a complete example, using the Python API, of solving a graph created with NYC Taxi data for a multiple routing problem via the /solve/graph endpoint. For more information on Network Graphs & Solvers, see Network Graphs & Solvers Concepts. Prerequisites Python API Installation Data File Script Detail Constants Graph Creation Multiple Routing Download & Run Prerequisites The prerequisites for running the multiple routing solve graph example are listed below:

Multiple Routing in Python

Mon, 01 Jan 0001 00:00:00 +0000

Multiple Routing on Seattle Road Network

Mon, 01 Jan 0001 00:00:00 +0000

The following is a complete example, using the Python API, of solving a graph created with Seattle road network data for a multiple routing problem via the /solve/graph endpoint. For more information on Network Graphs & Solvers, see Network Graphs & Solvers Concepts. Prerequisites Python API Installation Data File Script Detail Constants Graph Creation Multiple Routing Download & Run Prerequisites The prerequisites for running the multiple routing solve graph example are listed below:

Multiple Routing on Seattle Road Network

Mon, 01 Jan 0001 00:00:00 +0000

Multiple Supply Demand in Python

Mon, 01 Jan 0001 00:00:00 +0000

The following is a complete example, using the Python API, of matching stores (demands) to depots/trucks (suppliers) via the /match/graph endpoint using an underlying graph created from a modified OpenStreetMap (OSM) dataset. For more information on Network Graphs & Solvers, see Network Graphs & Solvers Concepts. Prerequisites Python API Installation Data File Script Detail Constants Table Setup Graph Creation Multiple Supply Demand with Priority Solution Analysis Multiple Supply Demand with Priority and Max Trip Cost Download & Run Prerequisites The prerequisites for running the match graph example are listed below:

Multiple Supply Demand in Python

Mon, 01 Jan 0001 00:00:00 +0000

Node.js Developer Guide

Mon, 01 Jan 0001 00:00:00 +0000

The following guide provides step-by-step instructions to get started writing Node.js applications using the client-side Node.js module for Kinetica. This guide demonstrates only a small set of the available API. A detailed description of the complete interface is available under Node.js API Reference. API Download The source code for the Node.js API is available for download from the GitHub repository kineticadb/kinetica-api-javascript. Follow the instructions in the included README file to use the API library.

Node.js Developer Guide

Mon, 01 Jan 0001 00:00:00 +0000

Page Rank in Python

Mon, 01 Jan 0001 00:00:00 +0000

The following is a complete example, using the Python API, of solving a graph created with NYC Taxi data for a page rank problem via the /solve/graph endpoint. For more information on Network Graphs & Solvers, see Network Graphs & Solvers Concepts. Prerequisites Python API Installation Data File Script Detail Constants Graph Creation Page Rank Download & Run Prerequisites The prerequisites for running the page rank solve graph example are listed below:

Page Rank in Python

Mon, 01 Jan 0001 00:00:00 +0000

Python Developer Guide

Mon, 01 Jan 0001 00:00:00 +0000

The following guide provides step-by-step instructions to get started writing Python applications using Kinetica. This guide demonstrates only a small set of the available API. A detailed description of the complete interface is available under Python API Reference. Prerequisites Python API Installation PyPI Git Data File Connecting to the Database Creating a Schema Creating a Type Creating a Table Inserting Data Key/Value Record In-Line Record CSV Retrieving Data Updating Records Deleting Records Alter Table Indexes Dictionary Encoding Filters Aggregates Joins Projections Union, Intersect, & Except Download & Run Prerequisites The prerequisites for running the match graph example are listed below:

Python Developer Guide

Mon, 01 Jan 0001 00:00:00 +0000

Python UDF Guide

Mon, 01 Jan 0001 00:00:00 +0000

The following guide provides step-by-step instructions to get started writing and running UDFs in Python. This example is a simple distributed UDF that copies data from one table to another using a CSV configuration file to determine on which processing node(s) data will be copied. Standard (non-replicated) tables have their data distributed across all processing nodes, while replicated tables have all of their data on every processing node. In this example, we'll use a standard table and copy only the portions of its data that reside on the nodes named in the CSV file.

Python UDF Guide

Mon, 01 Jan 0001 00:00:00 +0000

Querying Social Graphs

Mon, 01 Jan 0001 00:00:00 +0000

The following is a complete example, using the Python API, of querying social relationship data via the /query/graph endpoint. For more information on Network Graphs & Solvers, see Network Graphs & Solvers Concepts. Prerequisites Python API Installation Script Detail Constants Table Setup Graph Creation Querying the Graph Download & Run Prerequisites The prerequisites for running the query graph example are listed below: Graph server enabled Python API Query graph script Python API Installation The native Kinetica Python API is accessible through the following means:

Querying Social Graphs

Mon, 01 Jan 0001 00:00:00 +0000

Shortest Path with Python

Mon, 01 Jan 0001 00:00:00 +0000

The following is a complete example, using the Python API, of solving a graph created with Seattle road network data for a shortest path problem via the /solve/graph endpoint. For more information on Network Graphs & Solvers, see Network Graphs & Solvers Concepts. Prerequisites Python API Installation PyPI Git Data File Script Detail Constants Graph Creation Shortest Path Single Source to Single Destination Single Source to Many Destinations Many Sources to Many Destinations Download & Run Prerequisites The prerequisites for running the shortest path solve graph example are listed below:

Shortest Path with Python

Mon, 01 Jan 0001 00:00:00 +0000

Shortest Path with Turn Penalties & Restrictions

Mon, 01 Jan 0001 00:00:00 +0000

The following is a complete example, using the Python API, of solving a graph created with a Washington, D.C. HERE dataset for a shortest path problem with turn penalties via the /solve/graph endpoint. For more information on Network Graphs & Solvers, see Network Graphs & Solvers Concepts. For more information on turn penalties and restrictions, see Using Turn-based Weights & Restrictions. Prerequisites Python API Installation Data File Script Detail Constants Table Setup Graph Creation Shortest Path Download & Run Prerequisites The prerequisites for running this solve graph example are listed below:

Shortest Path with Turn Penalties & Restrictions

Mon, 01 Jan 0001 00:00:00 +0000

SQL Developer Guide

Mon, 01 Jan 0001 00:00:00 +0000

The following guide provides step-by-step instructions to get started interacting with Kinetica using SQL. This guide demonstrates some of the most common and useful SQL commands, but a detailed look into the full SQL support is available on the SQL page. Prerequisites Data File Creating a Type and Table Inserting Data Retrieving Data Updating Records Deleting Records Alter Table Indexes Dictionary Encoding Filters & Aggregates Subqueries Common Table Expression / With Joins Create Table As Union, Intersect, and Except Truncate Complete Sample Prerequisites For a description of how to configure various clients for issuing SQL commands, see Connecting.

SQL Developer Guide

Mon, 01 Jan 0001 00:00:00 +0000

SQL-Managed Python UDF: Semantic Search

Mon, 01 Jan 0001 00:00:00 +0000

Download & Run UDF Detail SQL Management Script Create Tables Load UDF & Data Files Create a Python UDF Environment Register UDF & UDTF Execute UDF & UDTF Python UDF Script Initialize UDF Perform Semantic Search Write Output Data The following is a SQL-managed UDF written in the Python UDF API that performs a semantic search for a given sentence on a baseline set of sentences, ranking the baseline sentences on their similarity to the given one.

SQL-Managed Python UDF: Semantic Search

Mon, 01 Jan 0001 00:00:00 +0000

Table Monitor Guide

Mon, 01 Jan 0001 00:00:00 +0000

The following is an excerpted tutorial, extracted from a complete example using the Python Table Monitor API, demonstrating the basic use of the three table monitor types: table insert monitor - watches a table for newly inserted records and can make use of those records elsewhere table update monitor - watches a table for updates and reports the number of records updated in each update request issued table delete monitor - watches a table for deletes and reports the number of records deleted in each delete request issued The table monitors will be managed via instances of the GPUdbTableMonitor.

Table Monitor Guide

Mon, 01 Jan 0001 00:00:00 +0000

Using WKT Data and Geospatial Functions

Mon, 01 Jan 0001 00:00:00 +0000

The following sections demonstrate how to ingest and work with WKT data as well as how to use geospatial functions via SQL and the Kinetica Python API. Details about the geospatial functions can be found under Geospatial/Geometry Functions. All geospatial functions are compatible in both native API and SQL. Prerequisites Loading Sample Data Examples via SQL Creating a Table and Inserting WKT Data Scalar Functions Aggregation Functions Joins Equality Examples via the Python API Creating a Table and Inserting WKT Data Scalar Functions Aggregation Functions Joins Equality Complete Samples Prerequisites KiSQL (if running the SQL examples) Python API (if running the Python examples) Sample CSV data files, which should be downloaded & copied to the host running the SQL client.

Using WKT Data and Geospatial Functions

Mon, 01 Jan 0001 00:00:00 +0000

Exporting Data

Mon, 01 Jan 0001 00:00:00 +0000

EXPORT ... INTO Sources (Table/Query) Data Sinks (File/Table/DML) Delimited Text Options Parquet Files Naming Options Sizing Options EXPORT ... INTO Sources (Table/Query) Table Query Table 1 2 EXPORT TABLE employee INTO FILE PATH '/export/employee.csv' Query 1 2 3 4 5 6 7 EXPORT QUERY ( SELECT id, manager_id, first_name, last_name, salary, hire_date FROM employee WHERE dept_id = 2 ) INTO FILE PATH '/export/employee_dept2.csv' Data Sinks (File/Table/DML) File Table (via JDBC) DML (via JDBC) Init Options (via JDBC) File 1 2 3 EXPORT TABLE employee INTO FILE PATH '/data/employee.

Exporting Data

Mon, 01 Jan 0001 00:00:00 +0000

Geohashing

Mon, 01 Jan 0001 00:00:00 +0000

Enrich a Point-Based Table with Geohashes Create an Aggregated View with WKT Geometries Enrich a Point-Based Table with Geohashes Create a geohash for pickup locations in the NYC taxi data set. Lat/Lon-Based Table WKT-Based Table Lat/Lon-Based Table 1 2 3 4 5 6 7 8 CREATE OR REPLACE TABLE example_geospatial.nyctaxi_geohash AS ( SELECT pickup_latitude, pickup_longitude, STXY_GEOHASH(pickup_longitude, pickup_latitude, 6) AS geohash FROM example_geospatial.nyctaxi_xy ) WKT-Based Table 1 2 3 4 5 6 7 CREATE OR REPLACE TABLE example_geospatial.

Geohashing

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H3 Geohashing

Mon, 01 Jan 0001 00:00:00 +0000

Enrich a Point-Based Table with H3 Indexes Create an Aggregated View with WKT Geometries Enrich a Point-Based Table with H3 Indexes Create an H3 index for pickup locations in the NYC taxi data set. Lat/Lon-Based Table WKT-Based Table Lat/Lon-Based Table 1 2 3 4 5 6 7 8 CREATE OR REPLACE TABLE example_geospatial.nyctaxi_h3 AS ( SELECT pickup_latitude, pickup_longitude, H3_XYTOCELL(pickup_longitude, pickup_latitude, 8) AS h3_index FROM example_geospatial.nyctaxi_xy ) WKT-Based Table 1 2 3 4 5 6 7 CREATE OR REPLACE TABLE example_geospatial.

H3 Geohashing

Mon, 01 Jan 0001 00:00:00 +0000

JSON Egress

Mon, 01 Jan 0001 00:00:00 +0000

Simple Egress Egress with Parameters Egress with Aggregation The /get/records/json REST endpoint can be called to retrieve data in JSON form directly from the database. See Overview for call details and Responses for return values. Simple Egress cURL Python Java JavaScript Node.js cURL 1 2 3 4 5 6 7 8 9 10 KINETICA_URL=https://abcdefg.cloud.kinetica.com/hijklmn/gpudb-0 USERNAME=auser PASSWORD=apassword TABLE_NAME=product # Quote the URL when passing multiple options, or any & will stop the URL # parsing and run the URL parsed up to that point as a background job curl -sS ${KINETICA_URL}/get/records/json?

JSON Egress

Mon, 01 Jan 0001 00:00:00 +0000

Simple Egress Egress with Parameters Egress with Aggregation The /get/records/json REST endpoint can be called to retrieve data in JSON form directly from the database. See Overview for call details and Responses for return values. Simple Egress cURL Python Java JavaScript Node.js cURL 1 2 3 4 5 6 7 8 9 10 KINETICA_URL=http://localhost:9191 USERNAME=auser PASSWORD=apassword TABLE_NAME=product # Quote the URL when passing multiple options, or any & will stop the URL # parsing and run the URL parsed up to that point as a background job curl -sS ${KINETICA_URL}/get/records/json?

JSON Ingest

Mon, 01 Jan 0001 00:00:00 +0000

Basic Ingest from File Ingest from File with Options Ingest from JSON String The /insert/records/json REST endpoint can be called directly, or with a convenient wrapper in the Java API. See Overview for call details and Responses for return values. Basic Ingest from File cURL Python Java Java (Distributed Ingest) JavaScript Node.js cURL 1 2 3 4 5 6 7 8 9 10 KINETICA_URL=https://abcdefg.cloud.kinetica.com/hijklmn/gpudb-0 USERNAME=auser PASSWORD=apassword TABLE_NAME=product JSON_FILE_NAME=products.json curl -sS -X POST --header "Content-Type: application/json" \ --user "${USERNAME}:${PASSWORD}" \ -d @${JSON_FILE_NAME} \ ${KINETICA_URL}/insert/records/json?

JSON Ingest

Mon, 01 Jan 0001 00:00:00 +0000

Basic Ingest from File Ingest from File with Options Ingest from JSON String The /insert/records/json REST endpoint can be called directly, or with a convenient wrapper in the Java API. See Overview for call details and Responses for return values. Basic Ingest from File cURL Python Java Java (Distributed Ingest) JavaScript Node.js cURL 1 2 3 4 5 6 7 8 9 10 KINETICA_URL=http://localhost:9191 USERNAME=auser PASSWORD=apassword TABLE_NAME=product JSON_FILE_NAME=products.json curl -sS -X POST --header "Content-Type: application/json" \ --user "${USERNAME}:${PASSWORD}" \ -d @${JSON_FILE_NAME} \ ${KINETICA_URL}/insert/records/json?

Loading Data

Mon, 01 Jan 0001 00:00:00 +0000

LOAD INTO Single & Multiple KiFS Files Data Sources File/Queue-Based Query-Based File Types Delimited Text Files JSON/GeoJSON Files Parquet Files Shapefiles Avro Files Primary/Shard Keys Query Partitioning Options Other Options External Tables LOAD INTO Single & Multiple KiFS Files Single File Multiple Files by List Single File 1 2 LOAD DATA INTO example.product FROM FILE PATHS 'kifs://data/products.csv' Multiple Files by List 1 2 LOAD DATA INTO example.product FROM FILE PATHS 'kifs://data/products.

Loading Data

Mon, 01 Jan 0001 00:00:00 +0000

JSON Egress Tests Enter Parameters URL Username Password Schema Run Test

Mon, 01 Jan 0001 00:00:00 +0000

JSON Ingest Tests Enter Parameters URL Username Password Schema Filename Run Test

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Tutorial Enter Parameters URL Username Password Run Tutorial

Mon, 01 Jan 0001 00:00:00 +0000

JSON Egress Tests Enter Parameters URL Username Password Schema Run Test

Mon, 01 Jan 0001 00:00:00 +0000

JSON Ingest Tests Enter Parameters URL Username Password Schema Filename Run Test

Mon, 01 Jan 0001 00:00:00 +0000

Tutorial Enter Parameters URL Username Password Run Tutorial

/admin/add/host

Mon, 01 Jan 0001 00:00:00 +0000

URL: http://<db.host>:<hm.port>/admin/add/host Adds a host to an existing cluster. NOTE: This endpoint is serviced by the host manager, not the database cluster itself, so the port specified needs to be the host manager port instead. The default host manager port can be found under Default Ports. For more information on the host manager, see Host Manager. NOTE: This endpoint should be used for on-premise deployments only. Input Parameter Description Name Type Description host_address string IP address of the host that will be added to the cluster.

/admin/add/host

Mon, 01 Jan 0001 00:00:00 +0000

URL: https://<aws.fqdn>/<aws.cluster.name>/gpudb-host-manager/admin/add/host Adds a host to an existing cluster. NOTE: This endpoint is serviced by the host manager, not the database cluster itself, so the port specified needs to be the host manager port instead. The default host manager port can be found under Default Ports. For more information on the host manager, see Host Manager. NOTE: This endpoint should be used for on-premise deployments only. Input Parameter Description Name Type Description host_address string IP address of the host that will be added to the cluster.

/admin/add/ranks

Mon, 01 Jan 0001 00:00:00 +0000

URL: http://<db.host>:<db.port>/admin/add/ranks Add one or more ranks to an existing Kinetica cluster. The new ranks will not contain any data initially (other than replicated tables) and will not be assigned any shards. To rebalance data and shards across the cluster, use /admin/rebalance. The database must be offline for this operation, see /admin/offline For example, if attempting to add three new ranks (two ranks on host 172.123.45.67 and one rank on host 172.

/admin/add/ranks

Mon, 01 Jan 0001 00:00:00 +0000

URL: https://<aws.fqdn>/<aws.cluster.name>/gpudb-0/admin/add/ranks Add one or more ranks to an existing Kinetica cluster. The new ranks will not contain any data initially (other than replicated tables) and will not be assigned any shards. To rebalance data and shards across the cluster, use /admin/rebalance. The database must be offline for this operation, see /admin/offline For example, if attempting to add three new ranks (two ranks on host 172.123.45.67 and one rank on host 172.

/admin/alter/host

Mon, 01 Jan 0001 00:00:00 +0000

URL: http://<db.host>:<hm.port>/admin/alter/host Alter properties on an existing host in the cluster. Currently, the only property that can be altered is a hosts ability to accept failover processes. NOTE: This endpoint is serviced by the host manager, not the database cluster itself, so the port specified needs to be the host manager port instead. The default host manager port can be found under Default Ports. For more information on the host manager, see Host Manager.

/admin/alter/host

Mon, 01 Jan 0001 00:00:00 +0000

URL: https://<aws.fqdn>/<aws.cluster.name>/gpudb-host-manager/admin/alter/host Alter properties on an existing host in the cluster. Currently, the only property that can be altered is a hosts ability to accept failover processes. NOTE: This endpoint is serviced by the host manager, not the database cluster itself, so the port specified needs to be the host manager port instead. The default host manager port can be found under Default Ports. For more information on the host manager, see Host Manager.

/admin/alter/jobs

Mon, 01 Jan 0001 00:00:00 +0000

URL: http://<db.host>:<db.port>/admin/alter/jobs Perform the requested action on a list of one or more job(s). Based on the type of job and the current state of execution, the action may not be successfully executed. The final result of the attempted actions for each specified job is returned in the status array of the response. See Job Manager for more information. Input Parameter Description Name Type Description job_ids array of longs Jobs to be modified.

/admin/alter/jobs

Mon, 01 Jan 0001 00:00:00 +0000

URL: https://<aws.fqdn>/<aws.cluster.name>/gpudb-0/admin/alter/jobs Perform the requested action on a list of one or more job(s). Based on the type of job and the current state of execution, the action may not be successfully executed. The final result of the attempted actions for each specified job is returned in the status array of the response. See Job Manager for more information. Input Parameter Description Name Type Description job_ids array of longs Jobs to be modified.

/admin/backup/begin

Mon, 01 Jan 0001 00:00:00 +0000

URL: http://<db.host>:<db.port>/admin/backup/begin Prepares the system for a backup by closing all open file handles after allowing current active jobs to complete. When the database is in backup mode, queries that result in a disk write operation will be blocked until backup mode has been completed by using /admin/backup/end. Input Parameter Description Name Type Description options map of string to strings Optional parameters. The default value is an empty map ( {} ).

/admin/backup/begin

Mon, 01 Jan 0001 00:00:00 +0000

URL: https://<aws.fqdn>/<aws.cluster.name>/gpudb-0/admin/backup/begin Prepares the system for a backup by closing all open file handles after allowing current active jobs to complete. When the database is in backup mode, queries that result in a disk write operation will be blocked until backup mode has been completed by using /admin/backup/end. Input Parameter Description Name Type Description options map of string to strings Optional parameters. The default value is an empty map ( {} ).

/admin/backup/end

Mon, 01 Jan 0001 00:00:00 +0000

URL: http://<db.host>:<db.port>/admin/backup/end Restores the system to normal operating mode after a backup has completed, allowing any queries that were blocked to complete. Input Parameter Description Name Type Description options map of string to strings Optional parameters. The default value is an empty map ( {} ). Output Parameter Description The GPUdb server embeds the endpoint response inside a standard response structure which contains status information and the actual response to the query.

/admin/backup/end

Mon, 01 Jan 0001 00:00:00 +0000

URL: https://<aws.fqdn>/<aws.cluster.name>/gpudb-0/admin/backup/end Restores the system to normal operating mode after a backup has completed, allowing any queries that were blocked to complete. Input Parameter Description Name Type Description options map of string to strings Optional parameters. The default value is an empty map ( {} ). Output Parameter Description The GPUdb server embeds the endpoint response inside a standard response structure which contains status information and the actual response to the query.

/admin/ha/refresh

Mon, 01 Jan 0001 00:00:00 +0000

URL: http://<db.host>:<db.port>/admin/ha/refresh Restarts the HA processing on the given cluster as a mechanism of accepting breaking HA conf changes. Additionally the cluster is put into read-only while HA is restarting. Input Parameter Description Name Type Description options map of string to strings Optional parameters. The default value is an empty map ( {} ). Output Parameter Description The GPUdb server embeds the endpoint response inside a standard response structure which contains status information and the actual response to the query.

/admin/ha/refresh

Mon, 01 Jan 0001 00:00:00 +0000

URL: https://<aws.fqdn>/<aws.cluster.name>/gpudb-0/admin/ha/refresh Restarts the HA processing on the given cluster as a mechanism of accepting breaking HA conf changes. Additionally the cluster is put into read-only while HA is restarting. Input Parameter Description Name Type Description options map of string to strings Optional parameters. The default value is an empty map ( {} ). Output Parameter Description The GPUdb server embeds the endpoint response inside a standard response structure which contains status information and the actual response to the query.

/admin/offline

Mon, 01 Jan 0001 00:00:00 +0000

URL: http://<db.host>:<db.port>/admin/offline Take the system offline. When the system is offline, no user operations can be performed with the exception of a system shutdown. Input Parameter Description Name Type Description offline boolean Set to true if desired state is offline. The supported values are: true false options map of string to strings Optional parameters. The default value is an empty map ( {} ). Supported Parameters (keys) Parameter Description flush_to_disk Flush to disk when going offline The supported values are:

/admin/offline

Mon, 01 Jan 0001 00:00:00 +0000

URL: https://<aws.fqdn>/<aws.cluster.name>/gpudb-0/admin/offline Take the system offline. When the system is offline, no user operations can be performed with the exception of a system shutdown. Input Parameter Description Name Type Description offline boolean Set to true if desired state is offline. The supported values are: true false options map of string to strings Optional parameters. The default value is an empty map ( {} ). Supported Parameters (keys) Parameter Description flush_to_disk Flush to disk when going offline The supported values are:

/admin/rebalance

Mon, 01 Jan 0001 00:00:00 +0000

URL: http://<db.host>:<db.port>/admin/rebalance Rebalance the data in the cluster so that all nodes contain an equal number of records approximately and/or rebalance the shards to be equally distributed (as much as possible) across all the ranks. The database must be offline for this operation, see /admin/offline If /admin/rebalance is invoked after a change is made to the cluster, e.g., a host was added or removed, sharded data will be evenly redistributed across the cluster by number of shards per rank while unsharded data will be redistributed across the cluster by data size per rank If /admin/rebalance is invoked at some point when unsharded data (a.

/admin/rebalance

Mon, 01 Jan 0001 00:00:00 +0000

URL: https://<aws.fqdn>/<aws.cluster.name>/gpudb-0/admin/rebalance Rebalance the data in the cluster so that all nodes contain an equal number of records approximately and/or rebalance the shards to be equally distributed (as much as possible) across all the ranks. The database must be offline for this operation, see /admin/offline If /admin/rebalance is invoked after a change is made to the cluster, e.g., a host was added or removed, sharded data will be evenly redistributed across the cluster by number of shards per rank while unsharded data will be redistributed across the cluster by data size per rank If /admin/rebalance is invoked at some point when unsharded data (a.

/admin/remove/host

Mon, 01 Jan 0001 00:00:00 +0000

URL: http://<db.host>:<hm.port>/admin/remove/host Removes a host from an existing cluster. If the host to be removed has any ranks running on it, the ranks must be removed using /admin/remove/ranks or manually switched over to a new host using /admin/switchover prior to host removal. If the host to be removed has the graph server or SQL planner running on it, these must be manually switched over to a new host using /admin/switchover.

/admin/remove/host

Mon, 01 Jan 0001 00:00:00 +0000

URL: https://<aws.fqdn>/<aws.cluster.name>/gpudb-host-manager/admin/remove/host Removes a host from an existing cluster. If the host to be removed has any ranks running on it, the ranks must be removed using /admin/remove/ranks or manually switched over to a new host using /admin/switchover prior to host removal. If the host to be removed has the graph server or SQL planner running on it, these must be manually switched over to a new host using /admin/switchover.

/admin/remove/ranks

Mon, 01 Jan 0001 00:00:00 +0000

URL: http://<db.host>:<db.port>/admin/remove/ranks Remove one or more ranks from an existing Kinetica cluster. All data will be rebalanced to other ranks before the rank(s) is removed unless the rebalance_sharded_data or rebalance_unsharded_data parameters are set to false in the input parameter options, in which case the corresponding sharded data and/or unsharded data (a.k.a. randomly-sharded) will be deleted. The database must be offline for this operation, see /admin/offline This endpoint's processing time depends on the amount of data in the system, thus the API call may time out if run directly.

/admin/remove/ranks

Mon, 01 Jan 0001 00:00:00 +0000

URL: https://<aws.fqdn>/<aws.cluster.name>/gpudb-0/admin/remove/ranks Remove one or more ranks from an existing Kinetica cluster. All data will be rebalanced to other ranks before the rank(s) is removed unless the rebalance_sharded_data or rebalance_unsharded_data parameters are set to false in the input parameter options, in which case the corresponding sharded data and/or unsharded data (a.k.a. randomly-sharded) will be deleted. The database must be offline for this operation, see /admin/offline This endpoint's processing time depends on the amount of data in the system, thus the API call may time out if run directly.

/admin/show/alerts

Mon, 01 Jan 0001 00:00:00 +0000

URL: http://<db.host>:<hm.port>/admin/show/alerts Requests a list of the most recent alerts. Returns lists of alert data, including timestamp and type. NOTE: This endpoint is serviced by the host manager, not the database cluster itself, so the port specified needs to be the host manager port instead. The default host manager port can be found under Default Ports. For more information on the host manager, see Host Manager. Input Parameter Description Name Type Description num_alerts int Number of most recent alerts to request.

/admin/show/alerts

Mon, 01 Jan 0001 00:00:00 +0000

URL: https://<aws.fqdn>/<aws.cluster.name>/gpudb-host-manager/admin/show/alerts Requests a list of the most recent alerts. Returns lists of alert data, including timestamp and type. NOTE: This endpoint is serviced by the host manager, not the database cluster itself, so the port specified needs to be the host manager port instead. The default host manager port can be found under Default Ports. For more information on the host manager, see Host Manager. Input Parameter Description Name Type Description num_alerts int Number of most recent alerts to request.

/admin/show/cluster/operations

Mon, 01 Jan 0001 00:00:00 +0000

URL: http://<db.host>:<db.port>/admin/show/cluster/operations Requests the detailed status of the current operation (by default) or a prior cluster operation specified by input parameter history_index. Returns details on the requested cluster operation. The response will also indicate how many cluster operations are stored in the history. Input Parameter Description Name Type Description history_index int Indicates which cluster operation to retrieve. Use 0 for the most recent. The default value is 0. options map of string to strings Optional parameters.

/admin/show/cluster/operations

Mon, 01 Jan 0001 00:00:00 +0000

URL: https://<aws.fqdn>/<aws.cluster.name>/gpudb-0/admin/show/cluster/operations Requests the detailed status of the current operation (by default) or a prior cluster operation specified by input parameter history_index. Returns details on the requested cluster operation. The response will also indicate how many cluster operations are stored in the history. Input Parameter Description Name Type Description history_index int Indicates which cluster operation to retrieve. Use 0 for the most recent. The default value is 0. options map of string to strings Optional parameters.

/admin/show/jobs

Mon, 01 Jan 0001 00:00:00 +0000

URL: http://<db.host>:<db.port>/admin/show/jobs Get a list of the current jobs in GPUdb. Input Parameter Description Name Type Description options map of string to strings Optional parameters. The default value is an empty map ( {} ). Supported Parameters (keys) Parameter Description show_async_jobs If true, then the completed async jobs are also included in the response. By default, once the async jobs are completed they are no longer included in the jobs list.

/admin/show/jobs

Mon, 01 Jan 0001 00:00:00 +0000

URL: https://<aws.fqdn>/<aws.cluster.name>/gpudb-0/admin/show/jobs Get a list of the current jobs in GPUdb. Input Parameter Description Name Type Description options map of string to strings Optional parameters. The default value is an empty map ( {} ). Supported Parameters (keys) Parameter Description show_async_jobs If true, then the completed async jobs are also included in the response. By default, once the async jobs are completed they are no longer included in the jobs list.

/admin/show/shards

Mon, 01 Jan 0001 00:00:00 +0000

URL: http://<db.host>:<db.port>/admin/show/shards Show the mapping of shards to the corresponding rank and tom. The response message contains list of 16384 (total number of shards in the system) Rank and TOM numbers corresponding to each shard. Input Parameter Description Name Type Description options map of string to strings Optional parameters. The default value is an empty map ( {} ). Output Parameter Description The GPUdb server embeds the endpoint response inside a standard response structure which contains status information and the actual response to the query.

/admin/show/shards

Mon, 01 Jan 0001 00:00:00 +0000

URL: https://<aws.fqdn>/<aws.cluster.name>/gpudb-0/admin/show/shards Show the mapping of shards to the corresponding rank and tom. The response message contains list of 16384 (total number of shards in the system) Rank and TOM numbers corresponding to each shard. Input Parameter Description Name Type Description options map of string to strings Optional parameters. The default value is an empty map ( {} ). Output Parameter Description The GPUdb server embeds the endpoint response inside a standard response structure which contains status information and the actual response to the query.

/admin/shutdown

Mon, 01 Jan 0001 00:00:00 +0000

URL: http://<db.host>:<db.port>/admin/shutdown Exits the database server application. Input Parameter Description Name Type Description exit_type string Reserved for future use. User can pass an empty string. authorization string No longer used. User can pass an empty string. options map of string to strings Optional parameters. The default value is an empty map ( {} ). Output Parameter Description The GPUdb server embeds the endpoint response inside a standard response structure which contains status information and the actual response to the query.

/admin/shutdown

Mon, 01 Jan 0001 00:00:00 +0000

URL: https://<aws.fqdn>/<aws.cluster.name>/gpudb-0/admin/shutdown Exits the database server application. Input Parameter Description Name Type Description exit_type string Reserved for future use. User can pass an empty string. authorization string No longer used. User can pass an empty string. options map of string to strings Optional parameters. The default value is an empty map ( {} ). Output Parameter Description The GPUdb server embeds the endpoint response inside a standard response structure which contains status information and the actual response to the query.

/admin/switchover

Mon, 01 Jan 0001 00:00:00 +0000

URL: http://<db.host>:<hm.port>/admin/switchover Manually switch over one or more processes to another host. Individual ranks or entire hosts may be moved to another host. NOTE: This endpoint is serviced by the host manager, not the database cluster itself, so the port specified needs to be the host manager port instead. The default host manager port can be found under Default Ports. For more information on the host manager, see Host Manager.

/admin/switchover

Mon, 01 Jan 0001 00:00:00 +0000

URL: https://<aws.fqdn>/<aws.cluster.name>/gpudb-host-manager/admin/switchover Manually switch over one or more processes to another host. Individual ranks or entire hosts may be moved to another host. NOTE: This endpoint is serviced by the host manager, not the database cluster itself, so the port specified needs to be the host manager port instead. The default host manager port can be found under Default Ports. For more information on the host manager, see Host Manager.

/admin/verifydb

Mon, 01 Jan 0001 00:00:00 +0000

URL: http://<db.host>:<db.port>/admin/verifydb Verify database is in a consistent state. When inconsistencies or errors are found, the verified_ok flag in the response is set to false and the list of errors found is provided in the error_list. Input Parameter Description Name Type Description options map of string to strings Optional parameters. The default value is an empty map ( {} ). Supported Parameters (keys) Parameter Description rebuild_on_error [DEPRECATED -- Use the Rebuild DB feature of GAdmin instead.

/admin/verifydb

Mon, 01 Jan 0001 00:00:00 +0000

URL: https://<aws.fqdn>/<aws.cluster.name>/gpudb-0/admin/verifydb Verify database is in a consistent state. When inconsistencies or errors are found, the verified_ok flag in the response is set to false and the list of errors found is provided in the error_list. Input Parameter Description Name Type Description options map of string to strings Optional parameters. The default value is an empty map ( {} ). Supported Parameters (keys) Parameter Description rebuild_on_error [DEPRECATED -- Use the Rebuild DB feature of GAdmin instead.

/aggregate/convexhull

Mon, 01 Jan 0001 00:00:00 +0000

URL: http://<db.host>:<db.port>/aggregate/convexhull Calculates and returns the convex hull for the values in a table specified by input parameter table_name. Input Parameter Description Name Type Description table_name string Name of table on which the operation will be performed. Must be an existing table, in [schema_name.]table_name format, using standard name resolution rules. x_column_name string Name of the column containing the x coordinates of the points for the operation being performed. y_column_name string Name of the column containing the y coordinates of the points for the operation being performed.

/aggregate/convexhull

Mon, 01 Jan 0001 00:00:00 +0000

URL: https://<aws.fqdn>/<aws.cluster.name>/gpudb-0/aggregate/convexhull Calculates and returns the convex hull for the values in a table specified by input parameter table_name. Input Parameter Description Name Type Description table_name string Name of table on which the operation will be performed. Must be an existing table, in [schema_name.]table_name format, using standard name resolution rules. x_column_name string Name of the column containing the x coordinates of the points for the operation being performed. y_column_name string Name of the column containing the y coordinates of the points for the operation being performed.

/aggregate/groupby

Mon, 01 Jan 0001 00:00:00 +0000

URL: http://<db.host>:<db.port>/aggregate/groupby Calculates unique combinations (groups) of values for the given columns in a given table or view and computes aggregates on each unique combination. This is somewhat analogous to an SQL-style SELECT...GROUP BY. For aggregation details and examples, see Aggregation. For limitations, see Aggregation Limitations. Any column(s) can be grouped on, and all column types except unrestricted-length strings may be used for computing applicable aggregates; columns marked as store-only are unable to be used in grouping or aggregation.

/aggregate/groupby

Mon, 01 Jan 0001 00:00:00 +0000

URL: https://<aws.fqdn>/<aws.cluster.name>/gpudb-0/aggregate/groupby Calculates unique combinations (groups) of values for the given columns in a given table or view and computes aggregates on each unique combination. This is somewhat analogous to an SQL-style SELECT...GROUP BY. For aggregation details and examples, see Aggregation. For limitations, see Aggregation Limitations. Any column(s) can be grouped on, and all column types except unrestricted-length strings may be used for computing applicable aggregates; columns marked as store-only are unable to be used in grouping or aggregation.

/aggregate/histogram

Mon, 01 Jan 0001 00:00:00 +0000

URL: http://<db.host>:<db.port>/aggregate/histogram Performs a histogram calculation given a table, a column, and an interval function. The input parameter interval is used to produce bins of that size and the result, computed over the records falling within each bin, is returned. For each bin, the start value is inclusive, but the end value is exclusive--except for the very last bin for which the end value is also inclusive. The value returned for each bin is the number of records in it, except when a column name is provided as a value_column.

/aggregate/histogram

Mon, 01 Jan 0001 00:00:00 +0000

URL: https://<aws.fqdn>/<aws.cluster.name>/gpudb-0/aggregate/histogram Performs a histogram calculation given a table, a column, and an interval function. The input parameter interval is used to produce bins of that size and the result, computed over the records falling within each bin, is returned. For each bin, the start value is inclusive, but the end value is exclusive--except for the very last bin for which the end value is also inclusive. The value returned for each bin is the number of records in it, except when a column name is provided as a value_column.

/aggregate/kmeans

Mon, 01 Jan 0001 00:00:00 +0000

URL: http://<db.host>:<db.port>/aggregate/kmeans This endpoint runs the k-means algorithm - a heuristic algorithm that attempts to do k-means clustering. An ideal k-means clustering algorithm selects k points such that the sum of the mean squared distances of each member of the set to the nearest of the k points is minimized. The k-means algorithm however does not necessarily produce such an ideal cluster. It begins with a randomly selected set of k points and then refines the location of the points iteratively and settles to a local minimum.

/aggregate/kmeans

Mon, 01 Jan 0001 00:00:00 +0000

URL: https://<aws.fqdn>/<aws.cluster.name>/gpudb-0/aggregate/kmeans This endpoint runs the k-means algorithm - a heuristic algorithm that attempts to do k-means clustering. An ideal k-means clustering algorithm selects k points such that the sum of the mean squared distances of each member of the set to the nearest of the k points is minimized. The k-means algorithm however does not necessarily produce such an ideal cluster. It begins with a randomly selected set of k points and then refines the location of the points iteratively and settles to a local minimum.

/aggregate/minmax

Mon, 01 Jan 0001 00:00:00 +0000

URL: http://<db.host>:<db.port>/aggregate/minmax Calculates and returns the minimum and maximum values of a particular column in a table. Input Parameter Description Name Type Description table_name string Name of the table on which the operation will be performed. Must be an existing table, in [schema_name.]table_name format, using standard name resolution rules. column_name string Name of a column or an expression of one or more column on which the min-max will be calculated.

/aggregate/minmax

Mon, 01 Jan 0001 00:00:00 +0000

URL: https://<aws.fqdn>/<aws.cluster.name>/gpudb-0/aggregate/minmax Calculates and returns the minimum and maximum values of a particular column in a table. Input Parameter Description Name Type Description table_name string Name of the table on which the operation will be performed. Must be an existing table, in [schema_name.]table_name format, using standard name resolution rules. column_name string Name of a column or an expression of one or more column on which the min-max will be calculated.

/aggregate/minmax/geometry

Mon, 01 Jan 0001 00:00:00 +0000

URL: http://<db.host>:<db.port>/aggregate/minmax/geometry Calculates and returns the minimum and maximum x- and y-coordinates of a particular geospatial geometry column in a table. Input Parameter Description Name Type Description table_name string Name of the table on which the operation will be performed. Must be an existing table, in [schema_name.]table_name format, using standard name resolution rules. column_name string Name of a geospatial geometry column on which the min-max will be calculated. options map of string to strings Optional parameters.

/aggregate/minmax/geometry

Mon, 01 Jan 0001 00:00:00 +0000

URL: https://<aws.fqdn>/<aws.cluster.name>/gpudb-0/aggregate/minmax/geometry Calculates and returns the minimum and maximum x- and y-coordinates of a particular geospatial geometry column in a table. Input Parameter Description Name Type Description table_name string Name of the table on which the operation will be performed. Must be an existing table, in [schema_name.]table_name format, using standard name resolution rules. column_name string Name of a geospatial geometry column on which the min-max will be calculated. options map of string to strings Optional parameters.

/aggregate/statistics

Mon, 01 Jan 0001 00:00:00 +0000

URL: http://<db.host>:<db.port>/aggregate/statistics Calculates the requested statistics of the given column(s) in a given table. The available statistics are: count (number of total objects), mean, stdv (standard deviation), variance, skew, kurtosis, sum, min, max, weighted_average, cardinality (unique count), estimated_cardinality, percentile, and percentile_rank. Estimated cardinality is calculated by using the hyperloglog approximation technique. Percentiles and percentile ranks are approximate and are calculated using the t-digest algorithm. They must include the desired percentile/percentile_rank.

/aggregate/statistics

Mon, 01 Jan 0001 00:00:00 +0000

URL: https://<aws.fqdn>/<aws.cluster.name>/gpudb-0/aggregate/statistics Calculates the requested statistics of the given column(s) in a given table. The available statistics are: count (number of total objects), mean, stdv (standard deviation), variance, skew, kurtosis, sum, min, max, weighted_average, cardinality (unique count), estimated_cardinality, percentile, and percentile_rank. Estimated cardinality is calculated by using the hyperloglog approximation technique. Percentiles and percentile ranks are approximate and are calculated using the t-digest algorithm. They must include the desired percentile/percentile_rank.

/aggregate/statistics/byrange

Mon, 01 Jan 0001 00:00:00 +0000

URL: http://<db.host>:<db.port>/aggregate/statistics/byrange Divides the given set into bins and calculates statistics of the values of a value-column in each bin. The bins are based on the values of a given binning-column. The statistics that may be requested are mean, stdv (standard deviation), variance, skew, kurtosis, sum, min, max, first, last and weighted average. In addition to the requested statistics the count of total samples in each bin is returned. This counts vector is just the histogram of the column used to divide the set members into bins.

/aggregate/statistics/byrange

Mon, 01 Jan 0001 00:00:00 +0000

URL: https://<aws.fqdn>/<aws.cluster.name>/gpudb-0/aggregate/statistics/byrange Divides the given set into bins and calculates statistics of the values of a value-column in each bin. The bins are based on the values of a given binning-column. The statistics that may be requested are mean, stdv (standard deviation), variance, skew, kurtosis, sum, min, max, first, last and weighted average. In addition to the requested statistics the count of total samples in each bin is returned. This counts vector is just the histogram of the column used to divide the set members into bins.

/aggregate/unique

Mon, 01 Jan 0001 00:00:00 +0000

URL: http://<db.host>:<db.port>/aggregate/unique Returns all the unique values from a particular column (specified by input parameter column_name) of a particular table or view (specified by input parameter table_name). If input parameter column_name is a numeric column, the values will be in output parameter binary_encoded_response. Otherwise if input parameter column_name is a string column, the values will be in output parameter json_encoded_response. The results can be paged via input parameter offset and input parameter limit parameters.

/aggregate/unique

Mon, 01 Jan 0001 00:00:00 +0000

URL: https://<aws.fqdn>/<aws.cluster.name>/gpudb-0/aggregate/unique Returns all the unique values from a particular column (specified by input parameter column_name) of a particular table or view (specified by input parameter table_name). If input parameter column_name is a numeric column, the values will be in output parameter binary_encoded_response. Otherwise if input parameter column_name is a string column, the values will be in output parameter json_encoded_response. The results can be paged via input parameter offset and input parameter limit parameters.

/aggregate/unpivot

Mon, 01 Jan 0001 00:00:00 +0000

URL: http://<db.host>:<db.port>/aggregate/unpivot Rotate the column values into rows values. For unpivot details and examples, see Unpivot. For limitations, see Unpivot Limitations. Unpivot is used to normalize tables that are built for cross tabular reporting purposes. The unpivot operator rotates the column values for all the pivoted columns. A variable column, value column and all columns from the source table except the unpivot columns are projected into the result table. The variable column and value columns in the result table indicate the pivoted column name and values respectively.

/aggregate/unpivot

Mon, 01 Jan 0001 00:00:00 +0000

URL: https://<aws.fqdn>/<aws.cluster.name>/gpudb-0/aggregate/unpivot Rotate the column values into rows values. For unpivot details and examples, see Unpivot. For limitations, see Unpivot Limitations. Unpivot is used to normalize tables that are built for cross tabular reporting purposes. The unpivot operator rotates the column values for all the pivoted columns. A variable column, value column and all columns from the source table except the unpivot columns are projected into the result table. The variable column and value columns in the result table indicate the pivoted column name and values respectively.

/alter/credential

Mon, 01 Jan 0001 00:00:00 +0000

URL: http://<db.host>:<db.port>/alter/credential Alter the properties of an existing credential. Input Parameter Description Name Type Description credential_name string Name of the credential to be altered. Must be an existing credential. credential_updates_map map of string to strings Map containing the properties of the credential to be updated. Error if empty. Supported Parameters (keys) Parameter Description type New type for the credential. The supported values are: aws_access_key aws_iam_role azure_ad azure_oauth azure_sas azure_storage_key docker gcs_service_account_id gcs_service_account_keys hdfs kafka identity New user for the credential secret New password for the credential schema_name Updates the schema name.

/alter/credential

Mon, 01 Jan 0001 00:00:00 +0000

URL: https://<aws.fqdn>/<aws.cluster.name>/gpudb-0/alter/credential Alter the properties of an existing credential. Input Parameter Description Name Type Description credential_name string Name of the credential to be altered. Must be an existing credential. credential_updates_map map of string to strings Map containing the properties of the credential to be updated. Error if empty. Supported Parameters (keys) Parameter Description type New type for the credential. The supported values are: aws_access_key aws_iam_role azure_ad azure_oauth azure_sas azure_storage_key docker gcs_service_account_id gcs_service_account_keys hdfs kafka identity New user for the credential secret New password for the credential schema_name Updates the schema name.

/alter/datasink

Mon, 01 Jan 0001 00:00:00 +0000

URL: http://<db.host>:<db.port>/alter/datasink Alters the properties of an existing data sink Input Parameter Description Name Type Description name string Name of the data sink to be altered. Must be an existing data sink. datasink_updates_map map of string to strings Map containing the properties of the data sink to be updated. Error if empty. Supported Parameters (keys) Parameter Description destination Destination for the output data in format 'destination_type://path[:port]'. Supported destination types are 'http', 'https' and 'kafka'.

/alter/datasink

Mon, 01 Jan 0001 00:00:00 +0000

URL: https://<aws.fqdn>/<aws.cluster.name>/gpudb-0/alter/datasink Alters the properties of an existing data sink Input Parameter Description Name Type Description name string Name of the data sink to be altered. Must be an existing data sink. datasink_updates_map map of string to strings Map containing the properties of the data sink to be updated. Error if empty. Supported Parameters (keys) Parameter Description destination Destination for the output data in format 'destination_type://path[:port]'. Supported destination types are 'http', 'https' and 'kafka'.

/alter/datasource

Mon, 01 Jan 0001 00:00:00 +0000

URL: http://<db.host>:<db.port>/alter/datasource Alters the properties of an existing data source Input Parameter Description Name Type Description name string Name of the data source to be altered. Must be an existing data source. datasource_updates_map map of string to strings Map containing the properties of the data source to be updated. Error if empty. Supported Parameters (keys) Parameter Description location Location of the remote storage in 'storage_provider_type://[storage_path[:storage_port]]' format. Supported storage provider types are 'azure','gcs','hdfs','kafka' and 's3'.

/alter/datasource

Mon, 01 Jan 0001 00:00:00 +0000

URL: https://<aws.fqdn>/<aws.cluster.name>/gpudb-0/alter/datasource Alters the properties of an existing data source Input Parameter Description Name Type Description name string Name of the data source to be altered. Must be an existing data source. datasource_updates_map map of string to strings Map containing the properties of the data source to be updated. Error if empty. Supported Parameters (keys) Parameter Description location Location of the remote storage in 'storage_provider_type://[storage_path[:storage_port]]' format. Supported storage provider types are 'azure','gcs','hdfs','kafka' and 's3'.

/alter/directory

Mon, 01 Jan 0001 00:00:00 +0000

URL: http://<db.host>:<db.port>/alter/directory Alters an existing directory in KiFS. Input Parameter Description Name Type Description directory_name string Name of the directory in KiFS to be altered. directory_updates_map map of string to strings Map containing the properties of the directory to be altered. Error if empty. Supported Parameters (keys) Parameter Description data_limit The maximum capacity, in bytes, to apply to the directory. Set to -1 to indicate no upper limit. options map of string to strings Optional parameters.

/alter/directory

Mon, 01 Jan 0001 00:00:00 +0000

URL: https://<aws.fqdn>/<aws.cluster.name>/gpudb-0/alter/directory Alters an existing directory in KiFS. Input Parameter Description Name Type Description directory_name string Name of the directory in KiFS to be altered. directory_updates_map map of string to strings Map containing the properties of the directory to be altered. Error if empty. Supported Parameters (keys) Parameter Description data_limit The maximum capacity, in bytes, to apply to the directory. Set to -1 to indicate no upper limit. options map of string to strings Optional parameters.

/alter/environment

Mon, 01 Jan 0001 00:00:00 +0000

URL: http://<db.host>:<db.port>/alter/environment Alters an existing environment which can be referenced by a user-defined function (UDF). Input Parameter Description Name Type Description environment_name string Name of the environment to be altered. action string Modification operation to be applied Supported Values Description install_package Install a python package from PyPI, an external data source or KiFS install_requirements Install packages from a requirements file uninstall_package Uninstall a python package. uninstall_requirements Uninstall packages from a requirements file reset Uninstalls all packages in the environment and resets it to the original state at time of creation rebuild Recreates the environment and re-installs all packages, upgrades the packages if necessary based on dependencies value string The value of the modification, depending on input parameter action.

/alter/environment

Mon, 01 Jan 0001 00:00:00 +0000

URL: https://<aws.fqdn>/<aws.cluster.name>/gpudb-0/alter/environment Alters an existing environment which can be referenced by a user-defined function (UDF). Input Parameter Description Name Type Description environment_name string Name of the environment to be altered. action string Modification operation to be applied Supported Values Description install_package Install a python package from PyPI, an external data source or KiFS install_requirements Install packages from a requirements file uninstall_package Uninstall a python package. uninstall_requirements Uninstall packages from a requirements file reset Uninstalls all packages in the environment and resets it to the original state at time of creation rebuild Recreates the environment and re-installs all packages, upgrades the packages if necessary based on dependencies value string The value of the modification, depending on input parameter action.

/alter/resourcegroup

Mon, 01 Jan 0001 00:00:00 +0000

URL: http://<db.host>:<db.port>/alter/resourcegroup Alters the properties of an exisiting resource group to facilitate resource management. Input Parameter Description Name Type Description name string Name of the group to be altered. Must be an existing resource group name or an empty string when used inconjunction with the is_default_group option. tier_attributes map of string to maps of string to strings Optional map containing tier names and their respective attribute group limits. The only valid attribute limit that can be set is max_memory (in bytes) for the VRAM & RAM tiers.

/alter/resourcegroup

Mon, 01 Jan 0001 00:00:00 +0000

URL: https://<aws.fqdn>/<aws.cluster.name>/gpudb-0/alter/resourcegroup Alters the properties of an exisiting resource group to facilitate resource management. Input Parameter Description Name Type Description name string Name of the group to be altered. Must be an existing resource group name or an empty string when used inconjunction with the is_default_group option. tier_attributes map of string to maps of string to strings Optional map containing tier names and their respective attribute group limits. The only valid attribute limit that can be set is max_memory (in bytes) for the VRAM & RAM tiers.

/alter/role

Mon, 01 Jan 0001 00:00:00 +0000

URL: http://<db.host>:<db.port>/alter/role Alters a Role. Input Parameter Description Name Type Description name string Name of the role to be altered. Must be an existing role. action string Modification operation to be applied to the role. Supported Values Description set_resource_group Sets the resource group for an internal role. The resource group must exist, otherwise, an empty string assigns the role to the default resource group. value string The value of the modification, depending on input parameter action.

/alter/role

Mon, 01 Jan 0001 00:00:00 +0000

URL: https://<aws.fqdn>/<aws.cluster.name>/gpudb-0/alter/role Alters a Role. Input Parameter Description Name Type Description name string Name of the role to be altered. Must be an existing role. action string Modification operation to be applied to the role. Supported Values Description set_resource_group Sets the resource group for an internal role. The resource group must exist, otherwise, an empty string assigns the role to the default resource group. value string The value of the modification, depending on input parameter action.

/alter/schema

Mon, 01 Jan 0001 00:00:00 +0000

URL: http://<db.host>:<db.port>/alter/schema Used to change the name of a SQL-style schema, specified in input parameter schema_name. Input Parameter Description Name Type Description schema_name string Name of the schema to be altered. action string Modification operation to be applied Supported Values Description rename_schema Renames a schema to input parameter value. Has the same naming restrictions as tables. value string The value of the modification, depending on input parameter action. For now the only value of input parameter action is rename_schema.

/alter/schema

Mon, 01 Jan 0001 00:00:00 +0000

URL: https://<aws.fqdn>/<aws.cluster.name>/gpudb-0/alter/schema Used to change the name of a SQL-style schema, specified in input parameter schema_name. Input Parameter Description Name Type Description schema_name string Name of the schema to be altered. action string Modification operation to be applied Supported Values Description rename_schema Renames a schema to input parameter value. Has the same naming restrictions as tables. value string The value of the modification, depending on input parameter action. For now the only value of input parameter action is rename_schema.

/alter/system/properties

Mon, 01 Jan 0001 00:00:00 +0000

URL: http://<db.host>:<db.port>/alter/system/properties The /alter/system/properties endpoint is primarily used to simplify the testing of the system and is not expected to be used during normal execution. Commands are given through the input parameter property_updates_map whose keys are commands and values are strings representing integer values (for example '8000') or boolean values ('true' or 'false'). Input Parameter Description Name Type Description property_updates_map map of string to strings Map containing the properties of the system to be updated.

/alter/system/properties

Mon, 01 Jan 0001 00:00:00 +0000

URL: https://<aws.fqdn>/<aws.cluster.name>/gpudb-0/alter/system/properties The /alter/system/properties endpoint is primarily used to simplify the testing of the system and is not expected to be used during normal execution. Commands are given through the input parameter property_updates_map whose keys are commands and values are strings representing integer values (for example '8000') or boolean values ('true' or 'false'). Input Parameter Description Name Type Description property_updates_map map of string to strings Map containing the properties of the system to be updated.

/alter/table

Mon, 01 Jan 0001 00:00:00 +0000

URL: http://<db.host>:<db.port>/alter/table Apply various modifications to a table or view. The available modifications include the following: Manage a table's columns--a column can be added, removed, or have its type and properties modified, including whether it is dictionary encoded or not. External tables cannot be modified except for their refresh method. Create or delete a column, chunk skip, or geospatial index. This can speed up certain operations when using expressions containing equality or relational operators on indexed columns.

/alter/table

Mon, 01 Jan 0001 00:00:00 +0000

URL: https://<aws.fqdn>/<aws.cluster.name>/gpudb-0/alter/table Apply various modifications to a table or view. The available modifications include the following: Manage a table's columns--a column can be added, removed, or have its type and properties modified, including whether it is dictionary encoded or not. External tables cannot be modified except for their refresh method. Create or delete a column, chunk skip, or geospatial index. This can speed up certain operations when using expressions containing equality or relational operators on indexed columns.

/alter/table/columns

Mon, 01 Jan 0001 00:00:00 +0000

URL: http://<db.host>:<db.port>/alter/table/columns Apply various modifications to columns in a table, view. The available modifications include the following: Create or delete an index on a particular column. This can speed up certain operations when using expressions containing equality or relational operators on indexed columns. This only applies to tables. Manage a table's columns--a column can be added, removed, or have its type and properties modified, including whether it is dictionary encoded or not.

/alter/table/columns

Mon, 01 Jan 0001 00:00:00 +0000

URL: https://<aws.fqdn>/<aws.cluster.name>/gpudb-0/alter/table/columns Apply various modifications to columns in a table, view. The available modifications include the following: Create or delete an index on a particular column. This can speed up certain operations when using expressions containing equality or relational operators on indexed columns. This only applies to tables. Manage a table's columns--a column can be added, removed, or have its type and properties modified, including whether it is dictionary encoded or not.

/alter/table/metadata

Mon, 01 Jan 0001 00:00:00 +0000

URL: http://<db.host>:<db.port>/alter/table/metadata Updates (adds or changes) metadata for tables. The metadata key and values must both be strings. This is an easy way to annotate whole tables rather than single records within tables. Some examples of metadata are owner of the table, table creation timestamp etc. Input Parameter Description Name Type Description table_names array of strings Names of the tables whose metadata will be updated, in [schema_name.]table_name format, using standard name resolution rules.

/alter/table/metadata

Mon, 01 Jan 0001 00:00:00 +0000

URL: https://<aws.fqdn>/<aws.cluster.name>/gpudb-0/alter/table/metadata Updates (adds or changes) metadata for tables. The metadata key and values must both be strings. This is an easy way to annotate whole tables rather than single records within tables. Some examples of metadata are owner of the table, table creation timestamp etc. Input Parameter Description Name Type Description table_names array of strings Names of the tables whose metadata will be updated, in [schema_name.]table_name format, using standard name resolution rules.

/alter/tablemonitor

Mon, 01 Jan 0001 00:00:00 +0000

URL: http://<db.host>:<db.port>/alter/tablemonitor Alters a table monitor previously created with /create/tablemonitor. Input Parameter Description Name Type Description topic_id string The topic ID returned by /create/tablemonitor. monitor_updates_map map of string to strings Map containing the properties of the table monitor to be updated. Error if empty. Supported Parameters (keys) Parameter Description schema_name Updates the schema name. If schema_name doesn't exist, an error will be thrown. If schema_name is empty, then the user's default schema will be used.

/alter/tablemonitor

Mon, 01 Jan 0001 00:00:00 +0000

URL: https://<aws.fqdn>/<aws.cluster.name>/gpudb-0/alter/tablemonitor Alters a table monitor previously created with /create/tablemonitor. Input Parameter Description Name Type Description topic_id string The topic ID returned by /create/tablemonitor. monitor_updates_map map of string to strings Map containing the properties of the table monitor to be updated. Error if empty. Supported Parameters (keys) Parameter Description schema_name Updates the schema name. If schema_name doesn't exist, an error will be thrown. If schema_name is empty, then the user's default schema will be used.

/alter/tier

Mon, 01 Jan 0001 00:00:00 +0000

URL: http://<db.host>:<db.port>/alter/tier Alters properties of an exisiting tier to facilitate resource management. To disable watermark-based eviction, set both high_watermark and low_watermark to 100. Input Parameter Description Name Type Description name string Name of the tier to be altered. Must be an existing tier group name. options map of string to strings Optional parameters. The default value is an empty map ( {} ). Supported Parameters (keys) Parameter Description capacity Maximum size in bytes this tier may hold at once.

/alter/tier

Mon, 01 Jan 0001 00:00:00 +0000

URL: https://<aws.fqdn>/<aws.cluster.name>/gpudb-0/alter/tier Alters properties of an exisiting tier to facilitate resource management. To disable watermark-based eviction, set both high_watermark and low_watermark to 100. Input Parameter Description Name Type Description name string Name of the tier to be altered. Must be an existing tier group name. options map of string to strings Optional parameters. The default value is an empty map ( {} ). Supported Parameters (keys) Parameter Description capacity Maximum size in bytes this tier may hold at once.

/alter/user

Mon, 01 Jan 0001 00:00:00 +0000

URL: http://<db.host>:<db.port>/alter/user Alters a user. Input Parameter Description Name Type Description name string Name of the user to be altered. Must be an existing user. action string Modification operation to be applied to the user. Supported Values Description set_password Sets the password of the user. The user must be an internal user. set_resource_group Sets the resource group for an internal user. The resource group must exist, otherwise, an empty string assigns the user to the default resource group.

/alter/user

Mon, 01 Jan 0001 00:00:00 +0000

URL: https://<aws.fqdn>/<aws.cluster.name>/gpudb-0/alter/user Alters a user. Input Parameter Description Name Type Description name string Name of the user to be altered. Must be an existing user. action string Modification operation to be applied to the user. Supported Values Description set_password Sets the password of the user. The user must be an internal user. set_resource_group Sets the resource group for an internal user. The resource group must exist, otherwise, an empty string assigns the user to the default resource group.

/alter/video

Mon, 01 Jan 0001 00:00:00 +0000

URL: http://<db.host>:<db.port>/alter/video Alters a video. Input Parameter Description Name Type Description path string Fully-qualified KiFS path to the video to be altered. options map of string to strings Optional parameters. The default value is an empty map ( {} ). Supported Parameters (keys) Parameter Description ttl Sets the TTL of the video. Output Parameter Description The GPUdb server embeds the endpoint response inside a standard response structure which contains status information and the actual response to the query.

/alter/video

Mon, 01 Jan 0001 00:00:00 +0000

URL: https://<aws.fqdn>/<aws.cluster.name>/gpudb-0/alter/video Alters a video. Input Parameter Description Name Type Description path string Fully-qualified KiFS path to the video to be altered. options map of string to strings Optional parameters. The default value is an empty map ( {} ). Supported Parameters (keys) Parameter Description ttl Sets the TTL of the video. Output Parameter Description The GPUdb server embeds the endpoint response inside a standard response structure which contains status information and the actual response to the query.

/append/records

Mon, 01 Jan 0001 00:00:00 +0000

URL: http://<db.host>:<db.port>/append/records Append (or insert) all records from a source table (specified by input parameter source_table_name) to a particular target table (specified by input parameter table_name). The field map (specified by input parameter field_map) holds the user specified map of target table column names with their mapped source column names. Input Parameter Description Name Type Description table_name string The table name for the records to be appended, in [schema_name.]table_name format, using standard name resolution rules.

/append/records

Mon, 01 Jan 0001 00:00:00 +0000

URL: https://<aws.fqdn>/<aws.cluster.name>/gpudb-0/append/records Append (or insert) all records from a source table (specified by input parameter source_table_name) to a particular target table (specified by input parameter table_name). The field map (specified by input parameter field_map) holds the user specified map of target table column names with their mapped source column names. Input Parameter Description Name Type Description table_name string The table name for the records to be appended, in [schema_name.]table_name format, using standard name resolution rules.

/clear/statistics

Mon, 01 Jan 0001 00:00:00 +0000

URL: http://<db.host>:<db.port>/clear/statistics Clears statistics (cardinality, mean value, etc.) for a column in a specified table. Input Parameter Description Name Type Description table_name string Name of a table, in [schema_name.]table_name format, using standard name resolution rules. Must be an existing table. The default value is ''. column_name string Name of the column in input parameter table_name for which to clear statistics. The column must be from an existing table. An empty string clears statistics for all columns in the table.

/clear/statistics

Mon, 01 Jan 0001 00:00:00 +0000

URL: https://<aws.fqdn>/<aws.cluster.name>/gpudb-0/clear/statistics Clears statistics (cardinality, mean value, etc.) for a column in a specified table. Input Parameter Description Name Type Description table_name string Name of a table, in [schema_name.]table_name format, using standard name resolution rules. Must be an existing table. The default value is ''. column_name string Name of the column in input parameter table_name for which to clear statistics. The column must be from an existing table. An empty string clears statistics for all columns in the table.

/clear/table

Mon, 01 Jan 0001 00:00:00 +0000

URL: http://<db.host>:<db.port>/clear/table Clears (drops) one or all tables in the database cluster. The operation is synchronous meaning that the table will be cleared before the function returns. The response payload returns the status of the operation along with the name of the table that was cleared. Input Parameter Description Name Type Description table_name string Name of the table to be cleared, in [schema_name.]table_name format, using standard name resolution rules. Must be an existing table.

/clear/table

Mon, 01 Jan 0001 00:00:00 +0000

URL: https://<aws.fqdn>/<aws.cluster.name>/gpudb-0/clear/table Clears (drops) one or all tables in the database cluster. The operation is synchronous meaning that the table will be cleared before the function returns. The response payload returns the status of the operation along with the name of the table that was cleared. Input Parameter Description Name Type Description table_name string Name of the table to be cleared, in [schema_name.]table_name format, using standard name resolution rules. Must be an existing table.

/clear/tablemonitor

Mon, 01 Jan 0001 00:00:00 +0000

URL: http://<db.host>:<db.port>/clear/tablemonitor Deactivates a table monitor previously created with /create/tablemonitor. Input Parameter Description Name Type Description topic_id string The topic ID returned by /create/tablemonitor. options map of string to strings Optional parameters. The default value is an empty map ( {} ). Supported Parameters (keys) Parameter Description keep_autogenerated_sink If true, the auto-generated datasink associated with this monitor, if there is one, will be retained for further use. If false, then the auto-generated sink will be dropped if there are no other monitors referencing it.

/clear/tablemonitor

Mon, 01 Jan 0001 00:00:00 +0000

URL: https://<aws.fqdn>/<aws.cluster.name>/gpudb-0/clear/tablemonitor Deactivates a table monitor previously created with /create/tablemonitor. Input Parameter Description Name Type Description topic_id string The topic ID returned by /create/tablemonitor. options map of string to strings Optional parameters. The default value is an empty map ( {} ). Supported Parameters (keys) Parameter Description keep_autogenerated_sink If true, the auto-generated datasink associated with this monitor, if there is one, will be retained for further use. If false, then the auto-generated sink will be dropped if there are no other monitors referencing it.

/clear/trigger

Mon, 01 Jan 0001 00:00:00 +0000

URL: http://<db.host>:<db.port>/clear/trigger Clears or cancels the trigger identified by the specified handle. The output returns the handle of the trigger cleared as well as indicating success or failure of the trigger deactivation. Input Parameter Description Name Type Description trigger_id string ID for the trigger to be deactivated. options map of string to strings Optional parameters. The default value is an empty map ( {} ). Output Parameter Description The GPUdb server embeds the endpoint response inside a standard response structure which contains status information and the actual response to the query.

/clear/trigger

Mon, 01 Jan 0001 00:00:00 +0000

URL: https://<aws.fqdn>/<aws.cluster.name>/gpudb-0/clear/trigger Clears or cancels the trigger identified by the specified handle. The output returns the handle of the trigger cleared as well as indicating success or failure of the trigger deactivation. Input Parameter Description Name Type Description trigger_id string ID for the trigger to be deactivated. options map of string to strings Optional parameters. The default value is an empty map ( {} ). Output Parameter Description The GPUdb server embeds the endpoint response inside a standard response structure which contains status information and the actual response to the query.

/collect/statistics

Mon, 01 Jan 0001 00:00:00 +0000

URL: http://<db.host>:<db.port>/collect/statistics Collect statistics for a column(s) in a specified table. Input Parameter Description Name Type Description table_name string Name of a table, in [schema_name.]table_name format, using standard name resolution rules. Must be an existing table. column_names array of strings List of one or more column names in input parameter table_name for which to collect statistics (cardinality, mean value, etc.). options map of string to strings Optional parameters. The default value is an empty map ( {} ).

/collect/statistics

Mon, 01 Jan 0001 00:00:00 +0000

URL: https://<aws.fqdn>/<aws.cluster.name>/gpudb-0/collect/statistics Collect statistics for a column(s) in a specified table. Input Parameter Description Name Type Description table_name string Name of a table, in [schema_name.]table_name format, using standard name resolution rules. Must be an existing table. column_names array of strings List of one or more column names in input parameter table_name for which to collect statistics (cardinality, mean value, etc.). options map of string to strings Optional parameters. The default value is an empty map ( {} ).

/create/credential

Mon, 01 Jan 0001 00:00:00 +0000

URL: http://<db.host>:<db.port>/create/credential Create a new credential. Input Parameter Description Name Type Description credential_name string Name of the credential to be created. Must contain only letters, digits, and underscores, and cannot begin with a digit. Must not match an existing credential name. type string Type of the credential to be created. The supported values are: aws_access_key aws_iam_role azure_ad azure_oauth azure_sas azure_storage_key docker gcs_service_account_id gcs_service_account_keys hdfs jdbc kafka confluent identity string User of the credential to be created.

/create/credential

Mon, 01 Jan 0001 00:00:00 +0000

URL: https://<aws.fqdn>/<aws.cluster.name>/gpudb-0/create/credential Create a new credential. Input Parameter Description Name Type Description credential_name string Name of the credential to be created. Must contain only letters, digits, and underscores, and cannot begin with a digit. Must not match an existing credential name. type string Type of the credential to be created. The supported values are: aws_access_key aws_iam_role azure_ad azure_oauth azure_sas azure_storage_key docker gcs_service_account_id gcs_service_account_keys hdfs jdbc kafka confluent identity string User of the credential to be created.

/create/datasink

Mon, 01 Jan 0001 00:00:00 +0000

URL: http://<db.host>:<db.port>/create/datasink Creates a data sink, which contains the destination information for a data sink that is external to the database. Input Parameter Description Name Type Description name string Name of the data sink to be created. destination string Destination for the output data in format 'storage_provider_type://path[:port]'. Supported storage provider types are 'azure', 'gcs', 'hdfs', 'http', 'https', 'jdbc', 'kafka' and 's3'. options map of string to strings Optional parameters. The default value is an empty map ( {} ).

/create/datasink

Mon, 01 Jan 0001 00:00:00 +0000

URL: https://<aws.fqdn>/<aws.cluster.name>/gpudb-0/create/datasink Creates a data sink, which contains the destination information for a data sink that is external to the database. Input Parameter Description Name Type Description name string Name of the data sink to be created. destination string Destination for the output data in format 'storage_provider_type://path[:port]'. Supported storage provider types are 'azure', 'gcs', 'hdfs', 'http', 'https', 'jdbc', 'kafka' and 's3'. options map of string to strings Optional parameters. The default value is an empty map ( {} ).

/create/datasource

Mon, 01 Jan 0001 00:00:00 +0000

URL: http://<db.host>:<db.port>/create/datasource Creates a data source, which contains the location and connection information for a data store that is external to the database. Input Parameter Description Name Type Description name string Name of the data source to be created. location string Location of the remote storage in 'storage_provider_type://[storage_path[:storage_port]]' format. Supported storage provider types are 'azure','gcs','hdfs','jdbc','kafka', 'confluent' and 's3'. user_name string Name of the remote system user; may be an empty string password string Password for the remote system user; may be an empty string options map of string to strings Optional parameters.

/create/datasource

Mon, 01 Jan 0001 00:00:00 +0000

URL: https://<aws.fqdn>/<aws.cluster.name>/gpudb-0/create/datasource Creates a data source, which contains the location and connection information for a data store that is external to the database. Input Parameter Description Name Type Description name string Name of the data source to be created. location string Location of the remote storage in 'storage_provider_type://[storage_path[:storage_port]]' format. Supported storage provider types are 'azure','gcs','hdfs','jdbc','kafka', 'confluent' and 's3'. user_name string Name of the remote system user; may be an empty string password string Password for the remote system user; may be an empty string options map of string to strings Optional parameters.

/create/directory

Mon, 01 Jan 0001 00:00:00 +0000

URL: http://<db.host>:<db.port>/create/directory Creates a new directory in KiFS. The new directory serves as a location in which the user can upload files using /upload/files. Input Parameter Description Name Type Description directory_name string Name of the directory in KiFS to be created. options map of string to strings Optional parameters. The default value is an empty map ( {} ). Supported Parameters (keys) Parameter Description create_home_directory When set, a home directory is created for the user name provided in the value.

/create/directory

Mon, 01 Jan 0001 00:00:00 +0000

URL: https://<aws.fqdn>/<aws.cluster.name>/gpudb-0/create/directory Creates a new directory in KiFS. The new directory serves as a location in which the user can upload files using /upload/files. Input Parameter Description Name Type Description directory_name string Name of the directory in KiFS to be created. options map of string to strings Optional parameters. The default value is an empty map ( {} ). Supported Parameters (keys) Parameter Description create_home_directory When set, a home directory is created for the user name provided in the value.

/create/environment

Mon, 01 Jan 0001 00:00:00 +0000

URL: http://<db.host>:<db.port>/create/environment Creates a new environment which can be used by user-defined functions (UDF). Input Parameter Description Name Type Description environment_name string Name of the environment to be created. options map of string to strings Optional parameters. The default value is an empty map ( {} ). Output Parameter Description The GPUdb server embeds the endpoint response inside a standard response structure which contains status information and the actual response to the query.

/create/environment

Mon, 01 Jan 0001 00:00:00 +0000

URL: https://<aws.fqdn>/<aws.cluster.name>/gpudb-0/create/environment Creates a new environment which can be used by user-defined functions (UDF). Input Parameter Description Name Type Description environment_name string Name of the environment to be created. options map of string to strings Optional parameters. The default value is an empty map ( {} ). Output Parameter Description The GPUdb server embeds the endpoint response inside a standard response structure which contains status information and the actual response to the query.

/create/graph

Mon, 01 Jan 0001 00:00:00 +0000

URL: http://<db.host>:<db.port>/create/graph Creates a new graph network using given nodes, edges, weights, and restrictions. IMPORTANT: It's highly recommended that you review the Network Graphs & Solvers concepts documentation, the Graph REST Tutorial, and/or some graph examples before using this endpoint. Input Parameter Description Name Type Description graph_name string Name of the graph resource to generate. directed_graph boolean If set to true, the graph will be directed. If set to false, the graph will not be directed.

/create/graph

Mon, 01 Jan 0001 00:00:00 +0000

URL: https://<aws.fqdn>/<aws.cluster.name>/gpudb-0/create/graph Creates a new graph network using given nodes, edges, weights, and restrictions. IMPORTANT: It's highly recommended that you review the Network Graphs & Solvers concepts documentation, the Graph REST Tutorial, and/or some graph examples before using this endpoint. Input Parameter Description Name Type Description graph_name string Name of the graph resource to generate. directed_graph boolean If set to true, the graph will be directed. If set to false, the graph will not be directed.

/create/job

Mon, 01 Jan 0001 00:00:00 +0000

URL: http://<db.host>:<db.port>/create/job Create a job which will run asynchronously. The response returns a job ID, which can be used to query the status and result of the job. The status and the result of the job upon completion can be requested by /get/job. Input Parameter Description Name Type Description endpoint string Indicates which endpoint to execute, e.g. '/alter/table'. request_encoding string The encoding of the request payload for the job. The default value is binary.

/create/job

Mon, 01 Jan 0001 00:00:00 +0000

URL: https://<aws.fqdn>/<aws.cluster.name>/gpudb-0/create/job Create a job which will run asynchronously. The response returns a job ID, which can be used to query the status and result of the job. The status and the result of the job upon completion can be requested by /get/job. Input Parameter Description Name Type Description endpoint string Indicates which endpoint to execute, e.g. '/alter/table'. request_encoding string The encoding of the request payload for the job. The default value is binary.

/create/jointable

Mon, 01 Jan 0001 00:00:00 +0000

URL: http://<db.host>:<db.port>/create/jointable Creates a table that is the result of a SQL JOIN. For join details and examples see: Joins. For limitations, see Join Limitations and Cautions. Input Parameter Description Name Type Description join_table_name string Name of the join table to be created, in [schema_name.]table_name format, using standard name resolution rules and meeting table naming criteria. table_names array of strings The list of table names composing the join, each in [schema_name.

/create/jointable

Mon, 01 Jan 0001 00:00:00 +0000

URL: https://<aws.fqdn>/<aws.cluster.name>/gpudb-0/create/jointable Creates a table that is the result of a SQL JOIN. For join details and examples see: Joins. For limitations, see Join Limitations and Cautions. Input Parameter Description Name Type Description join_table_name string Name of the join table to be created, in [schema_name.]table_name format, using standard name resolution rules and meeting table naming criteria. table_names array of strings The list of table names composing the join, each in [schema_name.

/create/materializedview

Mon, 01 Jan 0001 00:00:00 +0000

URL: http://<db.host>:<db.port>/create/materializedview Initiates the process of creating a materialized view, reserving the view's name to prevent other views or tables from being created with that name. For materialized view details and examples, see Materialized Views. The response contains output parameter view_id, which is used to tag each subsequent operation (projection, union, aggregation, filter, or join) that will compose the view. Input Parameter Description Name Type Description table_name string Name of the table to be created that is the top-level table of the materialized view, in [schema_name.

/create/materializedview

Mon, 01 Jan 0001 00:00:00 +0000

URL: https://<aws.fqdn>/<aws.cluster.name>/gpudb-0/create/materializedview Initiates the process of creating a materialized view, reserving the view's name to prevent other views or tables from being created with that name. For materialized view details and examples, see Materialized Views. The response contains output parameter view_id, which is used to tag each subsequent operation (projection, union, aggregation, filter, or join) that will compose the view. Input Parameter Description Name Type Description table_name string Name of the table to be created that is the top-level table of the materialized view, in [schema_name.

/create/proc

Mon, 01 Jan 0001 00:00:00 +0000

URL: http://<db.host>:<db.port>/create/proc Creates an instance (proc) of the user-defined functions (UDF) specified by the given command, options, and files, and makes it available for execution. Input Parameter Description Name Type Description proc_name string Name of the proc to be created. Must not be the name of a currently existing proc. execution_mode string The execution mode of the proc. The default value is distributed. Supported Values Description distributed Input table data will be divided into data segments that are distributed across all nodes in the cluster, and the proc command will be invoked once per data segment in parallel.

/create/proc

Mon, 01 Jan 0001 00:00:00 +0000

URL: https://<aws.fqdn>/<aws.cluster.name>/gpudb-0/create/proc Creates an instance (proc) of the user-defined functions (UDF) specified by the given command, options, and files, and makes it available for execution. Input Parameter Description Name Type Description proc_name string Name of the proc to be created. Must not be the name of a currently existing proc. execution_mode string The execution mode of the proc. The default value is distributed. Supported Values Description distributed Input table data will be divided into data segments that are distributed across all nodes in the cluster, and the proc command will be invoked once per data segment in parallel.

/create/projection

Mon, 01 Jan 0001 00:00:00 +0000

URL: http://<db.host>:<db.port>/create/projection Creates a new projection of an existing table. A projection represents a subset of the columns (potentially including derived columns) of a table. For projection details and examples, see Projections. For limitations, see Projection Limitations and Cautions. Window functions, which can perform operations like moving averages, are available through this endpoint as well as /get/records/bycolumn. A projection can be created with a different shard key than the source table.

/create/projection

Mon, 01 Jan 0001 00:00:00 +0000

URL: https://<aws.fqdn>/<aws.cluster.name>/gpudb-0/create/projection Creates a new projection of an existing table. A projection represents a subset of the columns (potentially including derived columns) of a table. For projection details and examples, see Projections. For limitations, see Projection Limitations and Cautions. Window functions, which can perform operations like moving averages, are available through this endpoint as well as /get/records/bycolumn. A projection can be created with a different shard key than the source table.

/create/resourcegroup

Mon, 01 Jan 0001 00:00:00 +0000

URL: http://<db.host>:<db.port>/create/resourcegroup Creates a new resource group to facilitate resource management. Input Parameter Description Name Type Description name string Name of the group to be created. Must contain only letters, digits, and underscores, and cannot begin with a digit. Must not match existing resource group name. tier_attributes map of string to maps of string to strings Optional map containing tier names and their respective attribute group limits. The only valid attribute limit that can be set is max_memory (in bytes) for the VRAM & RAM tiers.

/create/resourcegroup

Mon, 01 Jan 0001 00:00:00 +0000

URL: https://<aws.fqdn>/<aws.cluster.name>/gpudb-0/create/resourcegroup Creates a new resource group to facilitate resource management. Input Parameter Description Name Type Description name string Name of the group to be created. Must contain only letters, digits, and underscores, and cannot begin with a digit. Must not match existing resource group name. tier_attributes map of string to maps of string to strings Optional map containing tier names and their respective attribute group limits. The only valid attribute limit that can be set is max_memory (in bytes) for the VRAM & RAM tiers.

/create/role

Mon, 01 Jan 0001 00:00:00 +0000

URL: http://<db.host>:<db.port>/create/role Creates a new role. NOTE: This endpoint should be used for on-premise deployments only. Input Parameter Description Name Type Description name string Name of the role to be created. Must contain only lowercase letters, digits, and underscores, and cannot begin with a digit. Must not be the same name as an existing user or role. options map of string to strings Optional parameters. The default value is an empty map ( {} ).

/create/role

Mon, 01 Jan 0001 00:00:00 +0000

URL: https://<aws.fqdn>/<aws.cluster.name>/gpudb-0/create/role Creates a new role. NOTE: This endpoint should be used for on-premise deployments only. Input Parameter Description Name Type Description name string Name of the role to be created. Must contain only lowercase letters, digits, and underscores, and cannot begin with a digit. Must not be the same name as an existing user or role. options map of string to strings Optional parameters. The default value is an empty map ( {} ).

/create/schema

Mon, 01 Jan 0001 00:00:00 +0000

URL: http://<db.host>:<db.port>/create/schema Creates a SQL-style schema. Schemas are containers for tables and views. Multiple tables and views can be defined with the same name in different schemas. Input Parameter Description Name Type Description schema_name string Name of the schema to be created. Has the same naming restrictions as tables. options map of string to strings Optional parameters. The default value is an empty map ( {} ). Supported Parameters (keys) Parameter Description no_error_if_exists If true, prevents an error from occurring if the schema already exists.

/create/schema

Mon, 01 Jan 0001 00:00:00 +0000

URL: https://<aws.fqdn>/<aws.cluster.name>/gpudb-0/create/schema Creates a SQL-style schema. Schemas are containers for tables and views. Multiple tables and views can be defined with the same name in different schemas. Input Parameter Description Name Type Description schema_name string Name of the schema to be created. Has the same naming restrictions as tables. options map of string to strings Optional parameters. The default value is an empty map ( {} ). Supported Parameters (keys) Parameter Description no_error_if_exists If true, prevents an error from occurring if the schema already exists.

/create/table

Mon, 01 Jan 0001 00:00:00 +0000

URL: http://<db.host>:<db.port>/create/table Creates a new table. If a new table is being created, the type of the table is given by input parameter type_id, which must be the ID of a currently registered type (i.e. one created via /create/type). A table may optionally be designated to use a replicated distribution scheme, or be assigned: foreign keys to other tables, a partitioning scheme, and/or a tier strategy. Input Parameter Description Name Type Description table_name string Name of the table to be created, in [schema_name.

/create/table

Mon, 01 Jan 0001 00:00:00 +0000

URL: https://<aws.fqdn>/<aws.cluster.name>/gpudb-0/create/table Creates a new table. If a new table is being created, the type of the table is given by input parameter type_id, which must be the ID of a currently registered type (i.e. one created via /create/type). A table may optionally be designated to use a replicated distribution scheme, or be assigned: foreign keys to other tables, a partitioning scheme, and/or a tier strategy. Input Parameter Description Name Type Description table_name string Name of the table to be created, in [schema_name.

/create/table/external

Mon, 01 Jan 0001 00:00:00 +0000

URL: http://<db.host>:<db.port>/create/table/external Creates a new external table, which is a local database object whose source data is located externally to the database. The source data can be located either in KiFS; on the cluster, accessible to the database; or remotely, accessible via a pre-defined external data source. The external table can have its structure defined explicitly, via input parameter create_table_options, which contains many of the options from /create/table; or defined implicitly, inferred from the source data.

/create/table/external

Mon, 01 Jan 0001 00:00:00 +0000

URL: https://<aws.fqdn>/<aws.cluster.name>/gpudb-0/create/table/external Creates a new external table, which is a local database object whose source data is located externally to the database. The source data can be located either in KiFS; on the cluster, accessible to the database; or remotely, accessible via a pre-defined external data source. The external table can have its structure defined explicitly, via input parameter create_table_options, which contains many of the options from /create/table; or defined implicitly, inferred from the source data.

/create/tablemonitor

Mon, 01 Jan 0001 00:00:00 +0000

URL: http://<db.host>:<db.port>/create/tablemonitor Creates a monitor that watches for a single table modification event type (insert, update, or delete) on a particular table (identified by input parameter table_name) and forwards event notifications to subscribers via ZMQ. After this call completes, subscribe to the returned output parameter topic_id on the ZMQ table monitor port (default 9002). Each time an operation of the given type on the table completes, a multipart message is published for that topic; the first part contains only the topic ID, and each subsequent part contains one binary-encoded Avro object that corresponds to the event and can be decoded using output parameter type_schema.

/create/tablemonitor

Mon, 01 Jan 0001 00:00:00 +0000

URL: https://<aws.fqdn>/<aws.cluster.name>/gpudb-0/create/tablemonitor Creates a monitor that watches for a single table modification event type (insert, update, or delete) on a particular table (identified by input parameter table_name) and forwards event notifications to subscribers via ZMQ. After this call completes, subscribe to the returned output parameter topic_id on the ZMQ table monitor port (default 9002). Each time an operation of the given type on the table completes, a multipart message is published for that topic; the first part contains only the topic ID, and each subsequent part contains one binary-encoded Avro object that corresponds to the event and can be decoded using output parameter type_schema.

/create/trigger/byarea

Mon, 01 Jan 0001 00:00:00 +0000

URL: http://<db.host>:<db.port>/create/trigger/byarea Sets up an area trigger mechanism for two column_names for one or more tables. (This function is essentially the two-dimensional version of /create/trigger/byrange.) Once the trigger has been activated, any record added to the listed tables(s) via /insert/records with the chosen columns' values falling within the specified region will trip the trigger. All such records will be queued at the trigger port (by default '9001' but able to be retrieved via /show/system/status) for any listening client to collect.

/create/trigger/byarea

Mon, 01 Jan 0001 00:00:00 +0000

URL: https://<aws.fqdn>/<aws.cluster.name>/gpudb-0/create/trigger/byarea Sets up an area trigger mechanism for two column_names for one or more tables. (This function is essentially the two-dimensional version of /create/trigger/byrange.) Once the trigger has been activated, any record added to the listed tables(s) via /insert/records with the chosen columns' values falling within the specified region will trip the trigger. All such records will be queued at the trigger port (by default '9001' but able to be retrieved via /show/system/status) for any listening client to collect.

/create/trigger/byrange

Mon, 01 Jan 0001 00:00:00 +0000

URL: http://<db.host>:<db.port>/create/trigger/byrange Sets up a simple range trigger for a column_name for one or more tables. Once the trigger has been activated, any record added to the listed tables(s) via /insert/records with the chosen column_name's value falling within the specified range will trip the trigger. All such records will be queued at the trigger port (by default '9001' but able to be retrieved via /show/system/status) for any listening client to collect.

/create/trigger/byrange

Mon, 01 Jan 0001 00:00:00 +0000

URL: https://<aws.fqdn>/<aws.cluster.name>/gpudb-0/create/trigger/byrange Sets up a simple range trigger for a column_name for one or more tables. Once the trigger has been activated, any record added to the listed tables(s) via /insert/records with the chosen column_name's value falling within the specified range will trip the trigger. All such records will be queued at the trigger port (by default '9001' but able to be retrieved via /show/system/status) for any listening client to collect.

/create/type

Mon, 01 Jan 0001 00:00:00 +0000

URL: http://<db.host>:<db.port>/create/type Creates a new type describing the layout of a table. The type definition is a JSON string describing the fields (i.e. columns) of the type. Each field consists of a name and a data type. Supported data types are: double, float, int, long, string, and bytes. In addition, one or more properties can be specified for each column which customize the memory usage and query availability of that column.

/create/type

Mon, 01 Jan 0001 00:00:00 +0000

URL: https://<aws.fqdn>/<aws.cluster.name>/gpudb-0/create/type Creates a new type describing the layout of a table. The type definition is a JSON string describing the fields (i.e. columns) of the type. Each field consists of a name and a data type. Supported data types are: double, float, int, long, string, and bytes. In addition, one or more properties can be specified for each column which customize the memory usage and query availability of that column.

/create/union

Mon, 01 Jan 0001 00:00:00 +0000

URL: http://<db.host>:<db.port>/create/union Merges data from one or more tables with comparable data types into a new table. The following merges are supported: UNION (DISTINCT/ALL) - For data set union details and examples, see Union. For limitations, see Union Limitations and Cautions. INTERSECT (DISTINCT/ALL) - For data set intersection details and examples, see Intersect. For limitations, see Intersect Limitations. EXCEPT (DISTINCT/ALL) - For data set subtraction details and examples, see Except.

/create/union

Mon, 01 Jan 0001 00:00:00 +0000

URL: https://<aws.fqdn>/<aws.cluster.name>/gpudb-0/create/union Merges data from one or more tables with comparable data types into a new table. The following merges are supported: UNION (DISTINCT/ALL) - For data set union details and examples, see Union. For limitations, see Union Limitations and Cautions. INTERSECT (DISTINCT/ALL) - For data set intersection details and examples, see Intersect. For limitations, see Intersect Limitations. EXCEPT (DISTINCT/ALL) - For data set subtraction details and examples, see Except.

/create/user/external

Mon, 01 Jan 0001 00:00:00 +0000

URL: http://<db.host>:<db.port>/create/user/external Creates a new external user (a user whose credentials are managed by an external LDAP). NOTE: This endpoint should be used for on-premise deployments only. Input Parameter Description Name Type Description name string Name of the user to be created. Must exactly match the user's name in the external LDAP, prefixed with a @. Must not be the same name as an existing user. options map of string to strings Optional parameters.

/create/user/external

Mon, 01 Jan 0001 00:00:00 +0000

URL: https://<aws.fqdn>/<aws.cluster.name>/gpudb-0/create/user/external Creates a new external user (a user whose credentials are managed by an external LDAP). NOTE: This endpoint should be used for on-premise deployments only. Input Parameter Description Name Type Description name string Name of the user to be created. Must exactly match the user's name in the external LDAP, prefixed with a @. Must not be the same name as an existing user. options map of string to strings Optional parameters.

/create/user/internal

Mon, 01 Jan 0001 00:00:00 +0000

URL: http://<db.host>:<db.port>/create/user/internal Creates a new internal user (a user whose credentials are managed by the database system). Input Parameter Description Name Type Description name string Name of the user to be created. Must contain only lowercase letters, digits, and underscores, and cannot begin with a digit. Must not be the same name as an existing user or role. password string Initial password of the user to be created. May be an empty string for no password.

/create/user/internal

Mon, 01 Jan 0001 00:00:00 +0000

URL: https://<aws.fqdn>/<aws.cluster.name>/gpudb-0/create/user/internal Creates a new internal user (a user whose credentials are managed by the database system). Input Parameter Description Name Type Description name string Name of the user to be created. Must contain only lowercase letters, digits, and underscores, and cannot begin with a digit. Must not be the same name as an existing user or role. password string Initial password of the user to be created. May be an empty string for no password.

/create/video

Mon, 01 Jan 0001 00:00:00 +0000

URL: http://<db.host>:<db.port>/create/video Creates a job to generate a sequence of raster images that visualize data over a specified time. Input Parameter Description Name Type Description attribute string The animated attribute to map to the video's frames. Must be present in the LAYERS specified for the visualization. This is often a time-related field but may be any numeric type. begin string The start point for the video. Accepts an expression evaluable over the input parameter attribute.

/create/video

Mon, 01 Jan 0001 00:00:00 +0000

URL: https://<aws.fqdn>/<aws.cluster.name>/gpudb-0/create/video Creates a job to generate a sequence of raster images that visualize data over a specified time. Input Parameter Description Name Type Description attribute string The animated attribute to map to the video's frames. Must be present in the LAYERS specified for the visualization. This is often a time-related field but may be any numeric type. begin string The start point for the video. Accepts an expression evaluable over the input parameter attribute.

/delete/directory

Mon, 01 Jan 0001 00:00:00 +0000

URL: http://<db.host>:<db.port>/delete/directory Deletes a directory from KiFS. Input Parameter Description Name Type Description directory_name string Name of the directory in KiFS to be deleted. The directory must contain no files, unless recursive is true options map of string to strings Optional parameters. The default value is an empty map ( {} ). Supported Parameters (keys) Parameter Description recursive If true, will delete directory and all files residing in it. If false, directory must be empty for deletion.

/delete/directory

Mon, 01 Jan 0001 00:00:00 +0000

URL: https://<aws.fqdn>/<aws.cluster.name>/gpudb-0/delete/directory Deletes a directory from KiFS. Input Parameter Description Name Type Description directory_name string Name of the directory in KiFS to be deleted. The directory must contain no files, unless recursive is true options map of string to strings Optional parameters. The default value is an empty map ( {} ). Supported Parameters (keys) Parameter Description recursive If true, will delete directory and all files residing in it. If false, directory must be empty for deletion.

/delete/files

Mon, 01 Jan 0001 00:00:00 +0000

URL: http://<db.host>:<db.port>/delete/files Deletes one or more files from KiFS. Input Parameter Description Name Type Description file_names array of strings An array of names of files to be deleted. File paths may contain wildcard characters after the KiFS directory delimeter. Accepted wildcard characters are asterisk (*) to represent any string of zero or more characters, and question mark (?) to indicate a single character. options map of string to strings Optional parameters.

/delete/files

Mon, 01 Jan 0001 00:00:00 +0000

URL: https://<aws.fqdn>/<aws.cluster.name>/gpudb-0/delete/files Deletes one or more files from KiFS. Input Parameter Description Name Type Description file_names array of strings An array of names of files to be deleted. File paths may contain wildcard characters after the KiFS directory delimeter. Accepted wildcard characters are asterisk (*) to represent any string of zero or more characters, and question mark (?) to indicate a single character. options map of string to strings Optional parameters.

/delete/graph

Mon, 01 Jan 0001 00:00:00 +0000

URL: http://<db.host>:<db.port>/delete/graph Deletes an existing graph from the graph server and/or persist. Input Parameter Description Name Type Description graph_name string Name of the graph to be deleted. options map of string to strings Optional parameters. The default value is an empty map ( {} ). Supported Parameters (keys) Parameter Description delete_persist If set to true, the graph is removed from the server and persist. If set to false, the graph is removed from the server but is left in persist.

/delete/graph

Mon, 01 Jan 0001 00:00:00 +0000

URL: https://<aws.fqdn>/<aws.cluster.name>/gpudb-0/delete/graph Deletes an existing graph from the graph server and/or persist. Input Parameter Description Name Type Description graph_name string Name of the graph to be deleted. options map of string to strings Optional parameters. The default value is an empty map ( {} ). Supported Parameters (keys) Parameter Description delete_persist If set to true, the graph is removed from the server and persist. If set to false, the graph is removed from the server but is left in persist.

/delete/proc

Mon, 01 Jan 0001 00:00:00 +0000

URL: http://<db.host>:<db.port>/delete/proc Deletes a proc. Any currently running instances of the proc will be killed. Input Parameter Description Name Type Description proc_name string Name of the proc to be deleted. Must be the name of a currently existing proc. options map of string to strings Optional parameters. The default value is an empty map ( {} ). Output Parameter Description The GPUdb server embeds the endpoint response inside a standard response structure which contains status information and the actual response to the query.

/delete/proc

Mon, 01 Jan 0001 00:00:00 +0000

URL: https://<aws.fqdn>/<aws.cluster.name>/gpudb-0/delete/proc Deletes a proc. Any currently running instances of the proc will be killed. Input Parameter Description Name Type Description proc_name string Name of the proc to be deleted. Must be the name of a currently existing proc. options map of string to strings Optional parameters. The default value is an empty map ( {} ). Output Parameter Description The GPUdb server embeds the endpoint response inside a standard response structure which contains status information and the actual response to the query.

/delete/records

Mon, 01 Jan 0001 00:00:00 +0000

URL: http://<db.host>:<db.port>/delete/records Deletes record(s) matching the provided criteria from the given table. The record selection criteria can either be one or more input parameter expressions (matching multiple records), a single record identified by record_id options, or all records when using delete_all_records. Note that the three selection criteria are mutually exclusive. This operation cannot be run on a view. The operation is synchronous meaning that a response will not be available until the request is completely processed and all the matching records are deleted.

/delete/records

Mon, 01 Jan 0001 00:00:00 +0000

URL: https://<aws.fqdn>/<aws.cluster.name>/gpudb-0/delete/records Deletes record(s) matching the provided criteria from the given table. The record selection criteria can either be one or more input parameter expressions (matching multiple records), a single record identified by record_id options, or all records when using delete_all_records. Note that the three selection criteria are mutually exclusive. This operation cannot be run on a view. The operation is synchronous meaning that a response will not be available until the request is completely processed and all the matching records are deleted.

/delete/resourcegroup

Mon, 01 Jan 0001 00:00:00 +0000

URL: http://<db.host>:<db.port>/delete/resourcegroup Deletes a resource group. Input Parameter Description Name Type Description name string Name of the resource group to be deleted. options map of string to strings Optional parameters. The default value is an empty map ( {} ). Supported Parameters (keys) Parameter Description cascade_delete If true, delete any existing entities owned by this group. Otherwise this request will return an error of any such entities exist. The default value is false.

/delete/resourcegroup

Mon, 01 Jan 0001 00:00:00 +0000

URL: https://<aws.fqdn>/<aws.cluster.name>/gpudb-0/delete/resourcegroup Deletes a resource group. Input Parameter Description Name Type Description name string Name of the resource group to be deleted. options map of string to strings Optional parameters. The default value is an empty map ( {} ). Supported Parameters (keys) Parameter Description cascade_delete If true, delete any existing entities owned by this group. Otherwise this request will return an error of any such entities exist. The default value is false.

/delete/role

Mon, 01 Jan 0001 00:00:00 +0000

URL: http://<db.host>:<db.port>/delete/role Deletes an existing role. NOTE: This endpoint should be used for on-premise deployments only. Input Parameter Description Name Type Description name string Name of the role to be deleted. Must be an existing role. options map of string to strings Optional parameters. The default value is an empty map ( {} ). Output Parameter Description The GPUdb server embeds the endpoint response inside a standard response structure which contains status information and the actual response to the query.

/delete/role

Mon, 01 Jan 0001 00:00:00 +0000

URL: https://<aws.fqdn>/<aws.cluster.name>/gpudb-0/delete/role Deletes an existing role. NOTE: This endpoint should be used for on-premise deployments only. Input Parameter Description Name Type Description name string Name of the role to be deleted. Must be an existing role. options map of string to strings Optional parameters. The default value is an empty map ( {} ). Output Parameter Description The GPUdb server embeds the endpoint response inside a standard response structure which contains status information and the actual response to the query.

/delete/user

Mon, 01 Jan 0001 00:00:00 +0000

URL: http://<db.host>:<db.port>/delete/user Deletes an existing user. NOTE: This endpoint should be used for on-premise deployments only. Input Parameter Description Name Type Description name string Name of the user to be deleted. Must be an existing user. options map of string to strings Optional parameters. The default value is an empty map ( {} ). Output Parameter Description The GPUdb server embeds the endpoint response inside a standard response structure which contains status information and the actual response to the query.

/delete/user

Mon, 01 Jan 0001 00:00:00 +0000

URL: https://<aws.fqdn>/<aws.cluster.name>/gpudb-0/delete/user Deletes an existing user. NOTE: This endpoint should be used for on-premise deployments only. Input Parameter Description Name Type Description name string Name of the user to be deleted. Must be an existing user. options map of string to strings Optional parameters. The default value is an empty map ( {} ). Output Parameter Description The GPUdb server embeds the endpoint response inside a standard response structure which contains status information and the actual response to the query.

/download/files

Mon, 01 Jan 0001 00:00:00 +0000

URL: http://<db.host>:<db.port>/download/files Downloads one or more files from KiFS. Input Parameter Description Name Type Description file_names array of strings An array of the file names to download from KiFS. File paths may contain wildcard characters after the KiFS directory delimeter. Accepted wildcard characters are asterisk (*) to represent any string of zero or more characters, and question mark (?) to indicate a single character. read_offsets array of longs An array of starting byte offsets from which to read each respective file in input parameter file_names.

/download/files

Mon, 01 Jan 0001 00:00:00 +0000

URL: https://<aws.fqdn>/<aws.cluster.name>/gpudb-0/download/files Downloads one or more files from KiFS. Input Parameter Description Name Type Description file_names array of strings An array of the file names to download from KiFS. File paths may contain wildcard characters after the KiFS directory delimeter. Accepted wildcard characters are asterisk (*) to represent any string of zero or more characters, and question mark (?) to indicate a single character. read_offsets array of longs An array of starting byte offsets from which to read each respective file in input parameter file_names.

/drop/credential

Mon, 01 Jan 0001 00:00:00 +0000

URL: http://<db.host>:<db.port>/drop/credential Drop an existing credential. Input Parameter Description Name Type Description credential_name string Name of the credential to be dropped. Must be an existing credential. options map of string to strings Optional parameters. The default value is an empty map ( {} ). Output Parameter Description The GPUdb server embeds the endpoint response inside a standard response structure which contains status information and the actual response to the query.

/drop/credential

Mon, 01 Jan 0001 00:00:00 +0000

URL: https://<aws.fqdn>/<aws.cluster.name>/gpudb-0/drop/credential Drop an existing credential. Input Parameter Description Name Type Description credential_name string Name of the credential to be dropped. Must be an existing credential. options map of string to strings Optional parameters. The default value is an empty map ( {} ). Output Parameter Description The GPUdb server embeds the endpoint response inside a standard response structure which contains status information and the actual response to the query.

/drop/datasink

Mon, 01 Jan 0001 00:00:00 +0000

URL: http://<db.host>:<db.port>/drop/datasink Drops an existing data sink. By default, if any table monitors use this sink as a destination, the request will be blocked unless option clear_table_monitors is true. Input Parameter Description Name Type Description name string Name of the data sink to be dropped. Must be an existing data sink. options map of string to strings Optional parameters. The default value is an empty map ( {} ).

/drop/datasink

Mon, 01 Jan 0001 00:00:00 +0000

URL: https://<aws.fqdn>/<aws.cluster.name>/gpudb-0/drop/datasink Drops an existing data sink. By default, if any table monitors use this sink as a destination, the request will be blocked unless option clear_table_monitors is true. Input Parameter Description Name Type Description name string Name of the data sink to be dropped. Must be an existing data sink. options map of string to strings Optional parameters. The default value is an empty map ( {} ).

/drop/datasource

Mon, 01 Jan 0001 00:00:00 +0000

URL: http://<db.host>:<db.port>/drop/datasource Drops an existing data source. Any external tables that depend on the data source must be dropped before it can be dropped. Input Parameter Description Name Type Description name string Name of the data source to be dropped. Must be an existing data source. options map of string to strings Optional parameters. The default value is an empty map ( {} ). Output Parameter Description The GPUdb server embeds the endpoint response inside a standard response structure which contains status information and the actual response to the query.

/drop/datasource

Mon, 01 Jan 0001 00:00:00 +0000

URL: https://<aws.fqdn>/<aws.cluster.name>/gpudb-0/drop/datasource Drops an existing data source. Any external tables that depend on the data source must be dropped before it can be dropped. Input Parameter Description Name Type Description name string Name of the data source to be dropped. Must be an existing data source. options map of string to strings Optional parameters. The default value is an empty map ( {} ). Output Parameter Description The GPUdb server embeds the endpoint response inside a standard response structure which contains status information and the actual response to the query.

/drop/environment

Mon, 01 Jan 0001 00:00:00 +0000

URL: http://<db.host>:<db.port>/drop/environment Drop an existing user-defined function (UDF) environment. Input Parameter Description Name Type Description environment_name string Name of the environment to be dropped. Must be an existing environment. options map of string to strings Optional parameters. The default value is an empty map ( {} ). Supported Parameters (keys) Parameter Description no_error_if_not_exists If true and if the environment specified in input parameter environment_name does not exist, no error is returned.

/drop/environment

Mon, 01 Jan 0001 00:00:00 +0000

URL: https://<aws.fqdn>/<aws.cluster.name>/gpudb-0/drop/environment Drop an existing user-defined function (UDF) environment. Input Parameter Description Name Type Description environment_name string Name of the environment to be dropped. Must be an existing environment. options map of string to strings Optional parameters. The default value is an empty map ( {} ). Supported Parameters (keys) Parameter Description no_error_if_not_exists If true and if the environment specified in input parameter environment_name does not exist, no error is returned.

/drop/schema

Mon, 01 Jan 0001 00:00:00 +0000

URL: http://<db.host>:<db.port>/drop/schema Drops an existing SQL-style schema, specified in input parameter schema_name. Input Parameter Description Name Type Description schema_name string Name of the schema to be dropped. Must be an existing schema. options map of string to strings Optional parameters. The default value is an empty map ( {} ). Supported Parameters (keys) Parameter Description no_error_if_not_exists If true and if the schema specified in input parameter schema_name does not exist, no error is returned.

/drop/schema

Mon, 01 Jan 0001 00:00:00 +0000

URL: https://<aws.fqdn>/<aws.cluster.name>/gpudb-0/drop/schema Drops an existing SQL-style schema, specified in input parameter schema_name. Input Parameter Description Name Type Description schema_name string Name of the schema to be dropped. Must be an existing schema. options map of string to strings Optional parameters. The default value is an empty map ( {} ). Supported Parameters (keys) Parameter Description no_error_if_not_exists If true and if the schema specified in input parameter schema_name does not exist, no error is returned.

/execute/proc

Mon, 01 Jan 0001 00:00:00 +0000

URL: http://<db.host>:<db.port>/execute/proc Executes a proc. This endpoint is asynchronous and does not wait for the proc to complete before returning. If the proc being executed is distributed, input parameter input_table_names & input parameter input_column_names may be passed to the proc to use for reading data, and input parameter output_table_names may be passed to the proc to use for writing data. If the proc being executed is non-distributed, these table parameters will be ignored.

/execute/proc

Mon, 01 Jan 0001 00:00:00 +0000

URL: https://<aws.fqdn>/<aws.cluster.name>/gpudb-0/execute/proc Executes a proc. This endpoint is asynchronous and does not wait for the proc to complete before returning. If the proc being executed is distributed, input parameter input_table_names & input parameter input_column_names may be passed to the proc to use for reading data, and input parameter output_table_names may be passed to the proc to use for writing data. If the proc being executed is non-distributed, these table parameters will be ignored.

/execute/sql

Mon, 01 Jan 0001 00:00:00 +0000

URL: http://<db.host>:<db.port>/execute/sql Execute a SQL statement (query, DML, or DDL). See SQL Support for the complete set of supported SQL commands. Input Parameter Description Name Type Description statement string SQL statement (query, DML, or DDL) to be executed offset long A positive integer indicating the number of initial results to skip (this can be useful for paging through the results). The default value is 0.The minimum allowed value is 0.

/execute/sql

Mon, 01 Jan 0001 00:00:00 +0000

URL: https://<aws.fqdn>/<aws.cluster.name>/gpudb-0/execute/sql Execute a SQL statement (query, DML, or DDL). See SQL Support for the complete set of supported SQL commands. Input Parameter Description Name Type Description statement string SQL statement (query, DML, or DDL) to be executed offset long A positive integer indicating the number of initial results to skip (this can be useful for paging through the results). The default value is 0.The minimum allowed value is 0.

/export/records/tofiles

Mon, 01 Jan 0001 00:00:00 +0000

URL: http://<db.host>:<db.port>/export/records/tofiles Export records from a table to files. All tables can be exported, in full or partial (see columns_to_export and columns_to_skip). Additional filtering can be applied when using export table with expression through SQL. Default destination is KIFS, though other storage types (Azure, S3, GCS, and HDFS) are supported through datasink_name; see /create/datasink. Server's local file system is not supported. Default file format is delimited text. See options for different file types and different options for each file type.

/export/records/tofiles

Mon, 01 Jan 0001 00:00:00 +0000

URL: https://<aws.fqdn>/<aws.cluster.name>/gpudb-0/export/records/tofiles Export records from a table to files. All tables can be exported, in full or partial (see columns_to_export and columns_to_skip). Additional filtering can be applied when using export table with expression through SQL. Default destination is KIFS, though other storage types (Azure, S3, GCS, and HDFS) are supported through datasink_name; see /create/datasink. Server's local file system is not supported. Default file format is delimited text. See options for different file types and different options for each file type.

/export/records/totable

Mon, 01 Jan 0001 00:00:00 +0000

URL: http://<db.host>:<db.port>/export/records/totable Exports records from source table to the specified target table in an external database Input Parameter Description Name Type Description table_name string Name of the table from which the data will be exported to remote database, in [schema_name.]table_name format, using standard name resolution rules. remote_query string Parameterized insert query to export gpudb table data into remote database. The default value is ''. options map of string to strings Optional parameters.

/export/records/totable

Mon, 01 Jan 0001 00:00:00 +0000

URL: https://<aws.fqdn>/<aws.cluster.name>/gpudb-0/export/records/totable Exports records from source table to the specified target table in an external database Input Parameter Description Name Type Description table_name string Name of the table from which the data will be exported to remote database, in [schema_name.]table_name format, using standard name resolution rules. remote_query string Parameterized insert query to export gpudb table data into remote database. The default value is ''. options map of string to strings Optional parameters.

/filter

Mon, 01 Jan 0001 00:00:00 +0000

URL: http://<db.host>:<db.port>/filter Filters data based on the specified expression. The results are stored in a result set with the given input parameter view_name. For details see Expressions. The response message contains the number of points for which the expression evaluated to be true, which is equivalent to the size of the result view. Input Parameter Description Name Type Description table_name string Name of the table to filter, in [schema_name.]table_name format, using standard name resolution rules.

/filter

Mon, 01 Jan 0001 00:00:00 +0000

URL: https://<aws.fqdn>/<aws.cluster.name>/gpudb-0/filter Filters data based on the specified expression. The results are stored in a result set with the given input parameter view_name. For details see Expressions. The response message contains the number of points for which the expression evaluated to be true, which is equivalent to the size of the result view. Input Parameter Description Name Type Description table_name string Name of the table to filter, in [schema_name.]table_name format, using standard name resolution rules.

/filter/byarea

Mon, 01 Jan 0001 00:00:00 +0000

URL: http://<db.host>:<db.port>/filter/byarea Calculates which objects from a table are within a named area of interest (NAI/polygon). The operation is synchronous, meaning that a response will not be returned until all the matching objects are fully available. The response payload provides the count of the resulting set. A new resultant set (view) which satisfies the input NAI restriction specification is created with the name input parameter view_name passed in as part of the input.

/filter/byarea

Mon, 01 Jan 0001 00:00:00 +0000

URL: https://<aws.fqdn>/<aws.cluster.name>/gpudb-0/filter/byarea Calculates which objects from a table are within a named area of interest (NAI/polygon). The operation is synchronous, meaning that a response will not be returned until all the matching objects are fully available. The response payload provides the count of the resulting set. A new resultant set (view) which satisfies the input NAI restriction specification is created with the name input parameter view_name passed in as part of the input.

/filter/byarea/geometry

Mon, 01 Jan 0001 00:00:00 +0000

URL: http://<db.host>:<db.port>/filter/byarea/geometry Calculates which geospatial geometry objects from a table intersect a named area of interest (NAI/polygon). The operation is synchronous, meaning that a response will not be returned until all the matching objects are fully available. The response payload provides the count of the resulting set. A new resultant set (view) which satisfies the input NAI restriction specification is created with the name input parameter view_name passed in as part of the input.

/filter/byarea/geometry

Mon, 01 Jan 0001 00:00:00 +0000

URL: https://<aws.fqdn>/<aws.cluster.name>/gpudb-0/filter/byarea/geometry Calculates which geospatial geometry objects from a table intersect a named area of interest (NAI/polygon). The operation is synchronous, meaning that a response will not be returned until all the matching objects are fully available. The response payload provides the count of the resulting set. A new resultant set (view) which satisfies the input NAI restriction specification is created with the name input parameter view_name passed in as part of the input.

/filter/bybox

Mon, 01 Jan 0001 00:00:00 +0000

URL: http://<db.host>:<db.port>/filter/bybox Calculates how many objects within the given table lie in a rectangular box. The operation is synchronous, meaning that a response will not be returned until all the objects are fully available. The response payload provides the count of the resulting set. A new resultant set which satisfies the input NAI restriction specification is also created when a input parameter view_name is passed in as part of the input payload.

/filter/bybox

Mon, 01 Jan 0001 00:00:00 +0000

URL: https://<aws.fqdn>/<aws.cluster.name>/gpudb-0/filter/bybox Calculates how many objects within the given table lie in a rectangular box. The operation is synchronous, meaning that a response will not be returned until all the objects are fully available. The response payload provides the count of the resulting set. A new resultant set which satisfies the input NAI restriction specification is also created when a input parameter view_name is passed in as part of the input payload.

/filter/bybox/geometry

Mon, 01 Jan 0001 00:00:00 +0000

URL: http://<db.host>:<db.port>/filter/bybox/geometry Calculates which geospatial geometry objects from a table intersect a rectangular box. The operation is synchronous, meaning that a response will not be returned until all the objects are fully available. The response payload provides the count of the resulting set. A new resultant set which satisfies the input NAI restriction specification is also created when a input parameter view_name is passed in as part of the input payload.

/filter/bybox/geometry

Mon, 01 Jan 0001 00:00:00 +0000

URL: https://<aws.fqdn>/<aws.cluster.name>/gpudb-0/filter/bybox/geometry Calculates which geospatial geometry objects from a table intersect a rectangular box. The operation is synchronous, meaning that a response will not be returned until all the objects are fully available. The response payload provides the count of the resulting set. A new resultant set which satisfies the input NAI restriction specification is also created when a input parameter view_name is passed in as part of the input payload.

/filter/bygeometry

Mon, 01 Jan 0001 00:00:00 +0000

URL: http://<db.host>:<db.port>/filter/bygeometry Applies a geometry filter against a geospatial geometry column in a given table or view. The filtering geometry is provided by input parameter input_wkt. Input Parameter Description Name Type Description table_name string Name of the table on which the filter by geometry will be performed, in [schema_name.]table_name format, using standard name resolution rules. Must be an existing table or view containing a geospatial geometry column. view_name string If provided, then this will be the name of the view containing the results, in [schema_name.

/filter/bygeometry

Mon, 01 Jan 0001 00:00:00 +0000

URL: https://<aws.fqdn>/<aws.cluster.name>/gpudb-0/filter/bygeometry Applies a geometry filter against a geospatial geometry column in a given table or view. The filtering geometry is provided by input parameter input_wkt. Input Parameter Description Name Type Description table_name string Name of the table on which the filter by geometry will be performed, in [schema_name.]table_name format, using standard name resolution rules. Must be an existing table or view containing a geospatial geometry column. view_name string If provided, then this will be the name of the view containing the results, in [schema_name.

/filter/bylist

Mon, 01 Jan 0001 00:00:00 +0000

URL: http://<db.host>:<db.port>/filter/bylist Calculates which records from a table have values in the given list for the corresponding column. The operation is synchronous, meaning that a response will not be returned until all the objects are fully available. The response payload provides the count of the resulting set. A new resultant set (view) which satisfies the input filter specification is also created if a input parameter view_name is passed in as part of the request.

/filter/bylist

Mon, 01 Jan 0001 00:00:00 +0000

URL: https://<aws.fqdn>/<aws.cluster.name>/gpudb-0/filter/bylist Calculates which records from a table have values in the given list for the corresponding column. The operation is synchronous, meaning that a response will not be returned until all the objects are fully available. The response payload provides the count of the resulting set. A new resultant set (view) which satisfies the input filter specification is also created if a input parameter view_name is passed in as part of the request.

/filter/byradius

Mon, 01 Jan 0001 00:00:00 +0000

URL: http://<db.host>:<db.port>/filter/byradius Calculates which objects from a table lie within a circle with the given radius and center point (i.e. circular NAI). The operation is synchronous, meaning that a response will not be returned until all the objects are fully available. The response payload provides the count of the resulting set. A new resultant set (view) which satisfies the input circular NAI restriction specification is also created if a input parameter view_name is passed in as part of the request.

/filter/byradius

Mon, 01 Jan 0001 00:00:00 +0000

URL: https://<aws.fqdn>/<aws.cluster.name>/gpudb-0/filter/byradius Calculates which objects from a table lie within a circle with the given radius and center point (i.e. circular NAI). The operation is synchronous, meaning that a response will not be returned until all the objects are fully available. The response payload provides the count of the resulting set. A new resultant set (view) which satisfies the input circular NAI restriction specification is also created if a input parameter view_name is passed in as part of the request.

/filter/byradius/geometry

Mon, 01 Jan 0001 00:00:00 +0000

URL: http://<db.host>:<db.port>/filter/byradius/geometry Calculates which geospatial geometry objects from a table intersect a circle with the given radius and center point (i.e. circular NAI). The operation is synchronous, meaning that a response will not be returned until all the objects are fully available. The response payload provides the count of the resulting set. A new resultant set (view) which satisfies the input circular NAI restriction specification is also created if a input parameter view_name is passed in as part of the request.

/filter/byradius/geometry

Mon, 01 Jan 0001 00:00:00 +0000

URL: https://<aws.fqdn>/<aws.cluster.name>/gpudb-0/filter/byradius/geometry Calculates which geospatial geometry objects from a table intersect a circle with the given radius and center point (i.e. circular NAI). The operation is synchronous, meaning that a response will not be returned until all the objects are fully available. The response payload provides the count of the resulting set. A new resultant set (view) which satisfies the input circular NAI restriction specification is also created if a input parameter view_name is passed in as part of the request.

/filter/byrange

Mon, 01 Jan 0001 00:00:00 +0000

URL: http://<db.host>:<db.port>/filter/byrange Calculates which objects from a table have a column that is within the given bounds. An object from the table identified by input parameter table_name is added to the view input parameter view_name if its column is within [input parameter lower_bound, input parameter upper_bound] (inclusive). The operation is synchronous. The response provides a count of the number of objects which passed the bound filter. Although this functionality can also be accomplished with the standard filter function, it is more efficient.

/filter/byrange

Mon, 01 Jan 0001 00:00:00 +0000

URL: https://<aws.fqdn>/<aws.cluster.name>/gpudb-0/filter/byrange Calculates which objects from a table have a column that is within the given bounds. An object from the table identified by input parameter table_name is added to the view input parameter view_name if its column is within [input parameter lower_bound, input parameter upper_bound] (inclusive). The operation is synchronous. The response provides a count of the number of objects which passed the bound filter. Although this functionality can also be accomplished with the standard filter function, it is more efficient.

/filter/byseries

Mon, 01 Jan 0001 00:00:00 +0000

URL: http://<db.host>:<db.port>/filter/byseries Filters objects matching all points of the given track (works only on track type data). It allows users to specify a particular track to find all other points in the table that fall within specified ranges (spatial and temporal) of all points of the given track. Additionally, the user can specify another track to see if the two intersect (or go close to each other within the specified ranges).

/filter/byseries

Mon, 01 Jan 0001 00:00:00 +0000

URL: https://<aws.fqdn>/<aws.cluster.name>/gpudb-0/filter/byseries Filters objects matching all points of the given track (works only on track type data). It allows users to specify a particular track to find all other points in the table that fall within specified ranges (spatial and temporal) of all points of the given track. Additionally, the user can specify another track to see if the two intersect (or go close to each other within the specified ranges).

/filter/bystring

Mon, 01 Jan 0001 00:00:00 +0000

URL: http://<db.host>:<db.port>/filter/bystring Calculates which objects from a table or view match a string expression for the given string columns. Setting case_sensitive can modify case sensitivity in matching for all modes except search. For search mode details and limitations, see Full Text Search. Input Parameter Description Name Type Description table_name string Name of the table on which the filter operation will be performed, in [schema_name.]table_name format, using standard name resolution rules.

/filter/bystring

Mon, 01 Jan 0001 00:00:00 +0000

URL: https://<aws.fqdn>/<aws.cluster.name>/gpudb-0/filter/bystring Calculates which objects from a table or view match a string expression for the given string columns. Setting case_sensitive can modify case sensitivity in matching for all modes except search. For search mode details and limitations, see Full Text Search. Input Parameter Description Name Type Description table_name string Name of the table on which the filter operation will be performed, in [schema_name.]table_name format, using standard name resolution rules.

/filter/bytable

Mon, 01 Jan 0001 00:00:00 +0000

URL: http://<db.host>:<db.port>/filter/bytable Filters objects in one table based on objects in another table. The user must specify matching column types from the two tables (i.e. the target table from which objects will be filtered and the source table based on which the filter will be created); the column names need not be the same. If a input parameter view_name is specified, then the filtered objects will then be put in a newly created view.

/filter/bytable

Mon, 01 Jan 0001 00:00:00 +0000

URL: https://<aws.fqdn>/<aws.cluster.name>/gpudb-0/filter/bytable Filters objects in one table based on objects in another table. The user must specify matching column types from the two tables (i.e. the target table from which objects will be filtered and the source table based on which the filter will be created); the column names need not be the same. If a input parameter view_name is specified, then the filtered objects will then be put in a newly created view.

/filter/byvalue

Mon, 01 Jan 0001 00:00:00 +0000

URL: http://<db.host>:<db.port>/filter/byvalue Calculates which objects from a table has a particular value for a particular column. The input parameters provide a way to specify either a String or a Double valued column and a desired value for the column on which the filter is performed. The operation is synchronous, meaning that a response will not be returned until all the objects are fully available. The response payload provides the count of the resulting set.

/filter/byvalue

Mon, 01 Jan 0001 00:00:00 +0000

URL: https://<aws.fqdn>/<aws.cluster.name>/gpudb-0/filter/byvalue Calculates which objects from a table has a particular value for a particular column. The input parameters provide a way to specify either a String or a Double valued column and a desired value for the column on which the filter is performed. The operation is synchronous, meaning that a response will not be returned until all the objects are fully available. The response payload provides the count of the resulting set.

/get/job

Mon, 01 Jan 0001 00:00:00 +0000

URL: http://<db.host>:<db.port>/get/job Get the status and result of asynchronously running job. See the /create/job for starting an asynchronous job. Some fields of the response are filled only after the submitted job has finished execution. Input Parameter Description Name Type Description job_id long A unique identifier for the job whose status and result is to be fetched. options map of string to strings Optional parameters. The default value is an empty map ( {} ).

/get/job

Mon, 01 Jan 0001 00:00:00 +0000

URL: https://<aws.fqdn>/<aws.cluster.name>/gpudb-0/get/job Get the status and result of asynchronously running job. See the /create/job for starting an asynchronous job. Some fields of the response are filled only after the submitted job has finished execution. Input Parameter Description Name Type Description job_id long A unique identifier for the job whose status and result is to be fetched. options map of string to strings Optional parameters. The default value is an empty map ( {} ).

/get/records

Mon, 01 Jan 0001 00:00:00 +0000

URL: http://<db.host>:<db.port>/get/records Retrieves records from a given table, optionally filtered by an expression and/or sorted by a column. This operation can be performed on tables and views. Records can be returned encoded as binary, json, or geojson. This operation supports paging through the data via the input parameter offset and input parameter limit parameters. Note that when paging through a table, if the table (or the underlying table in case of a view) is updated (records are inserted, deleted or modified) the records retrieved may differ between calls based on the updates applied.

/get/records

Mon, 01 Jan 0001 00:00:00 +0000

URL: https://<aws.fqdn>/<aws.cluster.name>/gpudb-0/get/records Retrieves records from a given table, optionally filtered by an expression and/or sorted by a column. This operation can be performed on tables and views. Records can be returned encoded as binary, json, or geojson. This operation supports paging through the data via the input parameter offset and input parameter limit parameters. Note that when paging through a table, if the table (or the underlying table in case of a view) is updated (records are inserted, deleted or modified) the records retrieved may differ between calls based on the updates applied.

/get/records/bycolumn

Mon, 01 Jan 0001 00:00:00 +0000

URL: http://<db.host>:<db.port>/get/records/bycolumn For a given table, retrieves the values from the requested column(s). Maps of column name to the array of values as well as the column data type are returned. This endpoint supports pagination with the input parameter offset and input parameter limit parameters. Window functions, which can perform operations like moving averages, are available through this endpoint as well as /create/projection. When using pagination, if the table (or the underlying table in the case of a view) is modified (records are inserted, updated, or deleted) during a call to the endpoint, the records or values retrieved may differ between calls based on the type of the update, e.

/get/records/bycolumn

Mon, 01 Jan 0001 00:00:00 +0000

URL: https://<aws.fqdn>/<aws.cluster.name>/gpudb-0/get/records/bycolumn For a given table, retrieves the values from the requested column(s). Maps of column name to the array of values as well as the column data type are returned. This endpoint supports pagination with the input parameter offset and input parameter limit parameters. Window functions, which can perform operations like moving averages, are available through this endpoint as well as /create/projection. When using pagination, if the table (or the underlying table in the case of a view) is modified (records are inserted, updated, or deleted) during a call to the endpoint, the records or values retrieved may differ between calls based on the type of the update, e.

/get/records/byseries

Mon, 01 Jan 0001 00:00:00 +0000

URL: http://<db.host>:<db.port>/get/records/byseries Retrieves the complete series/track records from the given input parameter world_table_name based on the partial track information contained in the input parameter table_name. This operation supports paging through the data via the input parameter offset and input parameter limit parameters. In contrast to /get/records this returns records grouped by series/track. So if input parameter offset is 0 and input parameter limit is 5 this operation would return the first 5 series/tracks in input parameter table_name.

/get/records/byseries

Mon, 01 Jan 0001 00:00:00 +0000

URL: https://<aws.fqdn>/<aws.cluster.name>/gpudb-0/get/records/byseries Retrieves the complete series/track records from the given input parameter world_table_name based on the partial track information contained in the input parameter table_name. This operation supports paging through the data via the input parameter offset and input parameter limit parameters. In contrast to /get/records this returns records grouped by series/track. So if input parameter offset is 0 and input parameter limit is 5 this operation would return the first 5 series/tracks in input parameter table_name.

/get/records/fromcollection

Mon, 01 Jan 0001 00:00:00 +0000

URL: http://<db.host>:<db.port>/get/records/fromcollection Retrieves records from a collection. The operation can optionally return the record IDs which can be used in certain queries such as /delete/records. This operation supports paging through the data via the input parameter offset and input parameter limit parameters. Note that when using the Java API, it is not possible to retrieve records from join views using this operation. (DEPRECATED) Input Parameter Description Name Type Description table_name string Name of the collection or table from which records are to be retrieved, in [schema_name.

/get/records/fromcollection

Mon, 01 Jan 0001 00:00:00 +0000

URL: https://<aws.fqdn>/<aws.cluster.name>/gpudb-0/get/records/fromcollection Retrieves records from a collection. The operation can optionally return the record IDs which can be used in certain queries such as /delete/records. This operation supports paging through the data via the input parameter offset and input parameter limit parameters. Note that when using the Java API, it is not possible to retrieve records from join views using this operation. (DEPRECATED) Input Parameter Description Name Type Description table_name string Name of the collection or table from which records are to be retrieved, in [schema_name.

/get/records/json

Mon, 01 Jan 0001 00:00:00 +0000

URL: http://<db.host>:<db.port>/get/records/json Overview Usage Parameters Examples Responses Overview Kinetica provides a direct JSON egress service to allow records to be retrieved as raw JSON from the database. Several options can be used to identify & filter the data being requested. There is also limited support for aggregation. JSON objects will be returned as an array: Single or Multiple Records 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 [ { "id": 1, "category": "Furniture", "name": "Clamp-on Lamps", "description": "Strong, steadfast fasteners; localized lighting for laboring", "stock": 10 }, { "id": 14, "category": "Technology", "name": "Dot Matrix Printers", "description": "Impactful industrial implements for impressing ink iteratively", "stock": 27 } ] For examples, see Examples or JSON Egress Snippets.

/get/records/json

Mon, 01 Jan 0001 00:00:00 +0000

URL: https://<aws.fqdn>/<aws.cluster.name>/gpudb-0/get/records/json Overview Usage Parameters Examples Responses Overview Kinetica provides a direct JSON egress service to allow records to be retrieved as raw JSON from the database. Several options can be used to identify & filter the data being requested. There is also limited support for aggregation. JSON objects will be returned as an array: Single or Multiple Records 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 [ { "id": 1, "category": "Furniture", "name": "Clamp-on Lamps", "description": "Strong, steadfast fasteners; localized lighting for laboring", "stock": 10 }, { "id": 14, "category": "Technology", "name": "Dot Matrix Printers", "description": "Impactful industrial implements for impressing ink iteratively", "stock": 27 } ] For examples, see Examples or JSON Egress Snippets.

/grant/permission

Mon, 01 Jan 0001 00:00:00 +0000

URL: http://<db.host>:<db.port>/grant/permission Grant user or role the specified permission on the specified object. Input Parameter Description Name Type Description principal string Name of the user or role for which the permission is being granted. Must be an existing user or role. The default value is ''. object string Name of object permission is being granted to. It is recommended to use a fully-qualified name when possible. object_type string The type of object being granted to

/grant/permission

Mon, 01 Jan 0001 00:00:00 +0000

URL: https://<aws.fqdn>/<aws.cluster.name>/gpudb-0/grant/permission Grant user or role the specified permission on the specified object. Input Parameter Description Name Type Description principal string Name of the user or role for which the permission is being granted. Must be an existing user or role. The default value is ''. object string Name of object permission is being granted to. It is recommended to use a fully-qualified name when possible. object_type string The type of object being granted to

/grant/permission/credential

Mon, 01 Jan 0001 00:00:00 +0000

URL: http://<db.host>:<db.port>/grant/permission/credential Grants a credential-level permission to a user or role. Input Parameter Description Name Type Description name string Name of the user or role to which the permission will be granted. Must be an existing user or role. permission string Permission to grant to the user or role. Supported Values Description credential_admin Full read/write and administrative access on the credential. credential_read Ability to read and use the credential. credential_name string Name of the credential on which the permission will be granted.

/grant/permission/credential

Mon, 01 Jan 0001 00:00:00 +0000

URL: https://<aws.fqdn>/<aws.cluster.name>/gpudb-0/grant/permission/credential Grants a credential-level permission to a user or role. Input Parameter Description Name Type Description name string Name of the user or role to which the permission will be granted. Must be an existing user or role. permission string Permission to grant to the user or role. Supported Values Description credential_admin Full read/write and administrative access on the credential. credential_read Ability to read and use the credential. credential_name string Name of the credential on which the permission will be granted.

/grant/permission/datasource

Mon, 01 Jan 0001 00:00:00 +0000

URL: http://<db.host>:<db.port>/grant/permission/datasource Grants a data source permission to a user or role. Input Parameter Description Name Type Description name string Name of the user or role to which the permission will be granted. Must be an existing user or role. permission string Permission to grant to the user or role Supported Values Description admin Admin access on the given data source connect Connect access on the given data source datasource_name string Name of the data source on which the permission will be granted.

/grant/permission/datasource

Mon, 01 Jan 0001 00:00:00 +0000

URL: https://<aws.fqdn>/<aws.cluster.name>/gpudb-0/grant/permission/datasource Grants a data source permission to a user or role. Input Parameter Description Name Type Description name string Name of the user or role to which the permission will be granted. Must be an existing user or role. permission string Permission to grant to the user or role Supported Values Description admin Admin access on the given data source connect Connect access on the given data source datasource_name string Name of the data source on which the permission will be granted.

/grant/permission/directory

Mon, 01 Jan 0001 00:00:00 +0000

URL: http://<db.host>:<db.port>/grant/permission/directory Grants a KiFS directory-level permission to a user or role. Input Parameter Description Name Type Description name string Name of the user or role to which the permission will be granted. Must be an existing user or role. permission string Permission to grant to the user or role. Supported Values Description directory_read For files in the directory, access to list files, download files, or use files in server side functions directory_write Access to upload files to, or delete files from, the directory.

/grant/permission/directory

Mon, 01 Jan 0001 00:00:00 +0000

URL: https://<aws.fqdn>/<aws.cluster.name>/gpudb-0/grant/permission/directory Grants a KiFS directory-level permission to a user or role. Input Parameter Description Name Type Description name string Name of the user or role to which the permission will be granted. Must be an existing user or role. permission string Permission to grant to the user or role. Supported Values Description directory_read For files in the directory, access to list files, download files, or use files in server side functions directory_write Access to upload files to, or delete files from, the directory.

/grant/permission/proc

Mon, 01 Jan 0001 00:00:00 +0000

URL: http://<db.host>:<db.port>/grant/permission/proc Grants a proc-level permission to a user or role. Input Parameter Description Name Type Description name string Name of the user or role to which the permission will be granted. Must be an existing user or role. permission string Permission to grant to the user or role. Supported Values Description proc_admin Admin access to the proc. proc_execute Execute access to the proc. proc_name string Name of the proc to which the permission grants access.

/grant/permission/proc

Mon, 01 Jan 0001 00:00:00 +0000

URL: https://<aws.fqdn>/<aws.cluster.name>/gpudb-0/grant/permission/proc Grants a proc-level permission to a user or role. Input Parameter Description Name Type Description name string Name of the user or role to which the permission will be granted. Must be an existing user or role. permission string Permission to grant to the user or role. Supported Values Description proc_admin Admin access to the proc. proc_execute Execute access to the proc. proc_name string Name of the proc to which the permission grants access.

/grant/permission/system

Mon, 01 Jan 0001 00:00:00 +0000

URL: http://<db.host>:<db.port>/grant/permission/system Grants a system-level permission to a user or role. Input Parameter Description Name Type Description name string Name of the user or role to which the permission will be granted. Must be an existing user or role. permission string Permission to grant to the user or role. Supported Values Description system_admin Full access to all data and system functions. system_user_admin Access to administer users and roles that do not have system_admin permission.

/grant/permission/system

Mon, 01 Jan 0001 00:00:00 +0000

URL: https://<aws.fqdn>/<aws.cluster.name>/gpudb-0/grant/permission/system Grants a system-level permission to a user or role. Input Parameter Description Name Type Description name string Name of the user or role to which the permission will be granted. Must be an existing user or role. permission string Permission to grant to the user or role. Supported Values Description system_admin Full access to all data and system functions. system_user_admin Access to administer users and roles that do not have system_admin permission.

/grant/permission/table

Mon, 01 Jan 0001 00:00:00 +0000

URL: http://<db.host>:<db.port>/grant/permission/table Grants a table-level permission to a user or role. Input Parameter Description Name Type Description name string Name of the user or role to which the permission will be granted. Must be an existing user or role. permission string Permission to grant to the user or role. Supported Values Description table_admin Full read/write and administrative access to the table. table_insert Insert access to the table. table_update Update access to the table.

/grant/permission/table

Mon, 01 Jan 0001 00:00:00 +0000

URL: https://<aws.fqdn>/<aws.cluster.name>/gpudb-0/grant/permission/table Grants a table-level permission to a user or role. Input Parameter Description Name Type Description name string Name of the user or role to which the permission will be granted. Must be an existing user or role. permission string Permission to grant to the user or role. Supported Values Description table_admin Full read/write and administrative access to the table. table_insert Insert access to the table. table_update Update access to the table.

/grant/role

Mon, 01 Jan 0001 00:00:00 +0000

URL: http://<db.host>:<db.port>/grant/role Grants membership in a role to a user or role. Input Parameter Description Name Type Description role string Name of the role in which membership will be granted. Must be an existing role. member string Name of the user or role that will be granted membership in input parameter role. Must be an existing user or role. options map of string to strings Optional parameters. The default value is an empty map ( {} ).

/grant/role

Mon, 01 Jan 0001 00:00:00 +0000

URL: https://<aws.fqdn>/<aws.cluster.name>/gpudb-0/grant/role Grants membership in a role to a user or role. Input Parameter Description Name Type Description role string Name of the role in which membership will be granted. Must be an existing role. member string Name of the user or role that will be granted membership in input parameter role. Must be an existing user or role. options map of string to strings Optional parameters. The default value is an empty map ( {} ).

/has/permission

Mon, 01 Jan 0001 00:00:00 +0000

URL: http://<db.host>:<db.port>/has/permission Checks if the specified user has the specified permission on the specified object. Input Parameter Description Name Type Description principal string Name of the user for which the permission is being checked. Must be an existing user. If blank, will use the current user. The default value is ''. object string Name of object to check for the requested permission. It is recommended to use a fully-qualified name when possible.

/has/permission

Mon, 01 Jan 0001 00:00:00 +0000

URL: https://<aws.fqdn>/<aws.cluster.name>/gpudb-0/has/permission Checks if the specified user has the specified permission on the specified object. Input Parameter Description Name Type Description principal string Name of the user for which the permission is being checked. Must be an existing user. If blank, will use the current user. The default value is ''. object string Name of object to check for the requested permission. It is recommended to use a fully-qualified name when possible.

/has/proc

Mon, 01 Jan 0001 00:00:00 +0000

URL: http://<db.host>:<db.port>/has/proc Checks the existence of a proc with the given name. Input Parameter Description Name Type Description proc_name string Name of the proc to check for existence. options map of string to strings Optional parameters. The default value is an empty map ( {} ). Output Parameter Description The GPUdb server embeds the endpoint response inside a standard response structure which contains status information and the actual response to the query.

/has/proc

Mon, 01 Jan 0001 00:00:00 +0000

URL: https://<aws.fqdn>/<aws.cluster.name>/gpudb-0/has/proc Checks the existence of a proc with the given name. Input Parameter Description Name Type Description proc_name string Name of the proc to check for existence. options map of string to strings Optional parameters. The default value is an empty map ( {} ). Output Parameter Description The GPUdb server embeds the endpoint response inside a standard response structure which contains status information and the actual response to the query.

/has/role

Mon, 01 Jan 0001 00:00:00 +0000

URL: http://<db.host>:<db.port>/has/role Checks if the specified user has the specified role. Input Parameter Description Name Type Description principal string Name of the user for which role membersih is being checked. Must be an existing user. If blank, will use the current user. The default value is ''. role string Name of role to check for membership. options map of string to strings Optional parameters. The default value is an empty map ( {} ).

/has/role

Mon, 01 Jan 0001 00:00:00 +0000

URL: https://<aws.fqdn>/<aws.cluster.name>/gpudb-0/has/role Checks if the specified user has the specified role. Input Parameter Description Name Type Description principal string Name of the user for which role membersih is being checked. Must be an existing user. If blank, will use the current user. The default value is ''. role string Name of role to check for membership. options map of string to strings Optional parameters. The default value is an empty map ( {} ).

/has/schema

Mon, 01 Jan 0001 00:00:00 +0000

URL: http://<db.host>:<db.port>/has/schema Checks for the existence of a schema with the given name. Input Parameter Description Name Type Description schema_name string Name of the schema to check for existence, in root, using standard name resolution rules. options map of string to strings Optional parameters. The default value is an empty map ( {} ). Output Parameter Description The GPUdb server embeds the endpoint response inside a standard response structure which contains status information and the actual response to the query.

/has/schema

Mon, 01 Jan 0001 00:00:00 +0000

URL: https://<aws.fqdn>/<aws.cluster.name>/gpudb-0/has/schema Checks for the existence of a schema with the given name. Input Parameter Description Name Type Description schema_name string Name of the schema to check for existence, in root, using standard name resolution rules. options map of string to strings Optional parameters. The default value is an empty map ( {} ). Output Parameter Description The GPUdb server embeds the endpoint response inside a standard response structure which contains status information and the actual response to the query.

/has/table

Mon, 01 Jan 0001 00:00:00 +0000

URL: http://<db.host>:<db.port>/has/table Checks for the existence of a table with the given name. Input Parameter Description Name Type Description table_name string Name of the table to check for existence, in [schema_name.]table_name format, using standard name resolution rules. options map of string to strings Optional parameters. The default value is an empty map ( {} ). Output Parameter Description The GPUdb server embeds the endpoint response inside a standard response structure which contains status information and the actual response to the query.

/has/table

Mon, 01 Jan 0001 00:00:00 +0000

URL: https://<aws.fqdn>/<aws.cluster.name>/gpudb-0/has/table Checks for the existence of a table with the given name. Input Parameter Description Name Type Description table_name string Name of the table to check for existence, in [schema_name.]table_name format, using standard name resolution rules. options map of string to strings Optional parameters. The default value is an empty map ( {} ). Output Parameter Description The GPUdb server embeds the endpoint response inside a standard response structure which contains status information and the actual response to the query.

/has/type

Mon, 01 Jan 0001 00:00:00 +0000

URL: http://<db.host>:<db.port>/has/type Check for the existence of a type. Input Parameter Description Name Type Description type_id string Id of the type returned in response to /create/type request. options map of string to strings Optional parameters. The default value is an empty map ( {} ). Output Parameter Description The GPUdb server embeds the endpoint response inside a standard response structure which contains status information and the actual response to the query.

/has/type

Mon, 01 Jan 0001 00:00:00 +0000

URL: https://<aws.fqdn>/<aws.cluster.name>/gpudb-0/has/type Check for the existence of a type. Input Parameter Description Name Type Description type_id string Id of the type returned in response to /create/type request. options map of string to strings Optional parameters. The default value is an empty map ( {} ). Output Parameter Description The GPUdb server embeds the endpoint response inside a standard response structure which contains status information and the actual response to the query.

/insert/records

Mon, 01 Jan 0001 00:00:00 +0000

URL: http://<db.host>:<db.port>/insert/records Adds multiple records to the specified table. The operation is synchronous, meaning that a response will not be returned until all the records are fully inserted and available. The response payload provides the counts of the number of records actually inserted and/or updated, and can provide the unique identifier of each added record. The input parameter options parameter can be used to customize this function's behavior. The update_on_existing_pk option specifies the record collision policy for inserting into a table with a primary key, but is ignored if no primary key exists.

/insert/records

Mon, 01 Jan 0001 00:00:00 +0000

URL: https://<aws.fqdn>/<aws.cluster.name>/gpudb-0/insert/records Adds multiple records to the specified table. The operation is synchronous, meaning that a response will not be returned until all the records are fully inserted and available. The response payload provides the counts of the number of records actually inserted and/or updated, and can provide the unique identifier of each added record. The input parameter options parameter can be used to customize this function's behavior. The update_on_existing_pk option specifies the record collision policy for inserting into a table with a primary key, but is ignored if no primary key exists.

/insert/records/fromfiles

Mon, 01 Jan 0001 00:00:00 +0000

URL: http://<db.host>:<db.port>/insert/records/fromfiles Reads from one or more files and inserts the data into a new or existing table. The source data can be located either in KiFS; on the cluster, accessible to the database; or remotely, accessible via a pre-defined external data source. For delimited text files, there are two loading schemes: positional and name-based. The name-based loading scheme is enabled when the file has a header present and text_has_header is set to true.

/insert/records/fromfiles

Mon, 01 Jan 0001 00:00:00 +0000

URL: https://<aws.fqdn>/<aws.cluster.name>/gpudb-0/insert/records/fromfiles Reads from one or more files and inserts the data into a new or existing table. The source data can be located either in KiFS; on the cluster, accessible to the database; or remotely, accessible via a pre-defined external data source. For delimited text files, there are two loading schemes: positional and name-based. The name-based loading scheme is enabled when the file has a header present and text_has_header is set to true.

/insert/records/frompayload

Mon, 01 Jan 0001 00:00:00 +0000

URL: http://<db.host>:<db.port>/insert/records/frompayload Reads from the given text-based or binary payload and inserts the data into a new or existing table. The table will be created if it doesn't already exist. Returns once all records are processed. Input Parameter Description Name Type Description table_name string Name of the table into which the data will be inserted, in [schema_name.]table_name format, using standard name resolution rules. If the table does not exist, the table will be created using either an existing type_id or the type inferred from the payload, and the new table name will have to meet standard table naming criteria.

/insert/records/frompayload

Mon, 01 Jan 0001 00:00:00 +0000

URL: https://<aws.fqdn>/<aws.cluster.name>/gpudb-0/insert/records/frompayload Reads from the given text-based or binary payload and inserts the data into a new or existing table. The table will be created if it doesn't already exist. Returns once all records are processed. Input Parameter Description Name Type Description table_name string Name of the table into which the data will be inserted, in [schema_name.]table_name format, using standard name resolution rules. If the table does not exist, the table will be created using either an existing type_id or the type inferred from the payload, and the new table name will have to meet standard table naming criteria.

/insert/records/fromquery

Mon, 01 Jan 0001 00:00:00 +0000

URL: http://<db.host>:<db.port>/insert/records/fromquery Computes remote query result and inserts the result data into a new or existing table Input Parameter Description Name Type Description table_name string Name of the table into which the data will be inserted, in [schema_name.]table_name format, using standard name resolution rules. If the table does not exist, the table will be created using either an existing type_id or the type inferred from the remote query, and the new table name will have to meet standard table naming criteria.

/insert/records/fromquery

Mon, 01 Jan 0001 00:00:00 +0000

URL: https://<aws.fqdn>/<aws.cluster.name>/gpudb-0/insert/records/fromquery Computes remote query result and inserts the result data into a new or existing table Input Parameter Description Name Type Description table_name string Name of the table into which the data will be inserted, in [schema_name.]table_name format, using standard name resolution rules. If the table does not exist, the table will be created using either an existing type_id or the type inferred from the remote query, and the new table name will have to meet standard table naming criteria.

/insert/records/json

Mon, 01 Jan 0001 00:00:00 +0000

URL: http://<db.host>:<db.port>/insert/records/json Overview Usage Examples Responses Overview Kinetica provides a direct JSON ingest service to allow raw JSON to be translated into records and inserted into the database. If the target table exists, inserted records will be appended to it. If the target table does not exist, it will be created automatically, with type inferencing used to determine column types & sizes, before inserting data. Tip To ensure a particular column ordering with a created target table, use the columns_to_load parameter, specifying all columns in the desired order.

/insert/records/json

Mon, 01 Jan 0001 00:00:00 +0000

URL: https://<aws.fqdn>/<aws.cluster.name>/gpudb-0/insert/records/json Overview Usage Examples Responses Overview Kinetica provides a direct JSON ingest service to allow raw JSON to be translated into records and inserted into the database. If the target table exists, inserted records will be appended to it. If the target table does not exist, it will be created automatically, with type inferencing used to determine column types & sizes, before inserting data. Tip To ensure a particular column ordering with a created target table, use the columns_to_load parameter, specifying all columns in the desired order.

/insert/records/random

Mon, 01 Jan 0001 00:00:00 +0000

URL: http://<db.host>:<db.port>/insert/records/random Generates a specified number of random records and adds them to the given table. There is an optional parameter that allows the user to customize the ranges of the column values. It also allows the user to specify linear profiles for some or all columns in which case linear values are generated rather than random ones. Only individual tables are supported for this operation. This operation is synchronous, meaning that a response will not be returned until all random records are fully available.

/insert/records/random

Mon, 01 Jan 0001 00:00:00 +0000

URL: https://<aws.fqdn>/<aws.cluster.name>/gpudb-0/insert/records/random Generates a specified number of random records and adds them to the given table. There is an optional parameter that allows the user to customize the ranges of the column values. It also allows the user to specify linear profiles for some or all columns in which case linear values are generated rather than random ones. Only individual tables are supported for this operation. This operation is synchronous, meaning that a response will not be returned until all random records are fully available.

/insert/symbol

Mon, 01 Jan 0001 00:00:00 +0000

URL: http://<db.host>:<db.port>/insert/symbol Adds a symbol or icon (i.e. an image) to represent data points when data is rendered visually. Users must provide the symbol identifier (string), a format (currently supported: 'svg' and 'svg_path'), the data for the symbol, and any additional optional parameter (e.g. color). To have a symbol used for rendering create a table with a string column named 'SYMBOLCODE' (along with 'x' or 'y' for example). Then when the table is rendered (via WMS) if the 'dosymbology' parameter is 'true' then the value of the 'SYMBOLCODE' column is used to pick the symbol displayed for each point.

/insert/symbol

Mon, 01 Jan 0001 00:00:00 +0000

URL: https://<aws.fqdn>/<aws.cluster.name>/gpudb-0/insert/symbol Adds a symbol or icon (i.e. an image) to represent data points when data is rendered visually. Users must provide the symbol identifier (string), a format (currently supported: 'svg' and 'svg_path'), the data for the symbol, and any additional optional parameter (e.g. color). To have a symbol used for rendering create a table with a string column named 'SYMBOLCODE' (along with 'x' or 'y' for example). Then when the table is rendered (via WMS) if the 'dosymbology' parameter is 'true' then the value of the 'SYMBOLCODE' column is used to pick the symbol displayed for each point.

/kill/proc

Mon, 01 Jan 0001 00:00:00 +0000

URL: http://<db.host>:<db.port>/kill/proc Kills a running proc instance. Input Parameter Description Name Type Description run_id string The run ID of a running proc instance. If a proc with a matching run ID is not found or the proc instance has already completed, no procs will be killed. If not specified, all running proc instances will be killed. The default value is ''. options map of string to strings Optional parameters. The default value is an empty map ( {} ).

/kill/proc

Mon, 01 Jan 0001 00:00:00 +0000

URL: https://<aws.fqdn>/<aws.cluster.name>/gpudb-0/kill/proc Kills a running proc instance. Input Parameter Description Name Type Description run_id string The run ID of a running proc instance. If a proc with a matching run ID is not found or the proc instance has already completed, no procs will be killed. If not specified, all running proc instances will be killed. The default value is ''. options map of string to strings Optional parameters. The default value is an empty map ( {} ).

/lock/table

Mon, 01 Jan 0001 00:00:00 +0000

URL: http://<db.host>:<db.port>/lock/table Manages global access to a table's data. By default a table has a input parameter lock_type of read_write, indicating all operations are permitted. A user may request a read_only or a write_only lock, after which only read or write operations, respectively, are permitted on the table until the lock is removed. When input parameter lock_type is no_access then no operations are permitted on the table. The lock status can be queried by setting input parameter lock_type to status.

/lock/table

Mon, 01 Jan 0001 00:00:00 +0000

URL: https://<aws.fqdn>/<aws.cluster.name>/gpudb-0/lock/table Manages global access to a table's data. By default a table has a input parameter lock_type of read_write, indicating all operations are permitted. A user may request a read_only or a write_only lock, after which only read or write operations, respectively, are permitted on the table until the lock is removed. When input parameter lock_type is no_access then no operations are permitted on the table. The lock status can be queried by setting input parameter lock_type to status.

/match/graph

Mon, 01 Jan 0001 00:00:00 +0000

URL: http://<db.host>:<db.port>/match/graph Matches a directed route implied by a given set of latitude/longitude points to an existing underlying road network graph using a given solution type. IMPORTANT: It's highly recommended that you review the Network Graphs & Solvers concepts documentation, the Graph REST Tutorial, and/or some /match/graph examples before using this endpoint. Input Parameter Description Name Type Description graph_name string Name of the underlying geospatial graph resource to match to using input parameter sample_points.

/match/graph

Mon, 01 Jan 0001 00:00:00 +0000

URL: https://<aws.fqdn>/<aws.cluster.name>/gpudb-0/match/graph Matches a directed route implied by a given set of latitude/longitude points to an existing underlying road network graph using a given solution type. IMPORTANT: It's highly recommended that you review the Network Graphs & Solvers concepts documentation, the Graph REST Tutorial, and/or some /match/graph examples before using this endpoint. Input Parameter Description Name Type Description graph_name string Name of the underlying geospatial graph resource to match to using input parameter sample_points.

/merge/records

Mon, 01 Jan 0001 00:00:00 +0000

URL: http://<db.host>:<db.port>/merge/records Create a new empty result table (specified by input parameter table_name), and insert all records from source tables (specified by input parameter source_table_names) based on the field mapping information (specified by input parameter field_maps). For merge records details and examples, see Merge Records. For limitations, see Merge Records Limitations and Cautions. The field map (specified by input parameter field_maps) holds the user-specified maps of target table column names to source table columns.

/merge/records

Mon, 01 Jan 0001 00:00:00 +0000

URL: https://<aws.fqdn>/<aws.cluster.name>/gpudb-0/merge/records Create a new empty result table (specified by input parameter table_name), and insert all records from source tables (specified by input parameter source_table_names) based on the field mapping information (specified by input parameter field_maps). For merge records details and examples, see Merge Records. For limitations, see Merge Records Limitations and Cautions. The field map (specified by input parameter field_maps) holds the user-specified maps of target table column names to source table columns.

/modify/graph

Mon, 01 Jan 0001 00:00:00 +0000

URL: http://<db.host>:<db.port>/modify/graph Update an existing graph network using given nodes, edges, weights, restrictions, and options. IMPORTANT: It's highly recommended that you review the Network Graphs & Solvers concepts documentation, and Graph REST Tutorial before using this endpoint. Input Parameter Description Name Type Description graph_name string Name of the graph resource to modify. nodes array of strings Nodes with which to update existing input parameter nodes in graph specified by input parameter graph_name.

/modify/graph

Mon, 01 Jan 0001 00:00:00 +0000

URL: https://<aws.fqdn>/<aws.cluster.name>/gpudb-0/modify/graph Update an existing graph network using given nodes, edges, weights, restrictions, and options. IMPORTANT: It's highly recommended that you review the Network Graphs & Solvers concepts documentation, and Graph REST Tutorial before using this endpoint. Input Parameter Description Name Type Description graph_name string Name of the graph resource to modify. nodes array of strings Nodes with which to update existing input parameter nodes in graph specified by input parameter graph_name.

/query/graph

Mon, 01 Jan 0001 00:00:00 +0000

URL: http://<db.host>:<db.port>/query/graph Employs a topological query on a network graph generated a-priori by /create/graph and returns a list of adjacent edge(s) or node(s), also known as an adjacency list, depending on what's been provided to the endpoint; providing edges will return nodes and providing nodes will return edges. To determine the node(s) or edge(s) adjacent to a value from a given column, provide a list of values to input parameter queries.

/query/graph

Mon, 01 Jan 0001 00:00:00 +0000

URL: https://<aws.fqdn>/<aws.cluster.name>/gpudb-0/query/graph Employs a topological query on a network graph generated a-priori by /create/graph and returns a list of adjacent edge(s) or node(s), also known as an adjacency list, depending on what's been provided to the endpoint; providing edges will return nodes and providing nodes will return edges. To determine the node(s) or edge(s) adjacent to a value from a given column, provide a list of values to input parameter queries.

/repartition/graph

Mon, 01 Jan 0001 00:00:00 +0000

URL: http://<db.host>:<db.port>/repartition/graph Rebalances an existing partitioned graph. IMPORTANT: It's highly recommended that you review the Network Graphs & Solvers concepts documentation, the Graph REST Tutorial, and/or some graph examples before using this endpoint. Input Parameter Description Name Type Description graph_name string Name of the graph resource to rebalance. options map of string to strings Optional parameters. The default value is an empty map ( {} ). Supported Parameters (keys) Parameter Description new_graph_name If a non-empty value is specified, the original graph will be kept (non-default behaviour) and a new balanced graph will be created under this given name.

/repartition/graph

Mon, 01 Jan 0001 00:00:00 +0000

URL: https://<aws.fqdn>/<aws.cluster.name>/gpudb-0/repartition/graph Rebalances an existing partitioned graph. IMPORTANT: It's highly recommended that you review the Network Graphs & Solvers concepts documentation, the Graph REST Tutorial, and/or some graph examples before using this endpoint. Input Parameter Description Name Type Description graph_name string Name of the graph resource to rebalance. options map of string to strings Optional parameters. The default value is an empty map ( {} ). Supported Parameters (keys) Parameter Description new_graph_name If a non-empty value is specified, the original graph will be kept (non-default behaviour) and a new balanced graph will be created under this given name.

/revoke/permission

Mon, 01 Jan 0001 00:00:00 +0000

URL: http://<db.host>:<db.port>/revoke/permission Revoke user or role the specified permission on the specified object. Input Parameter Description Name Type Description principal string Name of the user or role for which the permission is being revoked. Must be an existing user or role. The default value is ''. object string Name of object permission is being revoked from. It is recommended to use a fully-qualified name when possible. object_type string The type of object being revoked

/revoke/permission

Mon, 01 Jan 0001 00:00:00 +0000

URL: https://<aws.fqdn>/<aws.cluster.name>/gpudb-0/revoke/permission Revoke user or role the specified permission on the specified object. Input Parameter Description Name Type Description principal string Name of the user or role for which the permission is being revoked. Must be an existing user or role. The default value is ''. object string Name of object permission is being revoked from. It is recommended to use a fully-qualified name when possible. object_type string The type of object being revoked

/revoke/permission/credential

Mon, 01 Jan 0001 00:00:00 +0000

URL: http://<db.host>:<db.port>/revoke/permission/credential Revokes a credential-level permission from a user or role. Input Parameter Description Name Type Description name string Name of the user or role from which the permission will be revoked. Must be an existing user or role. permission string Permission to revoke from the user or role. Supported Values Description credential_admin Full read/write and administrative access on the credential. credential_read Ability to read and use the credential. credential_name string Name of the credential on which the permission will be revoked.

/revoke/permission/credential

Mon, 01 Jan 0001 00:00:00 +0000

URL: https://<aws.fqdn>/<aws.cluster.name>/gpudb-0/revoke/permission/credential Revokes a credential-level permission from a user or role. Input Parameter Description Name Type Description name string Name of the user or role from which the permission will be revoked. Must be an existing user or role. permission string Permission to revoke from the user or role. Supported Values Description credential_admin Full read/write and administrative access on the credential. credential_read Ability to read and use the credential. credential_name string Name of the credential on which the permission will be revoked.

/revoke/permission/datasource

Mon, 01 Jan 0001 00:00:00 +0000

URL: http://<db.host>:<db.port>/revoke/permission/datasource Revokes a data source permission from a user or role. Input Parameter Description Name Type Description name string Name of the user or role from which the permission will be revoked. Must be an existing user or role. permission string Permission to revoke from the user or role Supported Values Description admin Admin access on the given data source connect Connect access on the given data source datasource_name string Name of the data source on which the permission will be revoked.

/revoke/permission/datasource

Mon, 01 Jan 0001 00:00:00 +0000

URL: https://<aws.fqdn>/<aws.cluster.name>/gpudb-0/revoke/permission/datasource Revokes a data source permission from a user or role. Input Parameter Description Name Type Description name string Name of the user or role from which the permission will be revoked. Must be an existing user or role. permission string Permission to revoke from the user or role Supported Values Description admin Admin access on the given data source connect Connect access on the given data source datasource_name string Name of the data source on which the permission will be revoked.

/revoke/permission/directory

Mon, 01 Jan 0001 00:00:00 +0000

URL: http://<db.host>:<db.port>/revoke/permission/directory Revokes a KiFS directory-level permission from a user or role. Input Parameter Description Name Type Description name string Name of the user or role from which the permission will be revoked. Must be an existing user or role. permission string Permission to revoke from the user or role. Supported Values Description directory_read For files in the directory, access to list files, download files, or use files in server side functions directory_write Access to upload files to, or delete files from, the directory.

/revoke/permission/directory

Mon, 01 Jan 0001 00:00:00 +0000

URL: https://<aws.fqdn>/<aws.cluster.name>/gpudb-0/revoke/permission/directory Revokes a KiFS directory-level permission from a user or role. Input Parameter Description Name Type Description name string Name of the user or role from which the permission will be revoked. Must be an existing user or role. permission string Permission to revoke from the user or role. Supported Values Description directory_read For files in the directory, access to list files, download files, or use files in server side functions directory_write Access to upload files to, or delete files from, the directory.

/revoke/permission/proc

Mon, 01 Jan 0001 00:00:00 +0000

URL: http://<db.host>:<db.port>/revoke/permission/proc Revokes a proc-level permission from a user or role. Input Parameter Description Name Type Description name string Name of the user or role from which the permission will be revoked. Must be an existing user or role. permission string Permission to revoke from the user or role. Supported Values Description proc_admin Admin access to the proc. proc_execute Execute access to the proc. proc_name string Name of the proc to which the permission grants access.

/revoke/permission/proc

Mon, 01 Jan 0001 00:00:00 +0000

URL: https://<aws.fqdn>/<aws.cluster.name>/gpudb-0/revoke/permission/proc Revokes a proc-level permission from a user or role. Input Parameter Description Name Type Description name string Name of the user or role from which the permission will be revoked. Must be an existing user or role. permission string Permission to revoke from the user or role. Supported Values Description proc_admin Admin access to the proc. proc_execute Execute access to the proc. proc_name string Name of the proc to which the permission grants access.

/revoke/permission/system

Mon, 01 Jan 0001 00:00:00 +0000

URL: http://<db.host>:<db.port>/revoke/permission/system Revokes a system-level permission from a user or role. Input Parameter Description Name Type Description name string Name of the user or role from which the permission will be revoked. Must be an existing user or role. permission string Permission to revoke from the user or role. Supported Values Description system_admin Full access to all data and system functions. system_user_admin Access to administer users and roles that do not have system_admin permission.

/revoke/permission/system

Mon, 01 Jan 0001 00:00:00 +0000

URL: https://<aws.fqdn>/<aws.cluster.name>/gpudb-0/revoke/permission/system Revokes a system-level permission from a user or role. Input Parameter Description Name Type Description name string Name of the user or role from which the permission will be revoked. Must be an existing user or role. permission string Permission to revoke from the user or role. Supported Values Description system_admin Full access to all data and system functions. system_user_admin Access to administer users and roles that do not have system_admin permission.

/revoke/permission/table

Mon, 01 Jan 0001 00:00:00 +0000

URL: http://<db.host>:<db.port>/revoke/permission/table Revokes a table-level permission from a user or role. Input Parameter Description Name Type Description name string Name of the user or role from which the permission will be revoked. Must be an existing user or role. permission string Permission to revoke from the user or role. Supported Values Description table_admin Full read/write and administrative access to the table. table_insert Insert access to the table. table_update Update access to the table.

/revoke/permission/table

Mon, 01 Jan 0001 00:00:00 +0000

URL: https://<aws.fqdn>/<aws.cluster.name>/gpudb-0/revoke/permission/table Revokes a table-level permission from a user or role. Input Parameter Description Name Type Description name string Name of the user or role from which the permission will be revoked. Must be an existing user or role. permission string Permission to revoke from the user or role. Supported Values Description table_admin Full read/write and administrative access to the table. table_insert Insert access to the table. table_update Update access to the table.

/revoke/role

Mon, 01 Jan 0001 00:00:00 +0000

URL: http://<db.host>:<db.port>/revoke/role Revokes membership in a role from a user or role. Input Parameter Description Name Type Description role string Name of the role in which membership will be revoked. Must be an existing role. member string Name of the user or role that will be revoked membership in input parameter role. Must be an existing user or role. options map of string to strings Optional parameters. The default value is an empty map ( {} ).

/revoke/role

Mon, 01 Jan 0001 00:00:00 +0000

URL: https://<aws.fqdn>/<aws.cluster.name>/gpudb-0/revoke/role Revokes membership in a role from a user or role. Input Parameter Description Name Type Description role string Name of the role in which membership will be revoked. Must be an existing role. member string Name of the user or role that will be revoked membership in input parameter role. Must be an existing user or role. options map of string to strings Optional parameters. The default value is an empty map ( {} ).

/show/credential

Mon, 01 Jan 0001 00:00:00 +0000

URL: http://<db.host>:<db.port>/show/credential Shows information about a specified credential or all credentials. Input Parameter Description Name Type Description credential_name string Name of the credential on which to retrieve information. The name must refer to a currently existing credential. If '*' is specified, information about all credentials will be returned. options map of string to strings Optional parameters. The default value is an empty map ( {} ). Output Parameter Description The GPUdb server embeds the endpoint response inside a standard response structure which contains status information and the actual response to the query.

/show/credential

Mon, 01 Jan 0001 00:00:00 +0000

URL: https://<aws.fqdn>/<aws.cluster.name>/gpudb-0/show/credential Shows information about a specified credential or all credentials. Input Parameter Description Name Type Description credential_name string Name of the credential on which to retrieve information. The name must refer to a currently existing credential. If '*' is specified, information about all credentials will be returned. options map of string to strings Optional parameters. The default value is an empty map ( {} ). Output Parameter Description The GPUdb server embeds the endpoint response inside a standard response structure which contains status information and the actual response to the query.

/show/datasink

Mon, 01 Jan 0001 00:00:00 +0000

URL: http://<db.host>:<db.port>/show/datasink Shows information about a specified data sink or all data sinks. Input Parameter Description Name Type Description name string Name of the data sink for which to retrieve information. The name must refer to a currently existing data sink. If '*' is specified, information about all data sinks will be returned. options map of string to strings Optional parameters. The default value is an empty map ( {} ).

/show/datasink

Mon, 01 Jan 0001 00:00:00 +0000

URL: https://<aws.fqdn>/<aws.cluster.name>/gpudb-0/show/datasink Shows information about a specified data sink or all data sinks. Input Parameter Description Name Type Description name string Name of the data sink for which to retrieve information. The name must refer to a currently existing data sink. If '*' is specified, information about all data sinks will be returned. options map of string to strings Optional parameters. The default value is an empty map ( {} ).

/show/datasource

Mon, 01 Jan 0001 00:00:00 +0000

URL: http://<db.host>:<db.port>/show/datasource Shows information about a specified data source or all data sources. Input Parameter Description Name Type Description name string Name of the data source for which to retrieve information. The name must refer to a currently existing data source. If '*' is specified, information about all data sources will be returned. options map of string to strings Optional parameters. The default value is an empty map ( {} ).

/show/datasource

Mon, 01 Jan 0001 00:00:00 +0000

URL: https://<aws.fqdn>/<aws.cluster.name>/gpudb-0/show/datasource Shows information about a specified data source or all data sources. Input Parameter Description Name Type Description name string Name of the data source for which to retrieve information. The name must refer to a currently existing data source. If '*' is specified, information about all data sources will be returned. options map of string to strings Optional parameters. The default value is an empty map ( {} ).

/show/directories

Mon, 01 Jan 0001 00:00:00 +0000

URL: http://<db.host>:<db.port>/show/directories Shows information about directories in KiFS. Can be used to show a single directory, or all directories. Input Parameter Description Name Type Description directory_name string The KiFS directory name to show. If empty, shows all directories. The default value is ''. options map of string to strings Optional parameters. The default value is an empty map ( {} ). Output Parameter Description The GPUdb server embeds the endpoint response inside a standard response structure which contains status information and the actual response to the query.

/show/directories

Mon, 01 Jan 0001 00:00:00 +0000

URL: https://<aws.fqdn>/<aws.cluster.name>/gpudb-0/show/directories Shows information about directories in KiFS. Can be used to show a single directory, or all directories. Input Parameter Description Name Type Description directory_name string The KiFS directory name to show. If empty, shows all directories. The default value is ''. options map of string to strings Optional parameters. The default value is an empty map ( {} ). Output Parameter Description The GPUdb server embeds the endpoint response inside a standard response structure which contains status information and the actual response to the query.

/show/environment

Mon, 01 Jan 0001 00:00:00 +0000

URL: http://<db.host>:<db.port>/show/environment Shows information about a specified user-defined function (UDF) environment or all environments. Returns detailed information about existing environments. Input Parameter Description Name Type Description environment_name string Name of the environment on which to retrieve information. The name must refer to a currently existing environment. If '*' or an empty value is specified, information about all environments will be returned. The default value is ''. options map of string to strings Optional parameters.

/show/environment

Mon, 01 Jan 0001 00:00:00 +0000

URL: https://<aws.fqdn>/<aws.cluster.name>/gpudb-0/show/environment Shows information about a specified user-defined function (UDF) environment or all environments. Returns detailed information about existing environments. Input Parameter Description Name Type Description environment_name string Name of the environment on which to retrieve information. The name must refer to a currently existing environment. If '*' or an empty value is specified, information about all environments will be returned. The default value is ''. options map of string to strings Optional parameters.

/show/files

Mon, 01 Jan 0001 00:00:00 +0000

URL: http://<db.host>:<db.port>/show/files Shows information about files in KiFS. Can be used for individual files, or to show all files in a given directory. Input Parameter Description Name Type Description paths array of strings File paths to show. Each path can be a KiFS directory name, or a full path to a KiFS file. File paths may contain wildcard characters after the KiFS directory delimeter. Accepted wildcard characters are asterisk (*) to represent any string of zero or more characters, and question mark (?

/show/files

Mon, 01 Jan 0001 00:00:00 +0000

URL: https://<aws.fqdn>/<aws.cluster.name>/gpudb-0/show/files Shows information about files in KiFS. Can be used for individual files, or to show all files in a given directory. Input Parameter Description Name Type Description paths array of strings File paths to show. Each path can be a KiFS directory name, or a full path to a KiFS file. File paths may contain wildcard characters after the KiFS directory delimeter. Accepted wildcard characters are asterisk (*) to represent any string of zero or more characters, and question mark (?

/show/graph

Mon, 01 Jan 0001 00:00:00 +0000

URL: http://<db.host>:<db.port>/show/graph Shows information and characteristics of graphs that exist on the graph server. Input Parameter Description Name Type Description graph_name string Name of the graph on which to retrieve information. If left as the default value, information about all graphs is returned. The default value is ''. options map of string to strings Optional parameters. The default value is an empty map ( {} ). Supported Parameters (keys) Parameter Description show_original_request If set to true, the request that was originally used to create the graph is also returned as JSON.

/show/graph

Mon, 01 Jan 0001 00:00:00 +0000

URL: https://<aws.fqdn>/<aws.cluster.name>/gpudb-0/show/graph Shows information and characteristics of graphs that exist on the graph server. Input Parameter Description Name Type Description graph_name string Name of the graph on which to retrieve information. If left as the default value, information about all graphs is returned. The default value is ''. options map of string to strings Optional parameters. The default value is an empty map ( {} ). Supported Parameters (keys) Parameter Description show_original_request If set to true, the request that was originally used to create the graph is also returned as JSON.

/show/proc

Mon, 01 Jan 0001 00:00:00 +0000

URL: http://<db.host>:<db.port>/show/proc Shows information about a proc. Input Parameter Description Name Type Description proc_name string Name of the proc to show information about. If specified, must be the name of a currently existing proc. If not specified, information about all procs will be returned. The default value is ''. options map of string to strings Optional parameters. The default value is an empty map ( {} ). Supported Parameters (keys) Parameter Description include_files If set to true, the files that make up the proc will be returned.

/show/proc

Mon, 01 Jan 0001 00:00:00 +0000

URL: https://<aws.fqdn>/<aws.cluster.name>/gpudb-0/show/proc Shows information about a proc. Input Parameter Description Name Type Description proc_name string Name of the proc to show information about. If specified, must be the name of a currently existing proc. If not specified, information about all procs will be returned. The default value is ''. options map of string to strings Optional parameters. The default value is an empty map ( {} ). Supported Parameters (keys) Parameter Description include_files If set to true, the files that make up the proc will be returned.

/show/proc/status

Mon, 01 Jan 0001 00:00:00 +0000

URL: http://<db.host>:<db.port>/show/proc/status Shows the statuses of running or completed proc instances. Results are grouped by run ID (as returned from /execute/proc) and data segment ID (each invocation of the proc command on a data segment is assigned a data segment ID). Input Parameter Description Name Type Description run_id string The run ID of a specific proc instance for which the status will be returned. If a proc with a matching run ID is not found, the response will be empty.

/show/proc/status

Mon, 01 Jan 0001 00:00:00 +0000

URL: https://<aws.fqdn>/<aws.cluster.name>/gpudb-0/show/proc/status Shows the statuses of running or completed proc instances. Results are grouped by run ID (as returned from /execute/proc) and data segment ID (each invocation of the proc command on a data segment is assigned a data segment ID). Input Parameter Description Name Type Description run_id string The run ID of a specific proc instance for which the status will be returned. If a proc with a matching run ID is not found, the response will be empty.

/show/resource/objects

Mon, 01 Jan 0001 00:00:00 +0000

URL: http://<db.host>:<db.port>/show/resource/objects Returns information about the internal sub-components (tiered objects) which use resources of the system. The request can either return results from actively used objects (default) or it can be used to query the status of the objects of a given list of tables. Returns detailed information about the requested resource objects. Input Parameter Description Name Type Description options map of string to strings Optional parameters. The default value is an empty map ( {} ).

/show/resource/objects

Mon, 01 Jan 0001 00:00:00 +0000

URL: https://<aws.fqdn>/<aws.cluster.name>/gpudb-0/show/resource/objects Returns information about the internal sub-components (tiered objects) which use resources of the system. The request can either return results from actively used objects (default) or it can be used to query the status of the objects of a given list of tables. Returns detailed information about the requested resource objects. Input Parameter Description Name Type Description options map of string to strings Optional parameters. The default value is an empty map ( {} ).

/show/resource/statistics

Mon, 01 Jan 0001 00:00:00 +0000

URL: http://<db.host>:<db.port>/show/resource/statistics Requests various statistics for storage/memory tiers and resource groups. Returns statistics on a per-rank basis. Input Parameter Description Name Type Description options map of string to strings Optional parameters. The default value is an empty map ( {} ). Output Parameter Description The GPUdb server embeds the endpoint response inside a standard response structure which contains status information and the actual response to the query. Here is a description of the various fields of the wrapper:

/show/resource/statistics

Mon, 01 Jan 0001 00:00:00 +0000

URL: https://<aws.fqdn>/<aws.cluster.name>/gpudb-0/show/resource/statistics Requests various statistics for storage/memory tiers and resource groups. Returns statistics on a per-rank basis. Input Parameter Description Name Type Description options map of string to strings Optional parameters. The default value is an empty map ( {} ). Output Parameter Description The GPUdb server embeds the endpoint response inside a standard response structure which contains status information and the actual response to the query. Here is a description of the various fields of the wrapper:

/show/resourcegroups

Mon, 01 Jan 0001 00:00:00 +0000

URL: http://<db.host>:<db.port>/show/resourcegroups Requests resource group properties. Returns detailed information about the requested resource groups. Input Parameter Description Name Type Description names array of strings List of names of groups to be shown. A single entry with an empty string returns all groups. options map of string to strings Optional parameters. The default value is an empty map ( {} ). Supported Parameters (keys) Parameter Description show_default_values If true include values of fields that are based on the default resource group.

/show/resourcegroups

Mon, 01 Jan 0001 00:00:00 +0000

URL: https://<aws.fqdn>/<aws.cluster.name>/gpudb-0/show/resourcegroups Requests resource group properties. Returns detailed information about the requested resource groups. Input Parameter Description Name Type Description names array of strings List of names of groups to be shown. A single entry with an empty string returns all groups. options map of string to strings Optional parameters. The default value is an empty map ( {} ). Supported Parameters (keys) Parameter Description show_default_values If true include values of fields that are based on the default resource group.

/show/schema

Mon, 01 Jan 0001 00:00:00 +0000

URL: http://<db.host>:<db.port>/show/schema Retrieves information about a schema (or all schemas), as specified in input parameter schema_name. Input Parameter Description Name Type Description schema_name string Name of the schema for which to retrieve the information. If blank, then info for all schemas is returned. options map of string to strings Optional parameters. The default value is an empty map ( {} ). Supported Parameters (keys) Parameter Description no_error_if_not_exists If false will return an error if the provided input parameter schema_name does not exist.

/show/schema

Mon, 01 Jan 0001 00:00:00 +0000

URL: https://<aws.fqdn>/<aws.cluster.name>/gpudb-0/show/schema Retrieves information about a schema (or all schemas), as specified in input parameter schema_name. Input Parameter Description Name Type Description schema_name string Name of the schema for which to retrieve the information. If blank, then info for all schemas is returned. options map of string to strings Optional parameters. The default value is an empty map ( {} ). Supported Parameters (keys) Parameter Description no_error_if_not_exists If false will return an error if the provided input parameter schema_name does not exist.

/show/security

Mon, 01 Jan 0001 00:00:00 +0000

URL: http://<db.host>:<db.port>/show/security Shows security information relating to users and/or roles. If the caller is not a system administrator, only information relating to the caller and their roles is returned. Input Parameter Description Name Type Description names array of strings A list of names of users and/or roles about which security information is requested. If none are provided, information about all users and roles will be returned. options map of string to strings Optional parameters.

/show/security

Mon, 01 Jan 0001 00:00:00 +0000

URL: https://<aws.fqdn>/<aws.cluster.name>/gpudb-0/show/security Shows security information relating to users and/or roles. If the caller is not a system administrator, only information relating to the caller and their roles is returned. Input Parameter Description Name Type Description names array of strings A list of names of users and/or roles about which security information is requested. If none are provided, information about all users and roles will be returned. options map of string to strings Optional parameters.

/show/sql/proc

Mon, 01 Jan 0001 00:00:00 +0000

URL: http://<db.host>:<db.port>/show/sql/proc Shows information about SQL procedures, including the full definition of each requested procedure. Input Parameter Description Name Type Description procedure_name string Name of the procedure for which to retrieve the information. If blank, then information about all procedures is returned. The default value is ''. options map of string to strings Optional parameters. The default value is an empty map ( {} ). Supported Parameters (keys) Parameter Description no_error_if_not_exists If true, no error will be returned if the requested procedure does not exist.

/show/sql/proc

Mon, 01 Jan 0001 00:00:00 +0000

URL: https://<aws.fqdn>/<aws.cluster.name>/gpudb-0/show/sql/proc Shows information about SQL procedures, including the full definition of each requested procedure. Input Parameter Description Name Type Description procedure_name string Name of the procedure for which to retrieve the information. If blank, then information about all procedures is returned. The default value is ''. options map of string to strings Optional parameters. The default value is an empty map ( {} ). Supported Parameters (keys) Parameter Description no_error_if_not_exists If true, no error will be returned if the requested procedure does not exist.

/show/statistics

Mon, 01 Jan 0001 00:00:00 +0000

URL: http://<db.host>:<db.port>/show/statistics Retrieves the collected column statistics for the specified table(s). Input Parameter Description Name Type Description table_names array of strings Names of tables whose metadata will be fetched, each in [schema_name.]table_name format, using standard name resolution rules. All provided tables must exist, or an error is returned. options map of string to strings Optional parameters. The default value is an empty map ( {} ). Output Parameter Description The GPUdb server embeds the endpoint response inside a standard response structure which contains status information and the actual response to the query.

/show/statistics

Mon, 01 Jan 0001 00:00:00 +0000

URL: https://<aws.fqdn>/<aws.cluster.name>/gpudb-0/show/statistics Retrieves the collected column statistics for the specified table(s). Input Parameter Description Name Type Description table_names array of strings Names of tables whose metadata will be fetched, each in [schema_name.]table_name format, using standard name resolution rules. All provided tables must exist, or an error is returned. options map of string to strings Optional parameters. The default value is an empty map ( {} ). Output Parameter Description The GPUdb server embeds the endpoint response inside a standard response structure which contains status information and the actual response to the query.

/show/system/properties

Mon, 01 Jan 0001 00:00:00 +0000

URL: http://<db.host>:<db.port>/show/system/properties Returns server configuration and version related information to the caller. The admin tool uses it to present server related information to the user. Input Parameter Description Name Type Description options map of string to strings Optional parameters. The default value is an empty map ( {} ). Supported Parameters (keys) Parameter Description properties A list of comma separated names of properties requested. If not specified, all properties will be returned.

/show/system/properties

Mon, 01 Jan 0001 00:00:00 +0000

URL: https://<aws.fqdn>/<aws.cluster.name>/gpudb-0/show/system/properties Returns server configuration and version related information to the caller. The admin tool uses it to present server related information to the user. Input Parameter Description Name Type Description options map of string to strings Optional parameters. The default value is an empty map ( {} ). Supported Parameters (keys) Parameter Description properties A list of comma separated names of properties requested. If not specified, all properties will be returned.

/show/system/status

Mon, 01 Jan 0001 00:00:00 +0000

URL: http://<db.host>:<db.port>/show/system/status Provides server configuration and health related status to the caller. The admin tool uses it to present server related information to the user. Input Parameter Description Name Type Description options map of string to strings Optional parameters, currently unused. The default value is an empty map ( {} ). Output Parameter Description The GPUdb server embeds the endpoint response inside a standard response structure which contains status information and the actual response to the query.

/show/system/status

Mon, 01 Jan 0001 00:00:00 +0000

URL: https://<aws.fqdn>/<aws.cluster.name>/gpudb-0/show/system/status Provides server configuration and health related status to the caller. The admin tool uses it to present server related information to the user. Input Parameter Description Name Type Description options map of string to strings Optional parameters, currently unused. The default value is an empty map ( {} ). Output Parameter Description The GPUdb server embeds the endpoint response inside a standard response structure which contains status information and the actual response to the query.

/show/system/timing

Mon, 01 Jan 0001 00:00:00 +0000

URL: http://<db.host>:<db.port>/show/system/timing Returns the last 100 database requests along with the request timing and internal job id. The admin tool uses it to present request timing information to the user. Input Parameter Description Name Type Description options map of string to strings Optional parameters, currently unused. The default value is an empty map ( {} ). Output Parameter Description The GPUdb server embeds the endpoint response inside a standard response structure which contains status information and the actual response to the query.

/show/system/timing

Mon, 01 Jan 0001 00:00:00 +0000

URL: https://<aws.fqdn>/<aws.cluster.name>/gpudb-0/show/system/timing Returns the last 100 database requests along with the request timing and internal job id. The admin tool uses it to present request timing information to the user. Input Parameter Description Name Type Description options map of string to strings Optional parameters, currently unused. The default value is an empty map ( {} ). Output Parameter Description The GPUdb server embeds the endpoint response inside a standard response structure which contains status information and the actual response to the query.

/show/table

Mon, 01 Jan 0001 00:00:00 +0000

URL: http://<db.host>:<db.port>/show/table Retrieves detailed information about a table, view, or schema, specified in input parameter table_name. If the supplied input parameter table_name is a schema the call can return information about either the schema itself or the tables and views it contains. If input parameter table_name is empty, information about all schemas will be returned. If the option get_sizes is set to true, then the number of records in each table is returned (in output parameter sizes and output parameter full_sizes), along with the total number of objects across all requested tables (in output parameter total_size and output parameter total_full_size).

/show/table

Mon, 01 Jan 0001 00:00:00 +0000

URL: https://<aws.fqdn>/<aws.cluster.name>/gpudb-0/show/table Retrieves detailed information about a table, view, or schema, specified in input parameter table_name. If the supplied input parameter table_name is a schema the call can return information about either the schema itself or the tables and views it contains. If input parameter table_name is empty, information about all schemas will be returned. If the option get_sizes is set to true, then the number of records in each table is returned (in output parameter sizes and output parameter full_sizes), along with the total number of objects across all requested tables (in output parameter total_size and output parameter total_full_size).

/show/table/metadata

Mon, 01 Jan 0001 00:00:00 +0000

URL: http://<db.host>:<db.port>/show/table/metadata Retrieves the user provided metadata for the specified tables. Input Parameter Description Name Type Description table_names array of strings Names of tables whose metadata will be fetched, in [schema_name.]table_name format, using standard name resolution rules. All provided tables must exist, or an error is returned. options map of string to strings Optional parameters. The default value is an empty map ( {} ). Output Parameter Description The GPUdb server embeds the endpoint response inside a standard response structure which contains status information and the actual response to the query.

/show/table/metadata

Mon, 01 Jan 0001 00:00:00 +0000

URL: https://<aws.fqdn>/<aws.cluster.name>/gpudb-0/show/table/metadata Retrieves the user provided metadata for the specified tables. Input Parameter Description Name Type Description table_names array of strings Names of tables whose metadata will be fetched, in [schema_name.]table_name format, using standard name resolution rules. All provided tables must exist, or an error is returned. options map of string to strings Optional parameters. The default value is an empty map ( {} ). Output Parameter Description The GPUdb server embeds the endpoint response inside a standard response structure which contains status information and the actual response to the query.

/show/tablemonitors

Mon, 01 Jan 0001 00:00:00 +0000

URL: http://<db.host>:<db.port>/show/tablemonitors Show table monitors and their properties. Table monitors are created using /create/tablemonitor. Returns detailed information about existing table monitors. Input Parameter Description Name Type Description monitor_ids array of strings List of monitors to be shown. An empty list or a single entry with an empty string returns all table monitors. options map of string to strings Optional parameters. The default value is an empty map ( {} ).

/show/tablemonitors

Mon, 01 Jan 0001 00:00:00 +0000

URL: https://<aws.fqdn>/<aws.cluster.name>/gpudb-0/show/tablemonitors Show table monitors and their properties. Table monitors are created using /create/tablemonitor. Returns detailed information about existing table monitors. Input Parameter Description Name Type Description monitor_ids array of strings List of monitors to be shown. An empty list or a single entry with an empty string returns all table monitors. options map of string to strings Optional parameters. The default value is an empty map ( {} ).

/show/tables/bytype

Mon, 01 Jan 0001 00:00:00 +0000

URL: http://<db.host>:<db.port>/show/tables/bytype Gets names of the tables whose type matches the given criteria. Each table has a particular type. This type comprises the schema and properties of the table and sometimes a type label. This function allows a look up of the existing tables based on full or partial type information. The operation is synchronous. Input Parameter Description Name Type Description type_id string Type id returned by a call to /create/type.

/show/tables/bytype

Mon, 01 Jan 0001 00:00:00 +0000

URL: https://<aws.fqdn>/<aws.cluster.name>/gpudb-0/show/tables/bytype Gets names of the tables whose type matches the given criteria. Each table has a particular type. This type comprises the schema and properties of the table and sometimes a type label. This function allows a look up of the existing tables based on full or partial type information. The operation is synchronous. Input Parameter Description Name Type Description type_id string Type id returned by a call to /create/type.

/show/triggers

Mon, 01 Jan 0001 00:00:00 +0000

URL: http://<db.host>:<db.port>/show/triggers Retrieves information regarding the specified triggers or all existing triggers currently active. Input Parameter Description Name Type Description trigger_ids array of strings List of IDs of the triggers whose information is to be retrieved. An empty list means information will be retrieved on all active triggers. options map of string to strings Optional parameters. The default value is an empty map ( {} ). Output Parameter Description The GPUdb server embeds the endpoint response inside a standard response structure which contains status information and the actual response to the query.

/show/triggers

Mon, 01 Jan 0001 00:00:00 +0000

URL: https://<aws.fqdn>/<aws.cluster.name>/gpudb-0/show/triggers Retrieves information regarding the specified triggers or all existing triggers currently active. Input Parameter Description Name Type Description trigger_ids array of strings List of IDs of the triggers whose information is to be retrieved. An empty list means information will be retrieved on all active triggers. options map of string to strings Optional parameters. The default value is an empty map ( {} ). Output Parameter Description The GPUdb server embeds the endpoint response inside a standard response structure which contains status information and the actual response to the query.

/show/types

Mon, 01 Jan 0001 00:00:00 +0000

URL: http://<db.host>:<db.port>/show/types Retrieves information for the specified data type ID or type label. For all data types that match the input criteria, the database returns the type ID, the type schema, the label (if available), and the type's column properties. Input Parameter Description Name Type Description type_id string Type Id returned in response to a call to /create/type. label string Option string that was supplied by user in a call to /create/type.

/show/types

Mon, 01 Jan 0001 00:00:00 +0000

URL: https://<aws.fqdn>/<aws.cluster.name>/gpudb-0/show/types Retrieves information for the specified data type ID or type label. For all data types that match the input criteria, the database returns the type ID, the type schema, the label (if available), and the type's column properties. Input Parameter Description Name Type Description type_id string Type Id returned in response to a call to /create/type. label string Option string that was supplied by user in a call to /create/type.

/show/video

Mon, 01 Jan 0001 00:00:00 +0000

URL: http://<db.host>:<db.port>/show/video Retrieves information about rendered videos. Input Parameter Description Name Type Description paths array of strings The fully-qualified KiFS paths for the videos to show. If empty, shows all videos. options map of string to strings Optional parameters. The default value is an empty map ( {} ). Output Parameter Description The GPUdb server embeds the endpoint response inside a standard response structure which contains status information and the actual response to the query.

/show/video

Mon, 01 Jan 0001 00:00:00 +0000

URL: https://<aws.fqdn>/<aws.cluster.name>/gpudb-0/show/video Retrieves information about rendered videos. Input Parameter Description Name Type Description paths array of strings The fully-qualified KiFS paths for the videos to show. If empty, shows all videos. options map of string to strings Optional parameters. The default value is an empty map ( {} ). Output Parameter Description The GPUdb server embeds the endpoint response inside a standard response structure which contains status information and the actual response to the query.

/solve/graph

Mon, 01 Jan 0001 00:00:00 +0000

URL: http://<db.host>:<db.port>/solve/graph Solves an existing graph for a type of problem (e.g., shortest path, page rank, travelling salesman, etc.) using source nodes, destination nodes, and additional, optional weights and restrictions. IMPORTANT: It's highly recommended that you review the Network Graphs & Solvers concepts documentation, the Graph REST Tutorial, and/or some /solve/graph examples before using this endpoint. Input Parameter Description Name Type Description graph_name string Name of the graph resource to solve.

/solve/graph

Mon, 01 Jan 0001 00:00:00 +0000

URL: https://<aws.fqdn>/<aws.cluster.name>/gpudb-0/solve/graph Solves an existing graph for a type of problem (e.g., shortest path, page rank, travelling salesman, etc.) using source nodes, destination nodes, and additional, optional weights and restrictions. IMPORTANT: It's highly recommended that you review the Network Graphs & Solvers concepts documentation, the Graph REST Tutorial, and/or some /solve/graph examples before using this endpoint. Input Parameter Description Name Type Description graph_name string Name of the graph resource to solve.

/update/records

Mon, 01 Jan 0001 00:00:00 +0000

URL: http://<db.host>:<db.port>/update/records Runs multiple predicate-based updates in a single call. With the list of given expressions, any matching record's column values will be updated as provided in input parameter new_values_maps. There is also an optional 'upsert' capability where if a particular predicate doesn't match any existing record, then a new record can be inserted. Note that this operation can only be run on an original table and not on a result view.

/update/records

Mon, 01 Jan 0001 00:00:00 +0000

URL: https://<aws.fqdn>/<aws.cluster.name>/gpudb-0/update/records Runs multiple predicate-based updates in a single call. With the list of given expressions, any matching record's column values will be updated as provided in input parameter new_values_maps. There is also an optional 'upsert' capability where if a particular predicate doesn't match any existing record, then a new record can be inserted. Note that this operation can only be run on an original table and not on a result view.

/update/records/byseries

Mon, 01 Jan 0001 00:00:00 +0000

URL: http://<db.host>:<db.port>/update/records/byseries Updates the view specified by input parameter table_name to include full series (track) information from the input parameter world_table_name for the series (tracks) present in the input parameter view_name. Input Parameter Description Name Type Description table_name string Name of the view on which the update operation will be performed, in [schema_name.]view_name format, using standard name resolution rules. Must be an existing view. world_table_name string Name of the table containing the complete series (track) information, in [schema_name.

/update/records/byseries

Mon, 01 Jan 0001 00:00:00 +0000

URL: https://<aws.fqdn>/<aws.cluster.name>/gpudb-0/update/records/byseries Updates the view specified by input parameter table_name to include full series (track) information from the input parameter world_table_name for the series (tracks) present in the input parameter view_name. Input Parameter Description Name Type Description table_name string Name of the view on which the update operation will be performed, in [schema_name.]view_name format, using standard name resolution rules. Must be an existing view. world_table_name string Name of the table containing the complete series (track) information, in [schema_name.

/upload/files

Mon, 01 Jan 0001 00:00:00 +0000

URL: http://<db.host>:<db.port>/upload/files Uploads one or more files to KiFS. There are two methods for uploading files: load files in their entirety, or load files in parts. The latter is recommeded for files of approximately 60 MB or larger. To upload files in their entirety, populate input parameter file_names with the file names to upload into on KiFS, and their respective byte content in input parameter file_data. Multiple steps are involved when uploading in multiple parts.

/upload/files

Mon, 01 Jan 0001 00:00:00 +0000

URL: https://<aws.fqdn>/<aws.cluster.name>/gpudb-0/upload/files Uploads one or more files to KiFS. There are two methods for uploading files: load files in their entirety, or load files in parts. The latter is recommeded for files of approximately 60 MB or larger. To upload files in their entirety, populate input parameter file_names with the file names to upload into on KiFS, and their respective byte content in input parameter file_data. Multiple steps are involved when uploading in multiple parts.

/upload/files/fromurl

Mon, 01 Jan 0001 00:00:00 +0000

URL: http://<db.host>:<db.port>/upload/files/fromurl Uploads one or more files to KiFS. Each file path must reside in a top-level KiFS directory, i.e. one of the directories listed in /show/directories. The user must have write permission on the directory. Nested directories are permitted in file name paths. Directories are deliniated with the directory separator of '/'. For example, given the file path '/a/b/c/d.txt', 'a' must be a KiFS directory. These characters are allowed in file name paths: letters, numbers, spaces, the path delimiter of '/', and the characters: '.

/upload/files/fromurl

Mon, 01 Jan 0001 00:00:00 +0000

URL: https://<aws.fqdn>/<aws.cluster.name>/gpudb-0/upload/files/fromurl Uploads one or more files to KiFS. Each file path must reside in a top-level KiFS directory, i.e. one of the directories listed in /show/directories. The user must have write permission on the directory. Nested directories are permitted in file name paths. Directories are deliniated with the directory separator of '/'. For example, given the file path '/a/b/c/d.txt', 'a' must be a KiFS directory. These characters are allowed in file name paths: letters, numbers, spaces, the path delimiter of '/', and the characters: '.

/visualize/image/chart

Mon, 01 Jan 0001 00:00:00 +0000

URL: http://<db.host>:<db.port>/visualize/image/chart Scatter plot is the only plot type currently supported. A non-numeric column can be specified as x or y column and jitters can be added to them to avoid excessive overlapping. All color values must be in the format RRGGBB or AARRGGBB (to specify the alpha value). The image is contained in the output parameter image_data field. Input Parameter Description Name Type Description table_name string Name of the table containing the data to be drawn as a chart, in [schema_name.

/visualize/image/chart

Mon, 01 Jan 0001 00:00:00 +0000

URL: https://<aws.fqdn>/<aws.cluster.name>/gpudb-0/visualize/image/chart Scatter plot is the only plot type currently supported. A non-numeric column can be specified as x or y column and jitters can be added to them to avoid excessive overlapping. All color values must be in the format RRGGBB or AARRGGBB (to specify the alpha value). The image is contained in the output parameter image_data field. Input Parameter Description Name Type Description table_name string Name of the table containing the data to be drawn as a chart, in [schema_name.

/visualize/isochrone

Mon, 01 Jan 0001 00:00:00 +0000

URL: http://<db.host>:<db.port>/visualize/isochrone Generate an image containing isolines for travel results using an existing graph. Isolines represent curves of equal cost, with cost typically referring to the time or distance assigned as the weights of the underlying graph. See Network Graphs & Solvers for more information on graphs. Input Parameter Description Name Type Description graph_name string Name of the graph on which the isochrone is to be computed. source_node string Starting vertex on the underlying graph from/to which the isochrones are created.

/visualize/isochrone

Mon, 01 Jan 0001 00:00:00 +0000

URL: https://<aws.fqdn>/<aws.cluster.name>/gpudb-0/visualize/isochrone Generate an image containing isolines for travel results using an existing graph. Isolines represent curves of equal cost, with cost typically referring to the time or distance assigned as the weights of the underlying graph. See Network Graphs & Solvers for more information on graphs. Input Parameter Description Name Type Description graph_name string Name of the graph on which the isochrone is to be computed. source_node string Starting vertex on the underlying graph from/to which the isochrones are created.

/vts

Mon, 01 Jan 0001 00:00:00 +0000

URL: http://<db.host>:<db.port>/vts Overview Configuration Usage Example Limitations and Cautions Overview Kinetica provides a Vector Tile Service (VTS) to generate Vector Tiles and support client-side visualization of the geospatial data contained within the tiles. The Vector Tile format generated follows the open standard Mapbox Vector Tile specification. The Kinetica VTS feeds a client-side Vector Tile renderer, such as Mapbox GL, by adding the VTS URL to the renderer's style configuration as a map layer source.

/vts

Mon, 01 Jan 0001 00:00:00 +0000

URL: https://<aws.fqdn>/<aws.cluster.name>/gpudb-0/vts Overview Configuration Usage Example Limitations and Cautions Overview Kinetica provides a Vector Tile Service (VTS) to generate Vector Tiles and support client-side visualization of the geospatial data contained within the tiles. The Vector Tile format generated follows the open standard Mapbox Vector Tile specification. The Kinetica VTS feeds a client-side Vector Tile renderer, such as Mapbox GL, by adding the VTS URL to the renderer's style configuration as a map layer source.

/wms

Mon, 01 Jan 0001 00:00:00 +0000

URL: http://<db.host>:<db.port>/wms Overview Downloads Required Parameters Optional Parameters Modes RASTER CB_RASTER HEATMAP CONTOUR LABELS ISOCHRONES Overview Kinetica provides a Web Map Service (WMS) for generating image tiles from the geospatial data contained in it. The type of image tiles returned, the data used to generate the tiles, and the graphical styles in the tiles are specified in the query string of the WMS call. These would typically be used as overlays on top of a map.

/wms

Mon, 01 Jan 0001 00:00:00 +0000

URL: https://<aws.fqdn>/<aws.cluster.name>/gpudb-0/wms Overview Downloads Required Parameters Optional Parameters Modes RASTER CB_RASTER HEATMAP CONTOUR LABELS ISOCHRONES Overview Kinetica provides a Web Map Service (WMS) for generating image tiles from the geospatial data contained in it. The type of image tiles returned, the data used to generate the tiles, and the graphical styles in the tiles are specified in the query string of the WMS call. These would typically be used as overlays on top of a map.

5.2 Release Notes

Mon, 01 Jan 0001 00:00:00 +0000

Features Connectors Core Security GAdmin SQL Features Connectors Increased stability & performance across connectors Core Added support for 32, 64, 128, & 256 byte character strings Initial NULL support Added support for inner, left & right join set operations Added filter planner for displaying join path Added set concatenation operation Aggregation result sets can be made into views New functions: Character-based: lower, upper, min, max, ltrim, rtrim & trim Geographic: wkt_dist & wkt_is_within_dist Null: is_null, nvl, nvl2 & nullif Collapsed /alter/table/* and /show/table/* endpoints Security Added role-based security and supporting endpoints Removed passphrase-based authorization checks; no longer needed in new security model GAdmin Added to HA & security infrastructures Sortable data grid columns Added to table view: shard & foreign keys, replicated & protected statuses, TTL SQL Operations: JOIN, LEFT/RIGHT JOIN, EXISTS, SELECT DISTINCT, TOP, UNION ALL & IN Functions: CASE, CONVERT, IFNULL, NOT, TIMESTAMPADD, TRUNCATE

6.0 Release Notes

Mon, 01 Jan 0001 00:00:00 +0000

Features Core Security SQL Version 6.0.1 API Core SQL Features Reveal data exploration tool and analytics GUI User-Defined Function Framework User-defined binaries can receive table data, perform computations, and persist results in a distributed manner Orchestration API provided in C++ and Java bindings; integrates with high-speed IPC layer of every data container Visual Installer--allows for easy click-button installation across hundreds of nodes Core Increased node capacity & utilization, with active memory management; operations are host memory aware and write to disk, as needed GPU-only column designation for accelerated query performance Full NULL support Added Decimal, Date, & Time column types Support for renaming tables and adding/modifying/deleting columns in place Union, intersect & minus set operations Multi-column order-by support Added projections--filters that allow column expressions in the result set column list Moving average capability Security Integration with LDAP & Kerberos Table-level data access control per user SQL Operations: CROSS JOIN, FULL OUTER JOIN, UNION DISTINCT, UPDATE, DELETE, CREATE TABLE, DROP TABLE Functions: LIKE Types: DECIMAL(P,S), TYPE_DATE, & TYPE_TIME Version 6.

6.1 Release Notes

Mon, 01 Jan 0001 00:00:00 +0000

APIs Cloud Deployment Connectors Core Geospatial Installation / Management Reveal Security SQL User-Defined Functions (UDFs) APIs The Python API can be installed from PyPI Database backups possible while the system is still online The /wms endpoint has had numerous enhancements: Support for tables with multiple geospatial columns Additional RASTER and CB_RASTER mode options The ability to use a default class for the CB_RASTER mode The Java API BulkInserter will automatically retry any failed inserts to attempt to handle errors automatically The PIVOT operation is enabled via the /aggregate/groupby endpoint options pivot and pivot_values.

6.2 Release Notes

Mon, 01 Jan 0001 00:00:00 +0000

Core Geospatial Security SQL User-Defined Functions (UDFs) Core The size limit for primary keys has been increased to 320 bytes [1] Dictionary encoding performance enhancements Jobs can now be performed asynchronously The Kinetica File System (KiFS) has been introduced to greatly ease ML workflows centered around file processing and file generation Non-HA multi-head primary key lookup is now possible using the RecordRetriever object available in the Java and Python APIs

7.0 Release Notes

Mon, 01 Jan 0001 00:00:00 +0000

Publish Date: 01/31/2019 Features Active Analytics Workbench Core Geospatial / Network Graph KAgent SQL / OLAP UI Version 7.0.20 SQL/OLAP Geospatial/Network Graph/Visualization AAW APIs/Tools/Connectors UI Version 7.0.19 SQL/OLAP Geospatial/Network Graph/Visualization AAW UI Version 7.0.18 SQL/OLAP Geospatial/Network Graph/Visualization APIs/Tools/Connectors Version 7.0.17 SQL/OLAP Infrastructure Geospatial/Network Graph/Visualization APIs/Tools/Connectors Version 7.0.16 SQL/OLAP Geospatial/Visualization APIs/Tools/Connectors UI Version 7.0.15 Geospatial Version 7.0.14 SQL/OLAP Geospatial Version 7.0.13 SQL/OLAP Geospatial Version 7.0.12 SQL/OLAP Infrastructure Geospatial APIs/Tools/Connectors Version 7.

7.1 Release Notes

Mon, 01 Jan 0001 00:00:00 +0000

Publish Date: 2022.03.20 Provisioning Features Data and Analytics Capabilities Ingress / Egress Interfaces Tools Connectors UI Security Resilience Monitoring Version 7.1.9 Highlights SQL/OLAP Infrastructure Geospatial/Network Graph/Visualization APIs/Tools/Connectors UI Version 7.1.8 Highlights SQL/OLAP Infrastructure Geospatial/Network Graph/Visualization APIs/Tools/Connectors UI Version 7.1.7 Highlights SQL/OLAP Infrastructure Geospatial/Network Graph/Visualization APIs/Tools/Connectors UI Features Kinetica is now available as a managed application in the AWS Marketplace! Streamlined provisioning process simplifies setup and gets you up and running in 1 hour Pay-as-you-go option allows you to pay for what you use, billed through AWS Infrastructure provisioned into your AWS subscription Kinetica Workbench simplifies SQL analysis and collaboration Easily ingest data from developer's local environment into Kinetica's marketplace instance Easily set up streaming ingestion from Kafka, AWS S3, and Azure blob storage from within Kinetica User-Defined Functions (UDFs), Graphs, ML models, and more can be managed & executed via SQL Integrated performance monitoring with AWS Monitor One-click upgrades Data and Analytics Capabilities SQL Analytics Kinetica supports:

7.1 Release Notes

Mon, 01 Jan 0001 00:00:00 +0000

Publish Date: 2020.08.19 Install Upgrade Features Core APIs/Tools/Connectors KAgent UI Version 7.1.10 SQL/OLAP Infrastructure Geospatial/Network Graph/Visualization UI Version 7.1.9 Highlights SQL/OLAP Infrastructure Geospatial/Network Graph/Visualization APIs/Tools/Connectors UI Version 7.1.8 Highlights SQL/OLAP Infrastructure Geospatial/Network Graph/Visualization APIs/Tools/Connectors UI Version 7.1.7 Highlights SQL/OLAP Infrastructure Geospatial/Network Graph/Visualization APIs/Tools/Connectors UI OS Support Version 7.1.6 Highlights SQL/OLAP Geospatial/Network Graph/Visualization APIs/Tools/Connectors ML Version 7.1.5 SQL/OLAP Geospatial/Network Graph/Visualization APIs/Tools/Connectors UI Version 7.1.4 SQL/OLAP Geospatial/Network Graph/Visualization AAW APIs/Tools/Connectors UI Version 7.

AAW REST API

Mon, 01 Jan 0001 00:00:00 +0000

AAW REST API

Mon, 01 Jan 0001 00:00:00 +0000

Active Analytics Workbench (AAW) Overview

Mon, 01 Jan 0001 00:00:00 +0000

Kinetica provides the Active Analytics Workbench (AAW) with the goal of simplifying and accelerating data science and machine learning in a scalable fashion. With AAW, users can ingest data, train models, make inferences (answers/output from models), and even audit models with a few endpoints (or clicks via the UI). The AAW package can be automatically installed via KAgent and coexists with the database--meaning easy access to one's data and GPUs.

Active Analytics Workbench (AAW) UI

Mon, 01 Jan 0001 00:00:00 +0000

The Active Analytics Workbench (AAW) UI allows for simplified and controlled usage of the Kinetica machine learning capabilities. AAW is usually installed on port 8070 of the Kinetica instance, so it can be accessed via http://<kinetica.aaw.node>:8070/. The AAW UI home page is the Dashboard. Dashboard Data IngestsDatasetsFeature Sets Models + Analytics DetailsModel CreationModel Deployment RAPIDS Notebook Workspace PrerequisitesOverview Deployments Details Audits Security DetailsNew Credential

Adding a Cluster to KAgent

Mon, 01 Jan 0001 00:00:00 +0000

If you have an existing on premise Kinetica cluster that is not managed by KAgent, you can add it to KAgent without upgrading it. This is particularly useful in the following scenarios: Not all administrative and normal users have direct server-level access to the nodes in the cluster, and they would like to individually manage all relevant services Not all administrative users have direct server-level access, and they would like to schedule and manage backups and snapshots and restore from snapshots if necessary Users would like to keep track of the valid Kubernetes Docker registries for use with the Active Analytics Workbench (AAW) The cluster addition process using KAgent involves adding key information about your cluster to KAgent, including deployment type, security information, node information, and current Kinetica-related packages/services installed.

Adjust Firewall

Mon, 01 Jan 0001 00:00:00 +0000

Firewall Settings RHEL 6 RHEL 6 uses iptables by default to configure its firewall settings. These can be updated using the /etc/sysconfig/iptables file, or, if you have X Server running, there is also a GUI for editing the firewall that can be run using the command: system-config-firewall RHEL 7 RHEL 7 continues to use iptables under the hood, but the preferred way to interact with iptables was updated to using the firewall-cmd command or firewall-config GUI.

Administration: Add Host

Mon, 01 Jan 0001 00:00:00 +0000

Adds a host to an existing cluster. NOTE: This endpoint should be used for on-premise deployments only. Input Parameter Description Name Type Description host_address string IP address of the host that will be added to the cluster. This host must have installed the same version of Kinetica as the cluster to which it is being added. options map of string to strings Optional parameters. The default value is an empty map ( {} ).

Administration: Add Host

Mon, 01 Jan 0001 00:00:00 +0000

Administration: Add Ranks

Mon, 01 Jan 0001 00:00:00 +0000

Add one or more ranks to an existing Kinetica cluster. The new ranks will not contain any data initially (other than replicated tables) and will not be assigned any shards. To rebalance data and shards across the cluster, use Administration: Rebalance. The database must be offline for this operation, see Administration: System Offline For example, if attempting to add three new ranks (two ranks on host 172.123.45.67 and one rank on host 172.

Administration: Add Ranks

Mon, 01 Jan 0001 00:00:00 +0000

Administration: Alter Host

Mon, 01 Jan 0001 00:00:00 +0000

Alter properties on an existing host in the cluster. Currently, the only property that can be altered is a hosts ability to accept failover processes. Input Parameter Description Name Type Description host string Identifies the host this applies to. Can be the host address, or formatted as 'hostN' where N is the host number as specified in gpudb.conf options map of string to strings Optional parameters. The default value is an empty map ( {} ).

Administration: Alter Host

Mon, 01 Jan 0001 00:00:00 +0000

Administration: Alter Job

Mon, 01 Jan 0001 00:00:00 +0000

Perform the requested action on a list of one or more job(s). Based on the type of job and the current state of execution, the action may not be successfully executed. The final result of the attempted actions for each specified job is returned in the status array of the response. See Job Manager for more information. Input Parameter Description Name Type Description job_ids array of longs Jobs to be modified.

Administration: Alter Job

Mon, 01 Jan 0001 00:00:00 +0000

Administration: Begin Backup

Mon, 01 Jan 0001 00:00:00 +0000

Prepares the system for a backup by closing all open file handles after allowing current active jobs to complete. When the database is in backup mode, queries that result in a disk write operation will be blocked until backup mode has been completed by using Administration: End Backup. Input Parameter Description Name Type Description options map of string to strings Optional parameters. The default value is an empty map ( {} ).

Administration: Begin Backup

Mon, 01 Jan 0001 00:00:00 +0000

Administration: End Backup

Mon, 01 Jan 0001 00:00:00 +0000

Restores the system to normal operating mode after a backup has completed, allowing any queries that were blocked to complete. Input Parameter Description Name Type Description options map of string to strings Optional parameters. The default value is an empty map ( {} ). Output Parameter Description Name Type Description info map of string to strings Additional information.

Administration: End Backup

Mon, 01 Jan 0001 00:00:00 +0000

Administration: HA refresh

Mon, 01 Jan 0001 00:00:00 +0000

Restarts the HA processing on the given cluster as a mechanism of accepting breaking HA conf changes. Additionally the cluster is put into read-only while HA is restarting. Input Parameter Description Name Type Description options map of string to strings Optional parameters. The default value is an empty map ( {} ). Output Parameter Description Name Type Description info map of string to strings Additional information.

Administration: HA refresh

Mon, 01 Jan 0001 00:00:00 +0000

Administration: Rebalance

Mon, 01 Jan 0001 00:00:00 +0000

Rebalance the data in the cluster so that all nodes contain an equal number of records approximately and/or rebalance the shards to be equally distributed (as much as possible) across all the ranks. The database must be offline for this operation, see Administration: System Offline If Administration: Rebalance is invoked after a change is made to the cluster, e.g., a host was added or removed, sharded data will be evenly redistributed across the cluster by number of shards per rank while unsharded data will be redistributed across the cluster by data size per rank If Administration: Rebalance is invoked at some point when unsharded data (a.

Administration: Rebalance

Mon, 01 Jan 0001 00:00:00 +0000

Administration: Remove Host

Mon, 01 Jan 0001 00:00:00 +0000

Removes a host from an existing cluster. If the host to be removed has any ranks running on it, the ranks must be removed using Administration: Remove Ranks or manually switched over to a new host using Administration: Switch Over Process prior to host removal. If the host to be removed has the graph server or SQL planner running on it, these must be manually switched over to a new host using Administration: Switch Over Process.

Administration: Remove Host

Mon, 01 Jan 0001 00:00:00 +0000

Administration: Remove Ranks

Mon, 01 Jan 0001 00:00:00 +0000

Remove one or more ranks from an existing Kinetica cluster. All data will be rebalanced to other ranks before the rank(s) is removed unless the rebalance_sharded_data or rebalance_unsharded_data parameters are set to false in the input parameter options, in which case the corresponding sharded data and/or unsharded data (a.k.a. randomly-sharded) will be deleted. The database must be offline for this operation, see Administration: System Offline This endpoint's processing time depends on the amount of data in the system, thus the API call may time out if run directly.

Administration: Remove Ranks

Mon, 01 Jan 0001 00:00:00 +0000

Administration: Show Alerts

Mon, 01 Jan 0001 00:00:00 +0000

Requests a list of the most recent alerts. Returns lists of alert data, including timestamp and type. Input Parameter Description Name Type Description num_alerts int Number of most recent alerts to request. The response will include up to input parameter num_alerts depending on how many alerts there are in the system. A value of 0 returns all stored alerts. options map of string to strings Optional parameters. The default value is an empty map ( {} ).

Administration: Show Alerts

Mon, 01 Jan 0001 00:00:00 +0000

Administration: Show Cluster Operations

Mon, 01 Jan 0001 00:00:00 +0000

Requests the detailed status of the current operation (by default) or a prior cluster operation specified by input parameter history_index. Returns details on the requested cluster operation. The response will also indicate how many cluster operations are stored in the history. Input Parameter Description Name Type Description history_index int Indicates which cluster operation to retrieve. Use 0 for the most recent. The default value is 0. options map of string to strings Optional parameters.

Administration: Show Cluster Operations

Mon, 01 Jan 0001 00:00:00 +0000

Administration: Show Jobs

Mon, 01 Jan 0001 00:00:00 +0000

Get a list of the current jobs in GPUdb. Input Parameter Description Name Type Description options map of string to strings Optional parameters. The default value is an empty map ( {} ). Supported Parameters (keys) Parameter Description show_async_jobs If true, then the completed async jobs are also included in the response. By default, once the async jobs are completed they are no longer included in the jobs list. The default value is false.

Administration: Show Jobs

Mon, 01 Jan 0001 00:00:00 +0000

Administration: Show Shards

Mon, 01 Jan 0001 00:00:00 +0000

Show the mapping of shards to the corresponding rank and tom. The response message contains list of 16384 (total number of shards in the system) Rank and TOM numbers corresponding to each shard. Input Parameter Description Name Type Description options map of string to strings Optional parameters. The default value is an empty map ( {} ). Output Parameter Description Name Type Description version long Current shard array version number.

Administration: Show Shards

Mon, 01 Jan 0001 00:00:00 +0000

Administration: Switch Over Process

Mon, 01 Jan 0001 00:00:00 +0000

Manually switch over one or more processes to another host. Individual ranks or entire hosts may be moved to another host. NOTE: This endpoint should be used for on-premise deployments only. Input Parameter Description Name Type Description processes array of strings Indicates the process identifier to switch over to another host. Options are 'hostN' and 'rankN' where 'N' corresponds to the number associated with a host or rank in the Network section of the gpudb.

Administration: Switch Over Process

Mon, 01 Jan 0001 00:00:00 +0000

Administration: System Offline

Mon, 01 Jan 0001 00:00:00 +0000

Take the system offline. When the system is offline, no user operations can be performed with the exception of a system shutdown. Input Parameter Description Name Type Description offline boolean Set to true if desired state is offline. The supported values are: true false options map of string to strings Optional parameters. The default value is an empty map ( {} ). Supported Parameters (keys) Parameter Description flush_to_disk Flush to disk when going offline The supported values are:

Administration: System Offline

Mon, 01 Jan 0001 00:00:00 +0000

Administration: System Shutdown

Mon, 01 Jan 0001 00:00:00 +0000

Exits the database server application. Input Parameter Description Name Type Description exit_type string Reserved for future use. User can pass an empty string. authorization string No longer used. User can pass an empty string. options map of string to strings Optional parameters. The default value is an empty map ( {} ). Output Parameter Description Name Type Description exit_status string 'OK' upon (right before) successful exit. info map of string to strings Additional information.

Administration: System Shutdown

Mon, 01 Jan 0001 00:00:00 +0000

Administration: Verify Database

Mon, 01 Jan 0001 00:00:00 +0000

Verify database is in a consistent state. When inconsistencies or errors are found, the verified_ok flag in the response is set to false and the list of errors found is provided in the error_list. Input Parameter Description Name Type Description options map of string to strings Optional parameters. The default value is an empty map ( {} ). Supported Parameters (keys) Parameter Description rebuild_on_error [DEPRECATED -- Use the Rebuild DB feature of GAdmin instead.

Administration: Verify Database

Mon, 01 Jan 0001 00:00:00 +0000

Aggregate Convex Hull

Mon, 01 Jan 0001 00:00:00 +0000

Calculates and returns the convex hull for the values in a table specified by input parameter table_name. Input Parameter Description Name Type Description table_name string Name of table on which the operation will be performed. Must be an existing table, in [schema_name.]table_name format, using standard name resolution rules. x_column_name string Name of the column containing the x coordinates of the points for the operation being performed. y_column_name string Name of the column containing the y coordinates of the points for the operation being performed.

Aggregate Convex Hull

Mon, 01 Jan 0001 00:00:00 +0000

Aggregate Group By

Mon, 01 Jan 0001 00:00:00 +0000

Calculates unique combinations (groups) of values for the given columns in a given table or view and computes aggregates on each unique combination. This is somewhat analogous to an SQL-style SELECT...GROUP BY. For aggregation details and examples, see Aggregation. For limitations, see Aggregation Limitations. Any column(s) can be grouped on, and all column types except unrestricted-length strings may be used for computing applicable aggregates; columns marked as store-only are unable to be used in grouping or aggregation.

Aggregate Group By

Mon, 01 Jan 0001 00:00:00 +0000

Aggregate Histogram

Mon, 01 Jan 0001 00:00:00 +0000

Performs a histogram calculation given a table, a column, and an interval function. The input parameter interval is used to produce bins of that size and the result, computed over the records falling within each bin, is returned. For each bin, the start value is inclusive, but the end value is exclusive--except for the very last bin for which the end value is also inclusive. The value returned for each bin is the number of records in it, except when a column name is provided as a value_column.

Aggregate Histogram

Mon, 01 Jan 0001 00:00:00 +0000

Aggregate K-means

Mon, 01 Jan 0001 00:00:00 +0000

This endpoint runs the k-means algorithm - a heuristic algorithm that attempts to do k-means clustering. An ideal k-means clustering algorithm selects k points such that the sum of the mean squared distances of each member of the set to the nearest of the k points is minimized. The k-means algorithm however does not necessarily produce such an ideal cluster. It begins with a randomly selected set of k points and then refines the location of the points iteratively and settles to a local minimum.

Aggregate K-means

Mon, 01 Jan 0001 00:00:00 +0000

Aggregate Min/Max

Mon, 01 Jan 0001 00:00:00 +0000

Calculates and returns the minimum and maximum values of a particular column in a table. Input Parameter Description Name Type Description table_name string Name of the table on which the operation will be performed. Must be an existing table, in [schema_name.]table_name format, using standard name resolution rules. column_name string Name of a column or an expression of one or more column on which the min-max will be calculated. options map of string to strings Optional parameters.

Aggregate Min/Max

Mon, 01 Jan 0001 00:00:00 +0000

Aggregate Min/Max Geometry

Mon, 01 Jan 0001 00:00:00 +0000

Calculates and returns the minimum and maximum x- and y-coordinates of a particular geospatial geometry column in a table. Input Parameter Description Name Type Description table_name string Name of the table on which the operation will be performed. Must be an existing table, in [schema_name.]table_name format, using standard name resolution rules. column_name string Name of a geospatial geometry column on which the min-max will be calculated. options map of string to strings Optional parameters.

Aggregate Min/Max Geometry

Mon, 01 Jan 0001 00:00:00 +0000

Aggregate Statistics

Mon, 01 Jan 0001 00:00:00 +0000

Calculates the requested statistics of the given column(s) in a given table. The available statistics are: count (number of total objects), mean, stdv (standard deviation), variance, skew, kurtosis, sum, min, max, weighted_average, cardinality (unique count), estimated_cardinality, percentile, and percentile_rank. Estimated cardinality is calculated by using the hyperloglog approximation technique. Percentiles and percentile ranks are approximate and are calculated using the t-digest algorithm. They must include the desired percentile/percentile_rank. To compute multiple percentiles each value must be specified separately (i.

Aggregate Statistics

Mon, 01 Jan 0001 00:00:00 +0000

Aggregate Statistics by Range

Mon, 01 Jan 0001 00:00:00 +0000

Divides the given set into bins and calculates statistics of the values of a value-column in each bin. The bins are based on the values of a given binning-column. The statistics that may be requested are mean, stdv (standard deviation), variance, skew, kurtosis, sum, min, max, first, last and weighted average. In addition to the requested statistics the count of total samples in each bin is returned. This counts vector is just the histogram of the column used to divide the set members into bins.

Aggregate Statistics by Range

Mon, 01 Jan 0001 00:00:00 +0000

Aggregate Unique

Mon, 01 Jan 0001 00:00:00 +0000

Returns all the unique values from a particular column (specified by input parameter column_name) of a particular table or view (specified by input parameter table_name). If input parameter column_name is a numeric column, the values will be in output parameter binary_encoded_response. Otherwise if input parameter column_name is a string column, the values will be in output parameter json_encoded_response. The results can be paged via input parameter offset and input parameter limit parameters.

Aggregate Unique

Mon, 01 Jan 0001 00:00:00 +0000

Aggregation

Mon, 01 Jan 0001 00:00:00 +0000

Execution Pivot Unpivot Memory-Only Tables and Persistence Sharding and Replication Limitations General Aggregate Memory-Only Tables Kinetica is able to aggregate data via the native APIs and SQL using various aggregate expressions. The native API endpoints related to aggregation: /aggregate/convexhull /aggregate/groupby /aggregate/histogram /aggregate/kmeans /aggregate/minmax /aggregate/minmax/geometry /aggregate/statistics /aggregate/statistics/byrange /aggregate/unique /aggregate/unpivot To read more about aggregation in SQL, see Aggregation. Execution In SQL, to find the minimum, maximum, & average trip distances, as well as the average passenger count for each vendor per year from the taxi data set (weeding out data with errant trip distances):

Aggregation

Mon, 01 Jan 0001 00:00:00 +0000

Alerting

Mon, 01 Jan 0001 00:00:00 +0000

Kinetica provides a simple alerting system controlled by Host Manager that can monitor the health of the system and resource usage. Alert Parameters Using Alerts Run an Executable Status Changes CUDA Errors Fallback Allocator Errors System Errors Memory Usage Disk Usage Maximum Alerts Alerts are enabled by default and pre-configured to report on errors, critical system states, and a nominal set of resource usage thresholds. If an alert is triggered, the alert is stored in memory and also logged to alert_store.

Alerting in AWS

Mon, 01 Jan 0001 00:00:00 +0000

Alerts

Mon, 01 Jan 0001 00:00:00 +0000

The Alerts page in KAgent hosts alert configuration and management as well as alert history. Visit Monitoring and Alerting for an overview of KAgent's monitoring and alerting capabilities, including configuring alerts and recipients. The Alerts page is divided into five tabs: History Metric Alerts Event Alerts Default Alerts Recipients Channels History The History tab displays a detailed alert history. Use the paging controls below the list of alerts to navigate through the history.

Alter Credential

Mon, 01 Jan 0001 00:00:00 +0000

Alter the properties of an existing credential. Input Parameter Description Name Type Description credential_name string Name of the credential to be altered. Must be an existing credential. credential_updates_map map of string to strings Map containing the properties of the credential to be updated. Error if empty. Supported Parameters (keys) Parameter Description type New type for the credential. The supported values are: aws_access_key aws_iam_role azure_ad azure_oauth azure_sas azure_storage_key docker gcs_service_account_id gcs_service_account_keys hdfs kafka identity New user for the credential secret New password for the credential schema_name Updates the schema name.

Alter Credential

Mon, 01 Jan 0001 00:00:00 +0000

Alter Data Sink

Mon, 01 Jan 0001 00:00:00 +0000

Alters the properties of an existing data sink Input Parameter Description Name Type Description name string Name of the data sink to be altered. Must be an existing data sink. datasink_updates_map map of string to strings Map containing the properties of the data sink to be updated. Error if empty. Supported Parameters (keys) Parameter Description destination Destination for the output data in format 'destination_type://path[:port]'. Supported destination types are 'http', 'https' and 'kafka'.

Alter Data Sink

Mon, 01 Jan 0001 00:00:00 +0000

Alter Data Source

Mon, 01 Jan 0001 00:00:00 +0000

Alters the properties of an existing data source Input Parameter Description Name Type Description name string Name of the data source to be altered. Must be an existing data source. datasource_updates_map map of string to strings Map containing the properties of the data source to be updated. Error if empty. Supported Parameters (keys) Parameter Description location Location of the remote storage in 'storage_provider_type://[storage_path[:storage_port]]' format. Supported storage provider types are 'azure','gcs','hdfs','kafka' and 's3'.

Alter Data Source

Mon, 01 Jan 0001 00:00:00 +0000

Alter Directory

Mon, 01 Jan 0001 00:00:00 +0000

Alters an existing directory in KiFS. Input Parameter Description Name Type Description directory_name string Name of the directory in KiFS to be altered. directory_updates_map map of string to strings Map containing the properties of the directory to be altered. Error if empty. Supported Parameters (keys) Parameter Description data_limit The maximum capacity, in bytes, to apply to the directory. Set to -1 to indicate no upper limit. options map of string to strings Optional parameters.

Alter Directory

Mon, 01 Jan 0001 00:00:00 +0000

Alter Resource Group

Mon, 01 Jan 0001 00:00:00 +0000

Alters the properties of an exisiting resource group to facilitate resource management. Input Parameter Description Name Type Description name string Name of the group to be altered. Must be an existing resource group name or an empty string when used inconjunction with the is_default_group option. tier_attributes map of string to maps of string to strings Optional map containing tier names and their respective attribute group limits. The only valid attribute limit that can be set is max_memory (in bytes) for the VRAM & RAM tiers.

Alter Resource Group

Mon, 01 Jan 0001 00:00:00 +0000

Alter Role

Mon, 01 Jan 0001 00:00:00 +0000

Alters a Role. Input Parameter Description Name Type Description name string Name of the role to be altered. Must be an existing role. action string Modification operation to be applied to the role. Supported Values Description set_resource_group Sets the resource group for an internal role. The resource group must exist, otherwise, an empty string assigns the role to the default resource group. value string The value of the modification, depending on input parameter action.

Alter Role

Mon, 01 Jan 0001 00:00:00 +0000

Alter Schema

Mon, 01 Jan 0001 00:00:00 +0000

Used to change the name of a SQL-style schema, specified in input parameter schema_name. Input Parameter Description Name Type Description schema_name string Name of the schema to be altered. action string Modification operation to be applied Supported Values Description rename_schema Renames a schema to input parameter value. Has the same naming restrictions as tables. value string The value of the modification, depending on input parameter action. For now the only value of input parameter action is rename_schema.

Alter Schema

Mon, 01 Jan 0001 00:00:00 +0000

Alter System Properties

Mon, 01 Jan 0001 00:00:00 +0000

The Alter System Properties endpoint is primarily used to simplify the testing of the system and is not expected to be used during normal execution. Commands are given through the input parameter property_updates_map whose keys are commands and values are strings representing integer values (for example '8000') or boolean values ('true' or 'false'). Input Parameter Description Name Type Description property_updates_map map of string to strings Map containing the properties of the system to be updated.

Alter System Properties

Mon, 01 Jan 0001 00:00:00 +0000

Alter Table

Mon, 01 Jan 0001 00:00:00 +0000

Apply various modifications to a table or view. The available modifications include the following: Manage a table's columns--a column can be added, removed, or have its type and properties modified, including whether it is dictionary encoded or not. External tables cannot be modified except for their refresh method. Create or delete a column, chunk skip, or geospatial index. This can speed up certain operations when using expressions containing equality or relational operators on indexed columns.

Alter Table

Mon, 01 Jan 0001 00:00:00 +0000

Alter Table Columns

Mon, 01 Jan 0001 00:00:00 +0000

Apply various modifications to columns in a table, view. The available modifications include the following: Create or delete an index on a particular column. This can speed up certain operations when using expressions containing equality or relational operators on indexed columns. This only applies to tables. Manage a table's columns--a column can be added, removed, or have its type and properties modified, including whether it is dictionary encoded or not.

Alter Table Columns

Mon, 01 Jan 0001 00:00:00 +0000

Alter Table Metadata

Mon, 01 Jan 0001 00:00:00 +0000

Updates (adds or changes) metadata for tables. The metadata key and values must both be strings. This is an easy way to annotate whole tables rather than single records within tables. Some examples of metadata are owner of the table, table creation timestamp etc. Input Parameter Description Name Type Description table_names array of strings Names of the tables whose metadata will be updated, in [schema_name.]table_name format, using standard name resolution rules.

Alter Table Metadata

Mon, 01 Jan 0001 00:00:00 +0000

Alter Table Monitor

Mon, 01 Jan 0001 00:00:00 +0000

Alters a table monitor previously created with Create Table Monitor. Input Parameter Description Name Type Description topic_id string The topic ID returned by Create Table Monitor . monitor_updates_map map of string to strings Map containing the properties of the table monitor to be updated. Error if empty. Supported Parameters (keys) Parameter Description schema_name Updates the schema name. If schema_name doesn't exist, an error will be thrown. If schema_name is empty, then the user's default schema will be used.

Alter Table Monitor

Mon, 01 Jan 0001 00:00:00 +0000

Alter Tier

Mon, 01 Jan 0001 00:00:00 +0000

Alters properties of an exisiting tier to facilitate resource management. To disable watermark-based eviction, set both high_watermark and low_watermark to 100. Input Parameter Description Name Type Description name string Name of the tier to be altered. Must be an existing tier group name. options map of string to strings Optional parameters. The default value is an empty map ( {} ). Supported Parameters (keys) Parameter Description capacity Maximum size in bytes this tier may hold at once.

Alter Tier

Mon, 01 Jan 0001 00:00:00 +0000

Alter UDF environment

Mon, 01 Jan 0001 00:00:00 +0000

Alters an existing environment which can be referenced by a user-defined function (UDF). Input Parameter Description Name Type Description environment_name string Name of the environment to be altered. action string Modification operation to be applied Supported Values Description install_package Install a python package from PyPI, an external data source or KiFS install_requirements Install packages from a requirements file uninstall_package Uninstall a python package. uninstall_requirements Uninstall packages from a requirements file reset Uninstalls all packages in the environment and resets it to the original state at time of creation rebuild Recreates the environment and re-installs all packages, upgrades the packages if necessary based on dependencies value string The value of the modification, depending on input parameter action.

Alter UDF environment

Mon, 01 Jan 0001 00:00:00 +0000

Alter User

Mon, 01 Jan 0001 00:00:00 +0000

Alters a user. Input Parameter Description Name Type Description name string Name of the user to be altered. Must be an existing user. action string Modification operation to be applied to the user. Supported Values Description set_password Sets the password of the user. The user must be an internal user. set_resource_group Sets the resource group for an internal user. The resource group must exist, otherwise, an empty string assigns the user to the default resource group.

Alter User

Mon, 01 Jan 0001 00:00:00 +0000

Alter Video

Mon, 01 Jan 0001 00:00:00 +0000

Alters a video. Input Parameter Description Name Type Description path string Fully-qualified KiFS path to the video to be altered. options map of string to strings Optional parameters. The default value is an empty map ( {} ). Supported Parameters (keys) Parameter Description ttl Sets the TTL of the video. Output Parameter Description Name Type Description path string Fully qualified KIFS path to the video file. info map of string to strings Additional information.

Alter Video

Mon, 01 Jan 0001 00:00:00 +0000

Amazon S3 Import

Mon, 01 Jan 0001 00:00:00 +0000

Import Overview Setup Source Destination Configure Summary Using the Amazon S3 Import wizard, files located in Amazon S3 can be imported into Kinetica. To import a file from Amazon S3 into Kinetica, click on the Amazon S3 panel on the Import landing page in Workbench. The Amazon S3 Import wizard appears in the right-hand pane. Amazon S3 Import Wizard The wizard has two tabs: Import - contains the 5-step process for importing files from Amazon S3 History - lists all of your previous Amazon S3 import attempts Import Overview When importing, the following five steps will need to be completed:

Amazon S3 Import

Mon, 01 Jan 0001 00:00:00 +0000

API Concepts

Mon, 01 Jan 0001 00:00:00 +0000

Native Connecting via API HTTP Connections HTTPS Connections with Certificate Validation HTTPS Connections without Certificate Validation Compatibility Matrix Dynamic Schemas Native C++ API Documentation | C++ GitHub Repo C# API Documentation | C# GitHub Repo Java API Documentation | Java GitHub Repo JavaScript API Documentation | JavaScript GitHub Repo Node.js API Documentation | Node.js GitHub Repo Python API Documentation | Python GitHub Repo REST API Documentation Connecting via API The following shows the means of connecting to Kinetica via the various APIs available.

API Concepts

Mon, 01 Jan 0001 00:00:00 +0000

Native Connecting via API HTTPS Connections with Certificate Validation HTTPS Connections without Certificate Validation Compatibility Matrix Dynamic Schemas Native C++ API Documentation | C++ GitHub Repo C# API Documentation | C# GitHub Repo Java API Documentation | Java GitHub Repo JavaScript API Documentation | JavaScript GitHub Repo Node.js API Documentation | Node.js GitHub Repo Python API Documentation | Python GitHub Repo REST API Documentation Connecting via API The following shows the means of connecting to Kinetica via the various APIs available.

API Documentation

Mon, 01 Jan 0001 00:00:00 +0000

Map Initialization initMap WMS Layer addWmsLayer updateWmsLayer updateWmsLayerType removeWmsLayer addCbLegend setLayerOpacity Cluster Layer addClusterLayer Events on off offById trigger Identify Modes enableIdentifyByRadiusMode enableIdentifyByPointMode disableIdentifyMode Map Initialization initMap Function initMap(options) -> {Promise<Map>} Returns A Promise that delivers the Mapbox GL Map when initialized; this is the Mapbox web map object that will be used throughout the rest of the API. Description Initializes a Mapbox web map. Parameter Type Required Description options Object Yes A configuration object for the map options.

API Documentation

Mon, 01 Jan 0001 00:00:00 +0000

Append Records

Mon, 01 Jan 0001 00:00:00 +0000

Append (or insert) all records from a source table (specified by input parameter source_table_name) to a particular target table (specified by input parameter table_name). The field map (specified by input parameter field_map) holds the user specified map of target table column names with their mapped source column names. Input Parameter Description Name Type Description table_name string The table name for the records to be appended, in [schema_name.]table_name format, using standard name resolution rules.

Append Records

Mon, 01 Jan 0001 00:00:00 +0000

Auditing

Mon, 01 Jan 0001 00:00:00 +0000

Kinetica can be configured to print audit information to a log for security or debugging purposes. The audit configuration settings can be found in the Auditing section of the gpudb.conf file (located in the /opt/gpudb/core/etc directory). The enable_audit setting must be enabled for the other settings to work. Any of these settings can be altered at runtime using /alter/system/properties to assist with debugging unless lock_audit is set to true. Below is a list of the settings and what they do:

Audits

Mon, 01 Jan 0001 00:00:00 +0000

Audits provide a means for reviewing inferences usage and accuracy. To initiate an audit search: Select a Model that has been deployed. Select a Date/Time Range. Optionally, add Search Filters: Click + Add Filter as many times as there are filters necessary to refine the search. For each filter, select a column and an operator & provide a value, e.g., fare_amount > 0. Click Search. Should the audit find anything, the Results table will become available.

Azure Blob Storage Import

Mon, 01 Jan 0001 00:00:00 +0000

Import Overview Setup Source Destination Configure Summary Using the Azure Blob Storage Import wizard, files located in Azure Blob Storage can be imported into Kinetica. To import a file from Azure Blob Storage into Kinetica, click on the Azure Blob Storage panel on the Import landing page in Workbench. The Azure Blob Storage Import wizard appears in the right-hand pane. Azure Blob Storage Import Wizard The wizard has two tabs:

Azure Blob Storage Import

Mon, 01 Jan 0001 00:00:00 +0000

Backing Up & Restoring the Cluster

Mon, 01 Jan 0001 00:00:00 +0000

You can back up Kinetica data through Workbench. Backups can be used to perform a complete data restoration from the point in time the backup was taken. A backup can be requested while the cluster is in a running state; there is no need to suspend it first. Restoring data from a backup, on the other hand, does require the cluster to be suspended first. Clicking on Snapshots, will display two lists:

Backing Up/Restoring Kinetica

Mon, 01 Jan 0001 00:00:00 +0000

KAgent can be used to simplify the processes of backing up and restoring the Kinetica database. It is distributed separately from the database and can be installed and used to configure a Kinetica cluster following the instructions under Kinetica Installation with KAgent. There are two interfaces to KAgent for backing up a Kinetica cluster: Graphical User Interface Command-Line Interface (described below) Prerequisites Backing Up Schedule Backup Path Examples Listing Backup Path Examples Restoring Restore From Backup Path Examples Deleting Backups Prerequisites KAgent backup management has two requirements:

Beam Developer Manual

Mon, 01 Jan 0001 00:00:00 +0000

The following guide provides step-by-step instructions to get started integrating Kinetica with Beam. This project is aimed to make Kinetica accessible to Beam pipelines, both for ingest and egress, meaning data can be transformed from a Kinetica table or to a Kinetica table via a Beam pipeline. Important The Kinetica Beam connector currently only supports Java Beam pipelines The two generic classes that integrate Kinetica with Beam are: com.kinetica.beam.io.KineticaIO.Read<T> -- A class that takes a standard Kinetica table type class to enable reading the data from the given table type com.

Beam Developer Manual

Mon, 01 Jan 0001 00:00:00 +0000

C#

Mon, 01 Jan 0001 00:00:00 +0000

C#

Mon, 01 Jan 0001 00:00:00 +0000

C++

Mon, 01 Jan 0001 00:00:00 +0000

C++

Mon, 01 Jan 0001 00:00:00 +0000

C++ UDF API

Mon, 01 Jan 0001 00:00:00 +0000

The information below includes all the information one needs to know to begin writing UDFs using the C++ UDF API. For more information on executing C++ UDFs, see Running C++ UDFs. Dependencies Initializing Column Types Reading Input Data Accessing Input Values Request Info Keys Writing Output Data Setting Output Values Status Reporting Complete Logging Dependencies To begin writing C++ UDFs, access to the Kinetica C++ UDF API is required. In default Kinetica installations, the C++ UDF API is located in the /opt/gpudb/udf/api/cpp directory.

Changing the Administrator Password

Mon, 01 Jan 0001 00:00:00 +0000

To change the administration account password, follow these steps: Log into GAdmin Enter Username (default is admin) Enter Password (default is admin) Important If the database was installed using KAgent, the password will be the Admin Password created during setup. Click Login Click Admin in the top right corner Click Change Password Enter the Current Password Enter a New Password that meets the password strength requirements (up to 1024 characters)

Changing the Administrator Password

Mon, 01 Jan 0001 00:00:00 +0000

To change the administration account password, follow these steps: Log into Workbench as the administrator Click Admin > Password in the top right corner Enter the Current Password Enter a New Password that meets the password strength requirements (up to 1024 characters) Enter the same new password in Confirm Password Click Update to update to the new password

Clear Statistics

Mon, 01 Jan 0001 00:00:00 +0000

Clears statistics (cardinality, mean value, etc.) for a column in a specified table. Input Parameter Description Name Type Description table_name string Name of a table, in [schema_name.]table_name format, using standard name resolution rules. Must be an existing table. The default value is ''. column_name string Name of the column in input parameter table_name for which to clear statistics. The column must be from an existing table. An empty string clears statistics for all columns in the table.

Clear Statistics

Mon, 01 Jan 0001 00:00:00 +0000

Clear Table

Mon, 01 Jan 0001 00:00:00 +0000

Clears (drops) one or all tables in the database cluster. The operation is synchronous meaning that the table will be cleared before the function returns. The response payload returns the status of the operation along with the name of the table that was cleared. Input Parameter Description Name Type Description table_name string Name of the table to be cleared, in [schema_name.]table_name format, using standard name resolution rules. Must be an existing table.

Clear Table

Mon, 01 Jan 0001 00:00:00 +0000

Clear Table Monitor

Mon, 01 Jan 0001 00:00:00 +0000

Deactivates a table monitor previously created with Create Table Monitor. Input Parameter Description Name Type Description topic_id string The topic ID returned by Create Table Monitor . options map of string to strings Optional parameters. The default value is an empty map ( {} ). Supported Parameters (keys) Parameter Description keep_autogenerated_sink If true, the auto-generated datasink associated with this monitor, if there is one, will be retained for further use.

Clear Table Monitor

Mon, 01 Jan 0001 00:00:00 +0000

Clear Trigger

Mon, 01 Jan 0001 00:00:00 +0000

Clears or cancels the trigger identified by the specified handle. The output returns the handle of the trigger cleared as well as indicating success or failure of the trigger deactivation. Input Parameter Description Name Type Description trigger_id string ID for the trigger to be deactivated. options map of string to strings Optional parameters. The default value is an empty map ( {} ). Output Parameter Description Name Type Description trigger_id string Value of input parameter trigger_id.

Clear Trigger

Mon, 01 Jan 0001 00:00:00 +0000

Cluster

Mon, 01 Jan 0001 00:00:00 +0000

The Cluster menu selection comprises several tabs that contain information about all the machines in your cluster as well as configuration and log file access. Summary data about your Kinetica cluster is pinned to the top right of each tab within Cluster; it includes: The status of Kinetica How many users are connected to Kinetica How many requests per second are being made to Kinetica How many tables are present in this Kinetica cluster How many rows are present in this Kinetica cluster The uptime of this Kinetica cluster A refresh button to refresh the cluster information Dashboard Ranks Admin License Config Alerts Logging Setting Loggers Debug Demo Visualize Dashboard The Dashboard page is also the GAdmin homepage.

Collect Statistics

Mon, 01 Jan 0001 00:00:00 +0000

Collect statistics for a column(s) in a specified table. Input Parameter Description Name Type Description table_name string Name of a table, in [schema_name.]table_name format, using standard name resolution rules. Must be an existing table. column_names array of strings List of one or more column names in input parameter table_name for which to collect statistics (cardinality, mean value, etc.). options map of string to strings Optional parameters. The default value is an empty map ( {} ).

Collect Statistics

Mon, 01 Jan 0001 00:00:00 +0000

Collections

Mon, 01 Jan 0001 00:00:00 +0000

Collections are the precursors to schemas, introduced in Kinetica v7.1. Any collections in prior versions will become schemas after upgrade, and any tables & views not contained within collections will be placed in the home schema. Operations on collections will no longer be supported after upgrade. See Schemas for details.

Concurrency Limits

Mon, 01 Jan 0001 00:00:00 +0000

Concurrency Limits The max_concurrency_per_node setting is available in the options map of the /create/proc. This option allows you to define a per-Kinetica- host concurrency limit for a UDF, i.e. no more than n OS processes (UDF instances) in charge of evaluating the UDF will be permitted to execute concurrently on a single Kinetica host. You may want to set a concurrency limit if you have limited resources (like GPUs) and want to avoid the risks of continually exhausting your resources.

Concurrency Limits

Mon, 01 Jan 0001 00:00:00 +0000

Create Asynchronous Job

Mon, 01 Jan 0001 00:00:00 +0000

Create a job which will run asynchronously. The response returns a job ID, which can be used to query the status and result of the job. The status and the result of the job upon completion can be requested by Get Asynchronous Job Result. Input Parameter Description Name Type Description endpoint string Indicates which endpoint to execute, e.g. '/alter/table'. request_encoding string The encoding of the request payload for the job.

Create Asynchronous Job

Mon, 01 Jan 0001 00:00:00 +0000

Create Credential

Mon, 01 Jan 0001 00:00:00 +0000

Create a new credential. Input Parameter Description Name Type Description credential_name string Name of the credential to be created. Must contain only letters, digits, and underscores, and cannot begin with a digit. Must not match an existing credential name. type string Type of the credential to be created. The supported values are: aws_access_key aws_iam_role azure_ad azure_oauth azure_sas azure_storage_key docker gcs_service_account_id gcs_service_account_keys hdfs jdbc kafka confluent identity string User of the credential to be created.

Create Credential

Mon, 01 Jan 0001 00:00:00 +0000

Create Credentials

Mon, 01 Jan 0001 00:00:00 +0000

Azure GCS HDFS JDBC Kafka (Apache) Kafka (Confluent) S3 (Amazon) Several authentication schemes across multiple providers are supported. For a detailed overview of all of the provider-specific options, see the SQL documentation. Azure Password SAS Token Active Directory Password 1 2 3 4 CREATE CREDENTIAL azure_cred TYPE = 'azure_storage_key', IDENTITY = 'sampleacc', SECRET = 'foobaz123' SAS Token 1 2 3 4 CREATE CREDENTIAL azure_cred TYPE = 'azure_sas', IDENTITY = 'sampleacc', SECRET = 'sv=2015-07-08&sr=b&sig=39Up0JzHkxhUlhFEjEH9673DJxe7w6.

Create Credentials

Mon, 01 Jan 0001 00:00:00 +0000

Create Data Sink

Mon, 01 Jan 0001 00:00:00 +0000

Creates a data sink, which contains the destination information for a data sink that is external to the database. Input Parameter Description Name Type Description name string Name of the data sink to be created. destination string Destination for the output data in format 'storage_provider_type://path[:port]'. Supported storage provider types are 'azure', 'gcs', 'hdfs', 'http', 'https', 'jdbc', 'kafka' and 's3'. options map of string to strings Optional parameters. The default value is an empty map ( {} ).

Create Data Sink

Mon, 01 Jan 0001 00:00:00 +0000

Create Data Sinks

Mon, 01 Jan 0001 00:00:00 +0000

Amazon S3 Azure BLOB CData Google Cloud Storage HDFS JDBC Apache Kafka Web Hook Several authentication schemes across multiple providers are supported. For a detailed overview of all of the provider-specific options, see the SQL documentation. Note Creating an authenticated data sink requires creating a corresponding credential object to store the authentication information and then referencing that object when creating the data sink. See Create Credentials for examples. Amazon S3 Credential 1 2 3 4 5 6 7 8 CREATE DATA SINK s3_dsink LOCATION = 'S3' WITH OPTIONS ( CREDENTIAL = 's3_cred', BUCKET NAME = 'samplebucket', REGION = 'us-east-2' ) Azure BLOB Credential 1 2 3 4 5 6 7 CREATE DATA SINK azure_dsink LOCATION = 'AZURE' WITH OPTIONS ( CREDENTIAL = 'azure_cred', CONTAINER NAME = 'samplecontainer' ) CData Credential Password in URL Credential 1 2 3 CREATE DATA SINK cdata_dsink LOCATION = 'jdbc:postgresql:Server=localhost;Port=5432;Database=ki_home' WITH OPTIONS (CREDENTIAL = 'cdata_cred') Password in URL 1 2 CREATE DATA SINK cdata_dsink LOCATION = 'jdbc:postgresql:Server=localhost;Port=5432;Database=ki_home;User=dsink_user;Password=dsink_pass' Google Cloud Storage Credential 1 2 3 4 5 6 7 CREATE DATA SINK gcs_dsink LOCATION = 'GCS' WITH OPTIONS ( CREDENTIAL = 'gcs_cred', GCS_BUCKET_NAME = 'gcs-private' ) HDFS Credential 1 2 3 CREATE DATA SINK hdfs_dsink LOCATION = 'HDFS://example.

Create Data Sinks

Mon, 01 Jan 0001 00:00:00 +0000

Create Data Source

Mon, 01 Jan 0001 00:00:00 +0000

Creates a data source, which contains the location and connection information for a data store that is external to the database. Input Parameter Description Name Type Description name string Name of the data source to be created. location string Location of the remote storage in 'storage_provider_type://[storage_path[:storage_port]]' format. Supported storage provider types are 'azure','gcs','hdfs','jdbc','kafka', 'confluent' and 's3'. user_name string Name of the remote system user; may be an empty string password string Password for the remote system user; may be an empty string options map of string to strings Optional parameters.

Create Data Source

Mon, 01 Jan 0001 00:00:00 +0000

Create Data Sources

Mon, 01 Jan 0001 00:00:00 +0000

Azure BLOB CData Google Cloud Storage HDFS JDBC Kafka (Apache) Kafka (Confluent) S3 (Amazon) Several authentication schemes across multiple providers are supported. For a detailed overview of all of the provider-specific options, see the SQL documentation. Azure BLOB Credential Public (No Auth) Password SAS Token Active Directory Credential 1 2 3 4 5 6 7 CREATE DATA SOURCE azure_ds LOCATION = 'AZURE' WITH OPTIONS ( CREDENTIAL = 'azure_cred', CONTAINER NAME = 'samplecontainer' ) Public (No Auth) 1 2 3 4 5 6 7 CREATE DATA SOURCE azure_ds LOCATION = 'AZURE' USER = 'sampleacc' WITH OPTIONS ( CONTAINER NAME = 'samplecontainer' ) Password 1 2 3 4 5 6 7 8 CREATE DATA SOURCE azure_ds LOCATION = 'AZURE' USER = 'sampleacc' PASSWORD = 'foobaz123' WITH OPTIONS ( CONTAINER NAME = 'samplecontainer' ) SAS Token 1 2 3 4 5 6 7 8 CREATE DATA SOURCE azure_ds LOCATION = 'AZURE' USER = 'sampleacc' WITH OPTIONS ( CONTAINER NAME = 'samplecontainer', SAS TOKEN = 'sv=2015-07-08&sr=b&sig=39Up0JzHkxhUlhFEjEH9673DJxe7w6clRCg0V6lCgSo%3D&se=2016-10-18T21%A51%A337Z&sp=rcw' ) Active Directory 1 2 3 4 5 6 7 8 9 10 CREATE DATA SOURCE azure_ds LOCATION = 'AZURE' USER = 'jdoe' PASSWORD = 'foobaz123' WITH OPTIONS ( STORAGE ACCOUNT NAME = 'sampelacc', CONTAINER NAME = 'samplecontainer', TENANT ID = 'x0xxx10-00x0-0x01-0xxx-x0x0x01xx100' ) CData Credential Password in URL Password as Parameter Credential 1 2 3 CREATE DATA SOURCE cdata_ds LOCATION = 'jdbc:postgresql:Server=my.

Create Data Sources

Mon, 01 Jan 0001 00:00:00 +0000

Azure BLOB CData Google Cloud Storage HDFS JDBC Kafka (Apache) Kafka (Confluent) S3 (Amazon) Several authentication schemes across multiple providers are supported. For a detailed overview of all of the provider-specific options, see the SQL documentation. Azure BLOB Credential Public (No Auth) Managed Credentials Password SAS Token Active Directory Credential 1 2 3 4 5 6 7 CREATE DATA SOURCE azure_ds LOCATION = 'AZURE' WITH OPTIONS ( CREDENTIAL = 'azure_cred', CONTAINER NAME = 'samplecontainer' ) Public (No Auth) 1 2 3 4 5 6 7 CREATE DATA SOURCE azure_ds LOCATION = 'AZURE' USER = 'sampleacc' WITH OPTIONS ( CONTAINER NAME = 'samplecontainer' ) Managed Credentials 1 2 3 4 5 6 7 8 9 10 CREATE DATA SOURCE azure_ds LOCATION = 'AZURE' USER = 'sampleacc' WITH OPTIONS ( USE_MANAGED_CREDENTIALS = true, STORAGE ACCOUNT NAME = 'sampelacc', CONTAINER NAME = 'samplecontainer', TENANT ID = 'x0xxx10-00x0-0x01-0xxx-x0x0x01xx100' ) Password 1 2 3 4 5 6 7 8 CREATE DATA SOURCE azure_ds LOCATION = 'AZURE' USER = 'sampleacc' PASSWORD = 'foobaz123' WITH OPTIONS ( CONTAINER NAME = 'samplecontainer' ) SAS Token 1 2 3 4 5 6 7 8 CREATE DATA SOURCE azure_ds LOCATION = 'AZURE' USER = 'sampleacc' WITH OPTIONS ( CONTAINER NAME = 'samplecontainer', SAS TOKEN = 'sv=2015-07-08&sr=b&sig=39Up0JzHkxhUlhFEjEH9673DJxe7w6clRCg0V6lCgSo%3D&se=2016-10-18T21%A51%A337Z&sp=rcw' ) Active Directory 1 2 3 4 5 6 7 8 9 10 CREATE DATA SOURCE azure_ds LOCATION = 'AZURE' USER = 'jdoe' PASSWORD = 'foobaz123' WITH OPTIONS ( STORAGE ACCOUNT NAME = 'sampelacc', CONTAINER NAME = 'samplecontainer', TENANT ID = 'x0xxx10-00x0-0x01-0xxx-x0x0x01xx100' ) CData Credential Password in URL Password as Parameter Credential 1 2 3 CREATE DATA SOURCE cdata_ds LOCATION = 'jdbc:postgresql:Server=my.

Create Directory

Mon, 01 Jan 0001 00:00:00 +0000

Creates a new directory in KiFS. The new directory serves as a location in which the user can upload files using Upload Files. Input Parameter Description Name Type Description directory_name string Name of the directory in KiFS to be created. options map of string to strings Optional parameters. The default value is an empty map ( {} ). Supported Parameters (keys) Parameter Description create_home_directory When set, a home directory is created for the user name provided in the value.

Create Directory

Mon, 01 Jan 0001 00:00:00 +0000

Create External Table

Mon, 01 Jan 0001 00:00:00 +0000

Creates a new external table, which is a local database object whose source data is located externally to the database. The source data can be located either in KiFS; on the cluster, accessible to the database; or remotely, accessible via a pre-defined external data source. The external table can have its structure defined explicitly, via input parameter create_table_options, which contains many of the options from Create Table; or defined implicitly, inferred from the source data.

Create External Table

Mon, 01 Jan 0001 00:00:00 +0000

Create External User

Mon, 01 Jan 0001 00:00:00 +0000

Creates a new external user (a user whose credentials are managed by an external LDAP). NOTE: This endpoint should be used for on-premise deployments only. Input Parameter Description Name Type Description name string Name of the user to be created. Must exactly match the user's name in the external LDAP, prefixed with a @. Must not be the same name as an existing user. options map of string to strings Optional parameters.

Create External User

Mon, 01 Jan 0001 00:00:00 +0000

Create Graph

Mon, 01 Jan 0001 00:00:00 +0000

Creates a new graph network using given nodes, edges, weights, and restrictions. IMPORTANT: It's highly recommended that you review the Network Graphs & Solvers concepts documentation, the Graph REST Tutorial, and/or some graph examples before using this endpoint. Input Parameter Description Name Type Description graph_name string Name of the graph resource to generate. directed_graph boolean If set to true, the graph will be directed. If set to false, the graph will not be directed.

Create Graph

Mon, 01 Jan 0001 00:00:00 +0000

Create Internal User

Mon, 01 Jan 0001 00:00:00 +0000

Creates a new internal user (a user whose credentials are managed by the database system). Input Parameter Description Name Type Description name string Name of the user to be created. Must contain only lowercase letters, digits, and underscores, and cannot begin with a digit. Must not be the same name as an existing user or role. password string Initial password of the user to be created. May be an empty string for no password.

Create Internal User

Mon, 01 Jan 0001 00:00:00 +0000

Create Join Table

Mon, 01 Jan 0001 00:00:00 +0000

Creates a table that is the result of a SQL JOIN. For join details and examples see: Joins. For limitations, see Join Limitations and Cautions. Input Parameter Description Name Type Description join_table_name string Name of the join table to be created, in [schema_name.]table_name format, using standard name resolution rules and meeting table naming criteria. table_names array of strings The list of table names composing the join, each in [schema_name.]table_name format, using standard name resolution rules.

Create Join Table

Mon, 01 Jan 0001 00:00:00 +0000

Create Materialized View

Mon, 01 Jan 0001 00:00:00 +0000

Initiates the process of creating a materialized view, reserving the view's name to prevent other views or tables from being created with that name. For materialized view details and examples, see Materialized Views. The response contains output parameter view_id, which is used to tag each subsequent operation (projection, union, aggregation, filter, or join) that will compose the view. Input Parameter Description Name Type Description table_name string Name of the table to be created that is the top-level table of the materialized view, in [schema_name.

Create Materialized View

Mon, 01 Jan 0001 00:00:00 +0000

Create Proc

Mon, 01 Jan 0001 00:00:00 +0000

Creates an instance (proc) of the user-defined functions (UDF) specified by the given command, options, and files, and makes it available for execution. Input Parameter Description Name Type Description proc_name string Name of the proc to be created. Must not be the name of a currently existing proc. execution_mode string The execution mode of the proc. The default value is distributed. Supported Values Description distributed Input table data will be divided into data segments that are distributed across all nodes in the cluster, and the proc command will be invoked once per data segment in parallel.

Create Proc

Mon, 01 Jan 0001 00:00:00 +0000

Create Projection

Mon, 01 Jan 0001 00:00:00 +0000

Creates a new projection of an existing table. A projection represents a subset of the columns (potentially including derived columns) of a table. For projection details and examples, see Projections. For limitations, see Projection Limitations and Cautions. Window functions, which can perform operations like moving averages, are available through this endpoint as well as Get Records by Column. A projection can be created with a different shard key than the source table.

Create Projection

Mon, 01 Jan 0001 00:00:00 +0000

Create Resource Group

Mon, 01 Jan 0001 00:00:00 +0000

Creates a new resource group to facilitate resource management. Input Parameter Description Name Type Description name string Name of the group to be created. Must contain only letters, digits, and underscores, and cannot begin with a digit. Must not match existing resource group name. tier_attributes map of string to maps of string to strings Optional map containing tier names and their respective attribute group limits. The only valid attribute limit that can be set is max_memory (in bytes) for the VRAM & RAM tiers.

Create Resource Group

Mon, 01 Jan 0001 00:00:00 +0000

Create Role

Mon, 01 Jan 0001 00:00:00 +0000

Creates a new role. NOTE: This endpoint should be used for on-premise deployments only. Input Parameter Description Name Type Description name string Name of the role to be created. Must contain only lowercase letters, digits, and underscores, and cannot begin with a digit. Must not be the same name as an existing user or role. options map of string to strings Optional parameters. The default value is an empty map ( {} ).

Create Role

Mon, 01 Jan 0001 00:00:00 +0000

Create Schema

Mon, 01 Jan 0001 00:00:00 +0000

Creates a SQL-style schema. Schemas are containers for tables and views. Multiple tables and views can be defined with the same name in different schemas. Input Parameter Description Name Type Description schema_name string Name of the schema to be created. Has the same naming restrictions as tables. options map of string to strings Optional parameters. The default value is an empty map ( {} ). Supported Parameters (keys) Parameter Description no_error_if_exists If true, prevents an error from occurring if the schema already exists.

Create Schema

Mon, 01 Jan 0001 00:00:00 +0000

Create Table

Mon, 01 Jan 0001 00:00:00 +0000

Creates a new table. If a new table is being created, the type of the table is given by input parameter type_id, which must be the ID of a currently registered type (i.e. one created via Create Type). A table may optionally be designated to use a replicated distribution scheme, or be assigned: foreign keys to other tables, a partitioning scheme, and/or a tier strategy. Input Parameter Description Name Type Description table_name string Name of the table to be created, in [schema_name.

Create Table

Mon, 01 Jan 0001 00:00:00 +0000

Create Table Monitor

Mon, 01 Jan 0001 00:00:00 +0000

Creates a monitor that watches for a single table modification event type (insert, update, or delete) on a particular table (identified by input parameter table_name) and forwards event notifications to subscribers via ZMQ. After this call completes, subscribe to the returned output parameter topic_id on the ZMQ table monitor port (default 9002). Each time an operation of the given type on the table completes, a multipart message is published for that topic; the first part contains only the topic ID, and each subsequent part contains one binary-encoded Avro object that corresponds to the event and can be decoded using output parameter type_schema.

Create Table Monitor

Mon, 01 Jan 0001 00:00:00 +0000

Create Trigger by Area

Mon, 01 Jan 0001 00:00:00 +0000

Sets up an area trigger mechanism for two column_names for one or more tables. (This function is essentially the two-dimensional version of Create Trigger by Range.) Once the trigger has been activated, any record added to the listed tables(s) via Insert Records with the chosen columns' values falling within the specified region will trip the trigger. All such records will be queued at the trigger port (by default '9001' but able to be retrieved via Show System Status) for any listening client to collect.

Create Trigger by Area

Mon, 01 Jan 0001 00:00:00 +0000

Create Trigger by Range

Mon, 01 Jan 0001 00:00:00 +0000

Sets up a simple range trigger for a column_name for one or more tables. Once the trigger has been activated, any record added to the listed tables(s) via Insert Records with the chosen column_name's value falling within the specified range will trip the trigger. All such records will be queued at the trigger port (by default '9001' but able to be retrieved via Show System Status) for any listening client to collect.

Create Trigger by Range

Mon, 01 Jan 0001 00:00:00 +0000

Create Type

Mon, 01 Jan 0001 00:00:00 +0000

Creates a new type describing the layout of a table. The type definition is a JSON string describing the fields (i.e. columns) of the type. Each field consists of a name and a data type. Supported data types are: double, float, int, long, string, and bytes. In addition, one or more properties can be specified for each column which customize the memory usage and query availability of that column. Note that some properties are mutually exclusive--i.

Create Type

Mon, 01 Jan 0001 00:00:00 +0000

Create UDF Environment

Mon, 01 Jan 0001 00:00:00 +0000

Creates a new environment which can be used by user-defined functions (UDF). Input Parameter Description Name Type Description environment_name string Name of the environment to be created. options map of string to strings Optional parameters. The default value is an empty map ( {} ). Output Parameter Description Name Type Description environment_name string Value of input parameter environment_name. info map of string to strings Additional information.

Create UDF Environment

Mon, 01 Jan 0001 00:00:00 +0000

Create Union

Mon, 01 Jan 0001 00:00:00 +0000

Merges data from one or more tables with comparable data types into a new table. The following merges are supported: UNION (DISTINCT/ALL) - For data set union details and examples, see Union. For limitations, see Union Limitations and Cautions. INTERSECT (DISTINCT/ALL) - For data set intersection details and examples, see Intersect. For limitations, see Intersect Limitations. EXCEPT (DISTINCT/ALL) - For data set subtraction details and examples, see Except. For limitations, see Except Limitations.

Create Union

Mon, 01 Jan 0001 00:00:00 +0000

Create Video

Mon, 01 Jan 0001 00:00:00 +0000

Creates a job to generate a sequence of raster images that visualize data over a specified time. Input Parameter Description Name Type Description attribute string The animated attribute to map to the video's frames. Must be present in the LAYERS specified for the visualization. This is often a time-related field but may be any numeric type. begin string The start point for the video. Accepts an expression evaluable over the input parameter attribute.

Create Video

Mon, 01 Jan 0001 00:00:00 +0000

Credentials

Mon, 01 Jan 0001 00:00:00 +0000

Managing Credentials Creating a Credential Provider-Specific Syntax Altering a Credential Removing a Credential Showing a Credential Updating Credential Permissions A credential is an authentication object for a resource or repository that is external to the database. It consists of the credentials used to authenticate to that external system, with the goal of providing an authentication token to any database object that may need to connect to that system. A credential name must adhere to the standard naming criteria.

Credentials

Mon, 01 Jan 0001 00:00:00 +0000

Cube

Mon, 01 Jan 0001 00:00:00 +0000

The cube operation takes n number of columns and produces 2n aggregates. For example, given a cube on columns A, B, & C, it computes the requested aggregates for the following combinations of columns: {ABC} - unique A B C triplets {AB } - unique A B pairs {A C} - unique A C pairs { BC} - unique B C pairs {A } - unique A values { B } - unique B values { C} - unique C values { } - all values The cube operation is an aggregate function that can be invoked natively in the options map of the /aggregate/groupby endpoint.

Cube

Mon, 01 Jan 0001 00:00:00 +0000

Custom Logging

Mon, 01 Jan 0001 00:00:00 +0000

The default core Kinetica log that records database interactions, startup/shutdown, error information, and more is located at /opt/gpudb/core/logs/gpudb.log. This log file can be configured to use a custom format that conforms to a rolling logging standard, enable various appenders and/or loggers, change the logging level, and more using the /opt/gpudb/core/etc/gpudb_logger.conf file. Customizing the Log Log Levels Appenders ToConsole ToSysLog ToFile ToRollingFile ToRollingDatedFile ToBacktraceFile Loggers Auditing Customizing the Log Audit Appenders Console File Rolling File Customizing the Log Review the available Log Levels.

Dashboard

Mon, 01 Jan 0001 00:00:00 +0000

The Dashboard is the home page for the AAW user interface. It provides a detailed summary of all entities stored within AAW as well as their status. Click Refresh All to refresh the Overview graphs and the entity tables below. The Overview displays a graph for each entity type: Ingests, Datasets, Models, and Deployments. Each graph is divided into portions that represent n entities that occupy one of six statuses.

Dashboard

Mon, 01 Jan 0001 00:00:00 +0000

The Dashboard page in KAgent hosts cluster and ring summary information, which provides a quick way to gather the health of your Kinetica environments. Rings Ring Summary Events Timeline Cluster Summary Rings Rings is the default view for the Dashboard page. The Rings view displays a list of the rings added to this instance of KAgent. For each ring listed, the following information is available: a list of clusters in the ring, a visual indicator of the health of each node in each cluster, and a visual indicator of the health of each rank in each cluster.

Data

Mon, 01 Jan 0001 00:00:00 +0000

Ingests Details Batch Streaming Import BYOC Datasets Details New Dataset Feature Sets Details New Feature Set Ingests An ingest is a means for getting data into Kinetica to be used in models. Point to + Add New Ingest then click one of the options to begin creating an ingest. If an ingest has an output table, click the output table name to view a preview of the table Type into Filter to filter down the ingests Click to display any archived ingests Click to refresh the table Click to export the table's values as JSON or CSV Click an existing ingest to display additional actions: Click View Selection to open the Ingest Details page Click Start to start the ingest job Click Export Entity to export the ingest as a JSON object Click Terminate to stop the ingest Click Clone to clone the ingest Click Archive to archive the ingest; it will be stopped (if not already) and hidden from the list of ingests Click Description / Config to review summary information for the ingest Details The Ingest Details page provides a detailed look at a given ingest, including configuration information, state, and a data preview (if the ingest has a destination table configured).

Data

Mon, 01 Jan 0001 00:00:00 +0000

All the data in the database can be viewed through GAdmin's Data menu selection. From here, you can manage each schema in the database and every table and view it contains; use WMS to generate a heatmap of a table or view with geocoordinates; and manage graphs. Tables Schema List Table/View List Creating Defining a Tier Strategy Partitioning Configuring Moving Deleting Rebuilding Detailed Table Information WMS Data Grid Export Data Advanced Table Security Users Roles Columns Example Graphs Create Query Solve Match Import Tables The Tables page provides information about all schemas and contained tables & views in the database in a grid layout.

Data Definition (DDL)

Mon, 01 Jan 0001 00:00:00 +0000

Column Types Column Properties CREATE SCHEMA ALTER SCHEMA Rename Schema DROP SCHEMA SHOW SCHEMA DESCRIBE SCHEMA SET CURRENT SCHEMA CREATE TABLE Partition Clause Tier Strategy Clause Index Clause Table Property Clause CREATE EXTERNAL TABLE Delimited Text Options Load Options Table Definition Clause Partition Clause Tier Strategy Clause Index Clause Table Property Clause Examples CREATE TABLE ... AS ALTER TABLE Rename Table Move Table Set Access Mode Set TTL Add Column Rename Column Modify Column Drop Column Add Column Index Drop Column Index Add Chunk Skip Index Drop Chunk Skip Index Add Geospatial Index Drop Geospatial Index Add Foreign Key Drop Foreign Key Add Partition Remove Partition Delete Partition Set Tier Strategy Manage Subscription REFRESH EXTERNAL TABLE TRUNCATE TABLE DROP TABLE SHOW TABLE DESCRIBE TABLE CREATE VIEW CREATE MATERIALIZED VIEW Table Property Clause Examples ALTER VIEW Move View ALTER MATERIALIZED VIEW Move View Set Access Mode Set Execution User Set Refresh Mode Set TTL REFRESH VIEW DROP VIEW SHOW VIEW DESCRIBE VIEW CREATE CREDENTIAL Credential Options Provider-Specific Syntax ALTER CREDENTIAL Set Properties DROP CREDENTIAL SHOW CREDENTIAL DESCRIBE CREDENTIAL CREATE DATA SOURCE Data Source Options Provider-Specific Syntax ALTER DATA SOURCE Set Properties LIST DATA SOURCE List Data Source Options DROP DATA SOURCE SHOW DATA SOURCE DESCRIBE DATA SOURCE CREATE DATA SINK Data Sink Options Consumer-Specific Syntax ALTER DATA SINK Set Properties DROP DATA SINK SHOW DATA SINK DESCRIBE DATA SINK CREATE STREAM Stream Options Consumer-Specific Syntax DROP STREAM SHOW STREAM DESCRIBE STREAM DESCRIBE Kinetica supports the basic notion of SQL tables as containers of one or more columns of data.

Data Definition (DDL)

Mon, 01 Jan 0001 00:00:00 +0000

Data Explorer

Mon, 01 Jan 0001 00:00:00 +0000

General Features Tables & Views Schema Services Table/View Services Data Sources Data Sinks Streams Graphs Context Function Environments The Data Explorer can be used to manage most object types. Data Explorer Tab To access the Data Explorer, in Workbench, click the Data tab of the left-hand navigation pane. General Features At the top of the Data Explorer tab are actions not tied to a specific object type: Search box - filters displayed objects across all three domains, by keyword Refresh icon - refreshes the list of displayed objects + icon - adds a new data object Tables & Views This section of the Data Explorer shows the list of accessible schemas at the top level, and beneath each, the set of accessible tables and views.

Data Explorer

Mon, 01 Jan 0001 00:00:00 +0000

Data Loading Concepts

Mon, 01 Jan 0001 00:00:00 +0000

Introduction The Basics of Loading Data Data Loading Interfaces Data Sources Supported Data Sources Creating a Data Source Create Credential Create Data Source SQL Examples Supported File Types Parquet Limitations Transformed Types Skipped Types JSON/GeoJSON Limitations Loading Data Workbench JDBC Client External Tables Load Into KiSQL Advanced Ingestion Type Inferencing Change Data Capture Tuning Batch Size Custom Ingest Applications 3rd Party Tools Examples File/Queue-Based Query-Based More SQL Examples Introduction Loading data in Kinetica is a nuanced process that is dependent on several factors, including the interface being used, the data source you are ingesting from, the chosen data format, and the desired access pattern for the external data.

Data Loading Concepts

Mon, 01 Jan 0001 00:00:00 +0000

Introduction The Basics of Loading Data Data Loading Interfaces Data Sources Supported Data Sources Creating a Data Source Create Credential Create Data Source SQL Examples Supported File Types Parquet Limitations Transformed Types Skipped Types JSON/GeoJSON Limitations Loading Data GAdmin Workbench JDBC Client External Tables Load Into KiSQL Advanced Ingestion Type Inferencing Change Data Capture Tuning Batch Size Custom Ingest Applications 3rd Party Tools Examples File/Queue-Based Query-Based More SQL Examples Introduction Loading data in Kinetica is a nuanced process that is dependent on several factors, including the interface being used, the data source you are ingesting from, the chosen data format, and the desired access pattern for the external data.

Data Manipulation (DML)

Mon, 01 Jan 0001 00:00:00 +0000

INSERT INSERT INTO ... VALUES INSERT INTO ... SELECT Upserting Ignoring Duplicates UPDATE Overwriting Duplicates Ignoring Duplicates DELETE INSERT There are two methods for inserting data into a table from within the database: Inserting values Copying data from another table When specifying a column list using either method, any non-nullable fields not included in the list will be given default values--empty string for strings, and 0 for numerics. The fields in the column list and the values or fields selected must align.

Data Manipulation (DML)

Mon, 01 Jan 0001 00:00:00 +0000

Data Sinks

Mon, 01 Jan 0001 00:00:00 +0000

Managing Data Sinks Creating a Data Sink Provider-Specific Syntax A data sink is reference object for a data target that is external to the database. It consists of the location & connection information to that external target. A data sink can make use of a credential object for storing remote authentication information. A data sink name must adhere to the standard naming criteria. Each data sink exists within a schema and follows the standard name resolution rules for tables.

Data Sinks

Mon, 01 Jan 0001 00:00:00 +0000

Data Sources

Mon, 01 Jan 0001 00:00:00 +0000

Managing Data Sources Creating a Data Source Provider-Specific Syntax Limitations A data source is reference object for a data set that is external to the database. It consists of the location & connection information to that external source, but doesn't hold the names of any specific data sets/files within that source. A data source can make use of a credential object for storing remote authentication information. A data source name must adhere to the standard naming criteria.

Data Sources

Mon, 01 Jan 0001 00:00:00 +0000

Date Bucketing

Mon, 01 Jan 0001 00:00:00 +0000

Date bucketing is the segmenting of a given data set into "buckets", based on some date-based column value or expression within the set. DATE_BUCKET Date bucketing is accomplished through the use of the DATE_BUCKET function, which calculates the date range in which a given timestamp falls, based on a set of fixed-width "buckets", start-aligned to a date/time, and offset from that start date/time. The basic form of the DATE_BUCKET function is:

Date Bucketing

Mon, 01 Jan 0001 00:00:00 +0000

Date/Time Types

Mon, 01 Jan 0001 00:00:00 +0000

There are three categories of date/time data types supported in both SQL and natively via API: Date Time Timestamp Support for the timestamp type comes in two flavors, depending on whether the data being ingested into Kinetica is numeric (milliseconds since the Epoch) or string (date/time literal). Once ingested, both of these types and stored and processed in the same way. SQL Date/Time Column Types Data Type Bytes Minimum Value Maximum Value Format DATE 4 1000-01-01 2900-12-31 YYYY-[M]M-[D]D 1000-01-01 2900-12-31 DATETIME 8 1000-01-01 00:00:00.

Date/Time Types

Mon, 01 Jan 0001 00:00:00 +0000

Default Ports

Mon, 01 Jan 0001 00:00:00 +0000

The default ports used for communication with Kinetica and various important services follow. Port Function 80 The non-secure listener for Kinetica application & connection traffic; will redirect automatically to the secure listener on port 443 443 The listener for applications (Workbench, Reveal, etc.) and connections (APIs, JDBC, etc.) 5432 The listener for PostgreSQL Wire Protocol connections 9002 Table monitor publishing server port. Users of database table monitors will need the ability to connect to this port to receive data generated via the table monitor.

Delete Directory

Mon, 01 Jan 0001 00:00:00 +0000

Deletes a directory from KiFS. Input Parameter Description Name Type Description directory_name string Name of the directory in KiFS to be deleted. The directory must contain no files, unless recursive is true options map of string to strings Optional parameters. The default value is an empty map ( {} ). Supported Parameters (keys) Parameter Description recursive If true, will delete directory and all files residing in it. If false, directory must be empty for deletion.

Delete Directory

Mon, 01 Jan 0001 00:00:00 +0000

Delete Files

Mon, 01 Jan 0001 00:00:00 +0000

Deletes one or more files from KiFS. Input Parameter Description Name Type Description file_names array of strings An array of names of files to be deleted. File paths may contain wildcard characters after the KiFS directory delimeter. Accepted wildcard characters are asterisk (*) to represent any string of zero or more characters, and question mark (?) to indicate a single character. options map of string to strings Optional parameters. The default value is an empty map ( {} ).

Delete Files

Mon, 01 Jan 0001 00:00:00 +0000

Delete Graph

Mon, 01 Jan 0001 00:00:00 +0000

Deletes an existing graph from the graph server and/or persist. Input Parameter Description Name Type Description graph_name string Name of the graph to be deleted. options map of string to strings Optional parameters. The default value is an empty map ( {} ). Supported Parameters (keys) Parameter Description delete_persist If set to true, the graph is removed from the server and persist. If set to false, the graph is removed from the server but is left in persist.

Delete Graph

Mon, 01 Jan 0001 00:00:00 +0000

Delete Proc

Mon, 01 Jan 0001 00:00:00 +0000

Deletes a proc. Any currently running instances of the proc will be killed. Input Parameter Description Name Type Description proc_name string Name of the proc to be deleted. Must be the name of a currently existing proc. options map of string to strings Optional parameters. The default value is an empty map ( {} ). Output Parameter Description Name Type Description proc_name string Value of input parameter proc_name. info map of string to strings Additional information.

Delete Proc

Mon, 01 Jan 0001 00:00:00 +0000

Delete Records

Mon, 01 Jan 0001 00:00:00 +0000

Deletes record(s) matching the provided criteria from the given table. The record selection criteria can either be one or more input parameter expressions (matching multiple records), a single record identified by record_id options, or all records when using delete_all_records. Note that the three selection criteria are mutually exclusive. This operation cannot be run on a view. The operation is synchronous meaning that a response will not be available until the request is completely processed and all the matching records are deleted.

Delete Records

Mon, 01 Jan 0001 00:00:00 +0000

Delete Resource Group

Mon, 01 Jan 0001 00:00:00 +0000

Deletes a resource group. Input Parameter Description Name Type Description name string Name of the resource group to be deleted. options map of string to strings Optional parameters. The default value is an empty map ( {} ). Supported Parameters (keys) Parameter Description cascade_delete If true, delete any existing entities owned by this group. Otherwise this request will return an error of any such entities exist. The default value is false.

Delete Resource Group

Mon, 01 Jan 0001 00:00:00 +0000

Delete Role

Mon, 01 Jan 0001 00:00:00 +0000

Deletes an existing role. NOTE: This endpoint should be used for on-premise deployments only. Input Parameter Description Name Type Description name string Name of the role to be deleted. Must be an existing role. options map of string to strings Optional parameters. The default value is an empty map ( {} ). Output Parameter Description Name Type Description name string Value of input parameter name. info map of string to strings Additional information.

Delete Role

Mon, 01 Jan 0001 00:00:00 +0000

Delete User

Mon, 01 Jan 0001 00:00:00 +0000

Deletes an existing user. NOTE: This endpoint should be used for on-premise deployments only. Input Parameter Description Name Type Description name string Name of the user to be deleted. Must be an existing user. options map of string to strings Optional parameters. The default value is an empty map ( {} ). Output Parameter Description Name Type Description name string Value of input parameter name. info map of string to strings Additional information.

Delete User

Mon, 01 Jan 0001 00:00:00 +0000

Deployments

Mon, 01 Jan 0001 00:00:00 +0000

A deployment is essentially an active model; if a model is deployed, inferences can be tested against it. After a model has been deployed, an entry for that deployment will be available on the Deployments page. AAW currently supports three types of deployments: On Demand, Batch, and Continuous. On Demand deployments can be tested manually and as necessary with user input. Batch deployments inference on a batch of data all at once.

Determining the Kinetica Connection URL

Mon, 01 Jan 0001 00:00:00 +0000

The URL for connecting to Kinetica can be found within the AWS Console. Sign into the AWS Console at: https://aws.amazon.com/console Search for CloudFormation in the console search bar. Choose the AWS Region where you originally deployed the stack (e.g., us-west-2). Select the original stack you created (not the nested stacks), and then click on the Outputs tab. The value in the workbenchUrl key is the URL for the Workbench application in Kinetica.

Dictionary Encoding

Mon, 01 Jan 0001 00:00:00 +0000

Dictionary encoding is a data compression technique that can be applied to individual columns of the following effective types: int long date char1 - char256 It will store each unique value of a column in memory and associate each record with its corresponding unique value. This eliminates the storage of duplicate values in a column, reducing the overall memory & disk space required to hold the data. Dictionary encoding is most effective on columns with low cardinality; the fewer the number of unique values within a column, the greater the reduction in memory usage.

Dictionary Encoding

Mon, 01 Jan 0001 00:00:00 +0000

Distributed Graph Servers

Mon, 01 Jan 0001 00:00:00 +0000

Kinetica enables distributed graph servers, in which the additional CPU power from distributed graph server hosts can be leveraged to make all types of graph operations more performant. Leveraging Distributed Graph Servers Examples Leveraging Distributed Graph Servers Each graph server will be provided an ID that will allow users to reference it during graph API endpoint operations. The system will automatically leverage distributed graph servers for each graph endpoint. For situations that demand more control over where graph operations are performed, users can specify the graph server ID when sending a graph-related endpoint request.

Distributed Graph Servers

Mon, 01 Jan 0001 00:00:00 +0000

In Kinetica versions 7.1.2 and greater, distributed graph servers are able to be initialized during the installation process. If distributed graph servers are enabled, the additional CPU power from distributed graph server hosts can be leveraged to make all types of graph operations more performant. Installation & Configuration Leveraging Distributed Graph Servers Examples Distributed Graph Server User Interface (UI) Installation & Configuration As mentioned above, determining if a cluster should have distributed graph servers happens during the nodes configuration process of the installation process.

Download Files

Mon, 01 Jan 0001 00:00:00 +0000

Downloads one or more files from KiFS. Input Parameter Description Name Type Description file_names array of strings An array of the file names to download from KiFS. File paths may contain wildcard characters after the KiFS directory delimeter. Accepted wildcard characters are asterisk (*) to represent any string of zero or more characters, and question mark (?) to indicate a single character. read_offsets array of longs An array of starting byte offsets from which to read each respective file in input parameter file_names.

Download Files

Mon, 01 Jan 0001 00:00:00 +0000

Downloads

Mon, 01 Jan 0001 00:00:00 +0000

Tip All of the downloads below (plus ODBC Mac and Linux clients) are available in Workbench on the home screen, under Getting Started ‣ API Downloads. Database API Downloads The database API bindings for each language can be found below. Name Repository Reference C++ C++ GitHub Repo C++ API Reference C++ API Tutorial C# C# GitHub Repo C# API Reference Java Java GitHub Repo Java API Reference Java API Tutorial JavaScript JavaScript GitHub Repo JavaScript API Reference JavaScript Developer Manual Node.

Downloads

Mon, 01 Jan 0001 00:00:00 +0000

Tip All of the downloads below (plus ODBC Mac and Linux clients) are available in GAdmin (Support ‣ APIs or Support ‣ Drivers) and in the /opt/gpudb/downloads/ directory on any server with Kinetica installed. Database API Downloads The database API bindings for each language can be found below. Name Repository Reference C++ C++ GitHub Repo C++ API Reference C++ API Tutorial C# C# GitHub Repo C# API Reference Java Java GitHub Repo Java API Reference Java API Tutorial JavaScript JavaScript GitHub Repo JavaScript API Reference JavaScript Developer Manual Node.

Drop Credential

Mon, 01 Jan 0001 00:00:00 +0000

Drop an existing credential. Input Parameter Description Name Type Description credential_name string Name of the credential to be dropped. Must be an existing credential. options map of string to strings Optional parameters. The default value is an empty map ( {} ). Output Parameter Description Name Type Description credential_name string Value of input parameter credential_name. info map of string to strings Additional information.

Drop Credential

Mon, 01 Jan 0001 00:00:00 +0000

Drop Data Sink

Mon, 01 Jan 0001 00:00:00 +0000

Drops an existing data sink. By default, if any table monitors use this sink as a destination, the request will be blocked unless option clear_table_monitors is true. Input Parameter Description Name Type Description name string Name of the data sink to be dropped. Must be an existing data sink. options map of string to strings Optional parameters. The default value is an empty map ( {} ). Supported Parameters (keys) Parameter Description clear_table_monitors If true, any table monitors that use this data sink will be cleared.

Drop Data Sink

Mon, 01 Jan 0001 00:00:00 +0000

Drop Data Source

Mon, 01 Jan 0001 00:00:00 +0000

Drops an existing data source. Any external tables that depend on the data source must be dropped before it can be dropped. Input Parameter Description Name Type Description name string Name of the data source to be dropped. Must be an existing data source. options map of string to strings Optional parameters. The default value is an empty map ( {} ). Output Parameter Description Name Type Description name string Value of input parameter name.

Drop Data Source

Mon, 01 Jan 0001 00:00:00 +0000

Drop Schema

Mon, 01 Jan 0001 00:00:00 +0000

Drops an existing SQL-style schema, specified in input parameter schema_name. Input Parameter Description Name Type Description schema_name string Name of the schema to be dropped. Must be an existing schema. options map of string to strings Optional parameters. The default value is an empty map ( {} ). Supported Parameters (keys) Parameter Description no_error_if_not_exists If true and if the schema specified in input parameter schema_name does not exist, no error is returned.

Drop Schema

Mon, 01 Jan 0001 00:00:00 +0000

Drop UDF Environment

Mon, 01 Jan 0001 00:00:00 +0000

Drop an existing user-defined function (UDF) environment. Input Parameter Description Name Type Description environment_name string Name of the environment to be dropped. Must be an existing environment. options map of string to strings Optional parameters. The default value is an empty map ( {} ). Supported Parameters (keys) Parameter Description no_error_if_not_exists If true and if the environment specified in input parameter environment_name does not exist, no error is returned. If false and if the environment specified in input parameter environment_name does not exist, then an error is returned.

Drop UDF Environment

Mon, 01 Jan 0001 00:00:00 +0000

Dynamic Schemas

Mon, 01 Jan 0001 00:00:00 +0000

Dynamic Schemas in Python Dynamic Schemas in Java For some endpoints (e.g. /aggregate/groupby, /aggregate/unique, /get/records/bycolumn), the response from Kinetica is formatted depending on the request and the data being returned. This is known as a dynamic schema. The response will contain an Avro schema string (in the response_schema_str field) and then either an Avro binary encoded response (in the binary_encoded_response field) or an Avro JSON encoded response (in the json_encoded_response field).

Dynamic Schemas

Mon, 01 Jan 0001 00:00:00 +0000

Event Codes

Mon, 01 Jan 0001 00:00:00 +0000

When adding an Event Alert, there are many event codes to choose from. You can search through the available events in the event alert creation window using one of the event codes below or using keywords from a description of the desired event, e.g., shutdown, standby, etc. The events are organized by Kinetica component. Cluster Operations HTTPD High Availability (HA) Host Manager Machine Learning (ML) Monitoring Rank Operations Reveal SQL Query Planner Cluster Operations Event Code Severity Description / Log Message 01.

Event Codes

Mon, 01 Jan 0001 00:00:00 +0000

Events

Mon, 01 Jan 0001 00:00:00 +0000

The Events page in KAgent hosts a running log of all events that have occurred. Events are configured via the Alerts page. Review Event Codes for a list of all available events. Actions The available actions on the Events page are as follows: Refresh the list of events by clicking Refresh Update any of the Advanced Filter fields and click Apply Filter to filter the events list based on the provided values.

Example UDF (CUDA) - cuBLAS

Mon, 01 Jan 0001 00:00:00 +0000

The following is a complete example, using the Python API, of a CUDA-based UDF that performs various computations using the scikit-CUDA interface. It will take two vectors and one matrix of data loaded from a Kinetica table and perform various operations in both NumPy & cuBLAS, writing the comparison output to the system log. This setup assumes the UDF is being developed on the Kinetica host (or head node host, if a multi-node Kinetica cluster); and that the Python database API is available at /opt/gpudb/api/python and the Python UDF API is available at /opt/gpudb/udf/api/python.

Example UDF (CUDA) - Sum of Squares

Mon, 01 Jan 0001 00:00:00 +0000

The following implements the sum-of-squares algorithm as a distributed UDF using the CUDA-based UDF C++ API. The initialization script will be run separately from the UDF itself, and the execution script will need to target the UDF C++ binary. This example will take a list of input tables and corresponding output tables (must be the same number) and, for each record of each input table, sums the squares of all input table columns and saves the result to the first column of the corresponding output table record; i.

Example UDF (Non-CUDA) - Distributed Model

Mon, 01 Jan 0001 00:00:00 +0000

The following is a complete example, using the Python UDF API, of a non-CUDA UDF that demonstrates how to build multiple models based on distributed data and combine them into an ensemble. This example (and others) can be found in the Python UDF API repository; this repository can be downloaded/cloned from GitHub. References Prerequisites UDF API Download Relevant Scripts UDF Deployment Execution Detail Database Setup Model Training UDF (dt_train.py) Training UDF Registration (register_execute_train.

Example UDF (Non-CUDA) - Distributed Model

Mon, 01 Jan 0001 00:00:00 +0000

Example UDF (Non-CUDA) - Pandas

Mon, 01 Jan 0001 00:00:00 +0000

The following is a complete example, using the Python UDF API, of a non-CUDA UDF that demonstrates how to create pandas dataframes and insert them into tables in Kinetica. This example (and others) can be found in the Python UDF API repository; this repository can be downloaded/cloned from GitHub. References Prerequisites UDF API Download Relevant Scripts UDF Deployment Execution Detail Database Setup UDF (df_to_output_UDF.py) UDF Registration (register_execute_UDF.py) References Python UDF Reference -- detailed description of the entire UDF API Running UDFs -- detailed description on running Python UDFs Example UDFs -- example UDFs written in Python Prerequisites The general prerequisites for using UDFs in Kinetica can be found under UDF Prerequisites.

Example UDF (Non-CUDA) - Pandas

Mon, 01 Jan 0001 00:00:00 +0000

Example UDF (Non-CUDA) - Sum of Squares

Mon, 01 Jan 0001 00:00:00 +0000

Download & Run UDF Detail Initialization (udf_sos_manager.py init) UDF (udf_sos_proc.py) Execution (udf_sos_manager.py exec) The following is a complete example, using the Python API, of a non-CUDA UDF that takes a list of input tables and corresponding output tables (must be the same number) and, for each record of each input table, sums the squares of input table columns and saves the result to the corresponding output table column; i.e.:

Example UDF (Non-CUDA) - Sum of Squares

Mon, 01 Jan 0001 00:00:00 +0000

Except

Mon, 01 Jan 0001 00:00:00 +0000

An except is a representation of all unique rows in one data set (table or view) that do not appear in another. See EXCEPT for the SQL version of this operation. An except is performed via the /create/union endpoint using the except or except_all mode: Except -- all unique rows that exist in one data set, but not the other Except All -- all rows (including duplicates) that exist in one data set, but not the other You can only perform an except two data sets, and the columns between the two must have similar data types.

Except

Mon, 01 Jan 0001 00:00:00 +0000

Execute Proc

Mon, 01 Jan 0001 00:00:00 +0000

Executes a proc. This endpoint is asynchronous and does not wait for the proc to complete before returning. If the proc being executed is distributed, input parameter input_table_names & input parameter input_column_names may be passed to the proc to use for reading data, and input parameter output_table_names may be passed to the proc to use for writing data. If the proc being executed is non-distributed, these table parameters will be ignored.

Execute Proc

Mon, 01 Jan 0001 00:00:00 +0000

Execute SQL

Mon, 01 Jan 0001 00:00:00 +0000

Execute a SQL statement (query, DML, or DDL). See SQL Support for the complete set of supported SQL commands. Input Parameter Description Name Type Description statement string SQL statement (query, DML, or DDL) to be executed offset long A positive integer indicating the number of initial results to skip (this can be useful for paging through the results). The default value is 0.The minimum allowed value is 0. The maximum allowed value is MAX_INT.

Execute SQL

Mon, 01 Jan 0001 00:00:00 +0000

Export records from table

Mon, 01 Jan 0001 00:00:00 +0000

Export records from a table to files. All tables can be exported, in full or partial (see columns_to_export and columns_to_skip). Additional filtering can be applied when using export table with expression through SQL. Default destination is KIFS, though other storage types (Azure, S3, GCS, and HDFS) are supported through datasink_name; see Create Data Sink. Server's local file system is not supported. Default file format is delimited text. See options for different file types and different options for each file type.

Export records from table

Mon, 01 Jan 0001 00:00:00 +0000

Exporting Data

Mon, 01 Jan 0001 00:00:00 +0000

EXPORT ... INTO Delimited Text Options Export Options Examples EXPORT ... INTO Kinetica can export data from one or more tables, using an EXPORT ... INTO statement. The data can be exported to either of the following: KiFS a data sink configured to allow write access to: remote files on Azure, GCS, HDFS, or S3 a writable remote database table via JDBC (or CData JDBC) Note For contextualized examples, see Examples.

Exporting Data

Mon, 01 Jan 0001 00:00:00 +0000

Expressions

Mon, 01 Jan 0001 00:00:00 +0000

Kinetica has native API support for a variety of expressions, which are used as inputs while querying data (for supported SQL expressions, see Queries (SQL) ). These native API expressions can involve one or more constants (both numeric and string) and table columns; however, expressions cannot be applied to store-only columns. The expressions follow certain constraints based on where they are used, but all the expressions should follow the basic guidelines outlined below.

Expressions

Mon, 01 Jan 0001 00:00:00 +0000

External Authentication Configuration

Mon, 01 Jan 0001 00:00:00 +0000

External authentication data store integration with Kinetica is accomplished through an Apache HTTPD proxy. This proxy comes packaged with Kinetica and can be found in /opt/gpudb/httpd. Since this portion is controlled by Apache HTTP not Kinetica, see the Apache documentation for further details. External authentication can be configured for Kinetica with or without SSL. Kinetica currently supports the following external authentication sources: LDAP Microsoft Active Directory Kerberos Important See Obfuscating Plain-Text Passwords for an example of obfuscating the plain-text LDAP/AD password in the HTTPD configuration file.

External Tables

Mon, 01 Jan 0001 00:00:00 +0000

Types Data File Formats Table Features Data Sources Ingestion Mode Refresh on Start Error Mode Creating an External Table An external table is a database object whose source data is located in one or more files external to the database. The source data can be located in either of the following locations: in KiFS on a remote system, accessible via a data source External tables are created via the /create/table/external native API call.

External Tables

Mon, 01 Jan 0001 00:00:00 +0000

File Explorer

Mon, 01 Jan 0001 00:00:00 +0000

General Features File List The File Explorer can be used to manage directories & files in Kinetica File System (KiFS). File Explorer Tab To access the File Explorer, in Workbench, click the Files tab of the left-hand navigation pane. General Features At the top of the File Explorer tab are several file/directory actions: Search box - filter displayed files & directories, by name; directory matches will result in all files in that directory being displayed Refresh icon - refresh the list of displayed files & directories + icon - create a new directory or upload a file File List The File Explorer displays a list of top-level directories and the set of files contained within them.

File Explorer

Mon, 01 Jan 0001 00:00:00 +0000

File Upload Import

Mon, 01 Jan 0001 00:00:00 +0000

Import Overview Setup Source Destination Configure Summary Using the File Upload Import wizard, local files can be staged in KiFS and imported into Kinetica. Once in KiFS, they can subsequently be imported via the Kinetica Filesystem import wizard or via SQL's LOAD INTO command, or be made the source of data for an external table, among other uses. To upload a local file to KiFS and import the data into Kinetica, click on the File Upload panel on the Import landing page in Workbench.

File Upload Import

Mon, 01 Jan 0001 00:00:00 +0000

Files & Directories (KiFS)

Mon, 01 Jan 0001 00:00:00 +0000

CREATE DIRECTORY ALTER DIRECTORY Set Data Limit LIST DIRECTORY DOWNLOAD DIRECTORY DROP DIRECTORY UPLOAD FILE UPLOAD URL LIST FILE DOWNLOAD FILE DROP FILE Kinetica, via KiFS, provides support for staging files within the database for subsequent ingestion. The file structure consists of a single layer of top-level directories, with each file contained within one of those directories. File names can contain / characters to give the appearance of existing under a hierarchy of one or more sub-directories.

Files & Directories (KiFS)

Mon, 01 Jan 0001 00:00:00 +0000

Filter

Mon, 01 Jan 0001 00:00:00 +0000

Filters data based on the specified expression. The results are stored in a result set with the given input parameter view_name. For details see Expressions. The response message contains the number of points for which the expression evaluated to be true, which is equivalent to the size of the result view. Input Parameter Description Name Type Description table_name string Name of the table to filter, in [schema_name.]table_name format, using standard name resolution rules.

Filter

Mon, 01 Jan 0001 00:00:00 +0000

Filter by Area

Mon, 01 Jan 0001 00:00:00 +0000

Calculates which objects from a table are within a named area of interest (NAI/polygon). The operation is synchronous, meaning that a response will not be returned until all the matching objects are fully available. The response payload provides the count of the resulting set. A new resultant set (view) which satisfies the input NAI restriction specification is created with the name input parameter view_name passed in as part of the input.

Filter by Area

Mon, 01 Jan 0001 00:00:00 +0000

Filter by Box

Mon, 01 Jan 0001 00:00:00 +0000

Calculates how many objects within the given table lie in a rectangular box. The operation is synchronous, meaning that a response will not be returned until all the objects are fully available. The response payload provides the count of the resulting set. A new resultant set which satisfies the input NAI restriction specification is also created when a input parameter view_name is passed in as part of the input payload.

Filter by Box

Mon, 01 Jan 0001 00:00:00 +0000

Filter by Geometry

Mon, 01 Jan 0001 00:00:00 +0000

Applies a geometry filter against a geospatial geometry column in a given table or view. The filtering geometry is provided by input parameter input_wkt. Input Parameter Description Name Type Description table_name string Name of the table on which the filter by geometry will be performed, in [schema_name.]table_name format, using standard name resolution rules. Must be an existing table or view containing a geospatial geometry column. view_name string If provided, then this will be the name of the view containing the results, in [schema_name.

Filter by Geometry

Mon, 01 Jan 0001 00:00:00 +0000

Filter by List

Mon, 01 Jan 0001 00:00:00 +0000

Calculates which records from a table have values in the given list for the corresponding column. The operation is synchronous, meaning that a response will not be returned until all the objects are fully available. The response payload provides the count of the resulting set. A new resultant set (view) which satisfies the input filter specification is also created if a input parameter view_name is passed in as part of the request.

Filter by List

Mon, 01 Jan 0001 00:00:00 +0000

Filter by Radius

Mon, 01 Jan 0001 00:00:00 +0000

Calculates which objects from a table lie within a circle with the given radius and center point (i.e. circular NAI). The operation is synchronous, meaning that a response will not be returned until all the objects are fully available. The response payload provides the count of the resulting set. A new resultant set (view) which satisfies the input circular NAI restriction specification is also created if a input parameter view_name is passed in as part of the request.

Filter by Radius

Mon, 01 Jan 0001 00:00:00 +0000

Filter by Range

Mon, 01 Jan 0001 00:00:00 +0000

Calculates which objects from a table have a column that is within the given bounds. An object from the table identified by input parameter table_name is added to the view input parameter view_name if its column is within [input parameter lower_bound, input parameter upper_bound] (inclusive). The operation is synchronous. The response provides a count of the number of objects which passed the bound filter. Although this functionality can also be accomplished with the standard filter function, it is more efficient.

Filter by Range

Mon, 01 Jan 0001 00:00:00 +0000

Filter by Series

Mon, 01 Jan 0001 00:00:00 +0000

Filters objects matching all points of the given track (works only on track type data). It allows users to specify a particular track to find all other points in the table that fall within specified ranges (spatial and temporal) of all points of the given track. Additionally, the user can specify another track to see if the two intersect (or go close to each other within the specified ranges). The user also has the flexibility of using different metrics for the spatial distance calculation: Euclidean (flat geometry) or Great Circle (spherical geometry to approximate the Earth's surface distances).

Filter by Series

Mon, 01 Jan 0001 00:00:00 +0000

Filter by String

Mon, 01 Jan 0001 00:00:00 +0000

Calculates which objects from a table or view match a string expression for the given string columns. Setting case_sensitive can modify case sensitivity in matching for all modes except search. For search mode details and limitations, see Full Text Search. Input Parameter Description Name Type Description table_name string Name of the table on which the filter operation will be performed, in [schema_name.]table_name format, using standard name resolution rules. Must be an existing table or view.

Filter by String

Mon, 01 Jan 0001 00:00:00 +0000

Filter by Table

Mon, 01 Jan 0001 00:00:00 +0000

Filters objects in one table based on objects in another table. The user must specify matching column types from the two tables (i.e. the target table from which objects will be filtered and the source table based on which the filter will be created); the column names need not be the same. If a input parameter view_name is specified, then the filtered objects will then be put in a newly created view.

Filter by Table

Mon, 01 Jan 0001 00:00:00 +0000

Filter by Value

Mon, 01 Jan 0001 00:00:00 +0000

Calculates which objects from a table has a particular value for a particular column. The input parameters provide a way to specify either a String or a Double valued column and a desired value for the column on which the filter is performed. The operation is synchronous, meaning that a response will not be returned until all the objects are fully available. The response payload provides the count of the resulting set.

Filter by Value

Mon, 01 Jan 0001 00:00:00 +0000

Filter Geometry by Area

Mon, 01 Jan 0001 00:00:00 +0000

Calculates which geospatial geometry objects from a table intersect a named area of interest (NAI/polygon). The operation is synchronous, meaning that a response will not be returned until all the matching objects are fully available. The response payload provides the count of the resulting set. A new resultant set (view) which satisfies the input NAI restriction specification is created with the name input parameter view_name passed in as part of the input.

Filter Geometry by Area

Mon, 01 Jan 0001 00:00:00 +0000

Filter Geometry by Box

Mon, 01 Jan 0001 00:00:00 +0000

Calculates which geospatial geometry objects from a table intersect a rectangular box. The operation is synchronous, meaning that a response will not be returned until all the objects are fully available. The response payload provides the count of the resulting set. A new resultant set which satisfies the input NAI restriction specification is also created when a input parameter view_name is passed in as part of the input payload.

Filter Geometry by Box

Mon, 01 Jan 0001 00:00:00 +0000

Filter Geometry by Radius

Mon, 01 Jan 0001 00:00:00 +0000

Calculates which geospatial geometry objects from a table intersect a circle with the given radius and center point (i.e. circular NAI). The operation is synchronous, meaning that a response will not be returned until all the objects are fully available. The response payload provides the count of the resulting set. A new resultant set (view) which satisfies the input circular NAI restriction specification is also created if a input parameter view_name is passed in as part of the request.

Filter Geometry by Radius

Mon, 01 Jan 0001 00:00:00 +0000

Filtered Views

Mon, 01 Jan 0001 00:00:00 +0000

A filtered view is a queryable filter of a table or another view. A filtered view can be created by filtering an existing table or view using the /filter endpoint. Filtered views can be updated to insert the missing data points for a series from the underlying table using /update/records/byseries. Given the need to minimize memory usage, filtered views are given a default time-to-live, after which they will expire and be removed from memory.

Filtered Views

Mon, 01 Jan 0001 00:00:00 +0000

Full Text Search

Mon, 01 Jan 0001 00:00:00 +0000

The SQL FILTER_BY_STRING function, as well as the /filter/bystring endpoint, enables the use of several string-based search modes, including full text search via the search mode. The syntax and restrictions for this search follow, including examples of applying different search criteria. In order for a full text search to be applied to a column, it must be a string type and have the text_search column property applied. The following effective types under the string base type are text-searchable:

Full Text Search

Mon, 01 Jan 0001 00:00:00 +0000

The SQL FILTER_BY_STRING function, as well as the /filter/bystring endpoint, enables the use of several string-based search modes, including full text search via the search mode. The syntax and restrictions for this search follow, including examples of applying different search criteria. In order for a full text search to be applied to a column, the following requirements must be met: Full text search must be enabled by setting enable_text_search to true in the /opt/gpudb/core/etc/gpudb.

Geospatial Examples

Mon, 01 Jan 0001 00:00:00 +0000

The following are complete examples for utilizing geospatial data, geospatial functions, and the Kinetica Web Mapping Service (WMS). Using WKT Data and Geospatial Functions Example of ingesting WKT data and using geospatial functions via SQL and the Kinetica Python API Generate Isochrones Example of generating images containing isochrones using an existing graph and the /visualize/isochrone and /wms endpoints Geospatial Partitioning Example of partitioning geospatial data to improve the performance of locality-based geospatial lookups

Geospatial Examples

Mon, 01 Jan 0001 00:00:00 +0000

Geospatial Objects

Mon, 01 Jan 0001 00:00:00 +0000

Points A point can be any record that has fields containing the longitude and latitude of a geospatial point. Shapes Kinetica supports the following WKT types: Point, LineString, Polygon, MultiPoint, MultiLineString, MultiPolygon, and GeometryCollection. WKT shapes can include a z-level value ranging from -128 to +128 but rendering points on the z-axis (e.g., via /wms or Workbench as either a Table/View WMS Preview or a Worksheet Map Block) is currently not supported.

Geospatial Objects

Mon, 01 Jan 0001 00:00:00 +0000

Points A point can be any record that has fields containing the longitude and latitude of a geospatial point. Shapes Kinetica supports the following WKT types: Point, LineString, Polygon, MultiPoint, MultiLineString, MultiPolygon, and GeometryCollection. WKT shapes can include a z-level value ranging from -128 to +128 but rendering points on the z-axis (e.g., via /wms or GAdmin) is currently not supported. Note Though LINEARRING WKT types may be inserted into tables, any LINEARRINGs used within a geospatial function will be converted to a LINESTRING

Geospatial Queries

Mon, 01 Jan 0001 00:00:00 +0000

Geospatial Partitioning Geospatial partitioning is a method for organizing geospatial data, grouping spatial entities in close proximity to each other. This geospatial grouping allows for accelerated geospatial processing of the grouped data. Geospatial joins, specifically, will take advantage of this process improvement. An increase in performance using this technique will be proportional to the size of the data being joined. Example The goal of the geospatial join in this example is to show flights that landed at (or passed over) JFK airport.

Geospatial Queries

Mon, 01 Jan 0001 00:00:00 +0000

Geospatial/Geometry Functions

Mon, 01 Jan 0001 00:00:00 +0000

Enhanced Performance Scalar Functions Scalar Functions Aggregation Functions Track Functions ST_TRACK_DWITHIN ST_TRACKINTERSECTS H3 Functions Five types of geospatial functions are available in Kinetica: Scalar Functions - apply a geospatial function at the record level to WKT or X/Y data Enhanced Performance Scalar Functions - apply performance-optimized geospatial functions to X/Y data Aggregate Functions - apply a geospatial function across groups of records to WKT or X/Y data Track Functions - apply scalar & aggregate functions to track-based data H3 Functions - apply H3 gridding functions to WKT or X/Y data Tip

Geospatial/Geometry Functions

Mon, 01 Jan 0001 00:00:00 +0000

Get Asynchronous Job Result

Mon, 01 Jan 0001 00:00:00 +0000

Get the status and result of asynchronously running job. See the Create Asynchronous Job for starting an asynchronous job. Some fields of the response are filled only after the submitted job has finished execution. Input Parameter Description Name Type Description job_id long A unique identifier for the job whose status and result is to be fetched. options map of string to strings Optional parameters. The default value is an empty map ( {} ).

Get Asynchronous Job Result

Mon, 01 Jan 0001 00:00:00 +0000

Get JSON Records

Mon, 01 Jan 0001 00:00:00 +0000

Overview Usage Parameters Examples Responses Overview Kinetica provides a direct JSON egress service to allow records to be retrieved as raw JSON from the database. Several options can be used to identify & filter the data being requested. There is also limited support for aggregation. JSON objects will be returned as an array: Single or Multiple Records 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 [ { "id": 1, "category": "Furniture", "name": "Clamp-on Lamps", "description": "Strong, steadfast fasteners; localized lighting for laboring", "stock": 10 }, { "id": 14, "category": "Technology", "name": "Dot Matrix Printers", "description": "Impactful industrial implements for impressing ink iteratively", "stock": 27 } ] For examples, see Examples or JSON Egress Snippets.

Get JSON Records

Mon, 01 Jan 0001 00:00:00 +0000

Get Records

Mon, 01 Jan 0001 00:00:00 +0000

Retrieves records from a given table, optionally filtered by an expression and/or sorted by a column. This operation can be performed on tables and views. Records can be returned encoded as binary, json, or geojson. This operation supports paging through the data via the input parameter offset and input parameter limit parameters. Note that when paging through a table, if the table (or the underlying table in case of a view) is updated (records are inserted, deleted or modified) the records retrieved may differ between calls based on the updates applied.

Get Records

Mon, 01 Jan 0001 00:00:00 +0000

Get Records by Column

Mon, 01 Jan 0001 00:00:00 +0000

For a given table, retrieves the values from the requested column(s). Maps of column name to the array of values as well as the column data type are returned. This endpoint supports pagination with the input parameter offset and input parameter limit parameters. Window functions, which can perform operations like moving averages, are available through this endpoint as well as Create Projection. When using pagination, if the table (or the underlying table in the case of a view) is modified (records are inserted, updated, or deleted) during a call to the endpoint, the records or values retrieved may differ between calls based on the type of the update, e.

Get Records by Column

Mon, 01 Jan 0001 00:00:00 +0000

Get Records by Series

Mon, 01 Jan 0001 00:00:00 +0000

Retrieves the complete series/track records from the given input parameter world_table_name based on the partial track information contained in the input parameter table_name. This operation supports paging through the data via the input parameter offset and input parameter limit parameters. In contrast to Get Records this returns records grouped by series/track. So if input parameter offset is 0 and input parameter limit is 5 this operation would return the first 5 series/tracks in input parameter table_name.

Get Records by Series

Mon, 01 Jan 0001 00:00:00 +0000

Get Records from Collection

Mon, 01 Jan 0001 00:00:00 +0000

Retrieves records from a collection. The operation can optionally return the record IDs which can be used in certain queries such as Delete Records. This operation supports paging through the data via the input parameter offset and input parameter limit parameters. Note that when using the Java API, it is not possible to retrieve records from join views using this operation. (DEPRECATED) Input Parameter Description Name Type Description table_name string Name of the collection or table from which records are to be retrieved, in [schema_name.

Get Records from Collection

Mon, 01 Jan 0001 00:00:00 +0000

GPU Driver

Mon, 01 Jan 0001 00:00:00 +0000

GPU Driver Matrix Cards Preferred The cards below have been tested in large-scale production environments and provide the best performance for the database. GPU Driver Kinetica Package P4/P40/P100 470.X (or higher) gpudb-cuda-license V100 470.X (or higher) gpudb-cuda-license T4 470.X (or higher) gpudb-cuda-license A10/A40/A100 470.X (or higher) gpudb-cuda-license Supported The cards below are supported for Kinetica but should only be used for smaller, testing workloads or as necessary. GPU Driver Kinetica Package 750ti 470.

Grant Credential Permission

Mon, 01 Jan 0001 00:00:00 +0000

Grants a credential-level permission to a user or role. Input Parameter Description Name Type Description name string Name of the user or role to which the permission will be granted. Must be an existing user or role. permission string Permission to grant to the user or role. Supported Values Description credential_admin Full read/write and administrative access on the credential. credential_read Ability to read and use the credential. credential_name string Name of the credential on which the permission will be granted.

Grant Credential Permission

Mon, 01 Jan 0001 00:00:00 +0000

Grant Data Source Permission

Mon, 01 Jan 0001 00:00:00 +0000

Grants a data source permission to a user or role. Input Parameter Description Name Type Description name string Name of the user or role to which the permission will be granted. Must be an existing user or role. permission string Permission to grant to the user or role Supported Values Description admin Admin access on the given data source connect Connect access on the given data source datasource_name string Name of the data source on which the permission will be granted.

Grant Data Source Permission

Mon, 01 Jan 0001 00:00:00 +0000

Grant Directory Permission

Mon, 01 Jan 0001 00:00:00 +0000

Grants a KiFS directory-level permission to a user or role. Input Parameter Description Name Type Description name string Name of the user or role to which the permission will be granted. Must be an existing user or role. permission string Permission to grant to the user or role. Supported Values Description directory_read For files in the directory, access to list files, download files, or use files in server side functions directory_write Access to upload files to, or delete files from, the directory.

Grant Directory Permission

Mon, 01 Jan 0001 00:00:00 +0000

Grant Permission

Mon, 01 Jan 0001 00:00:00 +0000

Grant user or role the specified permission on the specified object. Input Parameter Description Name Type Description principal string Name of the user or role for which the permission is being granted. Must be an existing user or role. The default value is ''. object string Name of object permission is being granted to. It is recommended to use a fully-qualified name when possible. object_type string The type of object being granted to

Grant Permission

Mon, 01 Jan 0001 00:00:00 +0000

Grant Proc Permission

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Grants a proc-level permission to a user or role. Input Parameter Description Name Type Description name string Name of the user or role to which the permission will be granted. Must be an existing user or role. permission string Permission to grant to the user or role. Supported Values Description proc_admin Admin access to the proc. proc_execute Execute access to the proc. proc_name string Name of the proc to which the permission grants access.

Grant Proc Permission

Mon, 01 Jan 0001 00:00:00 +0000

Grant Role

Mon, 01 Jan 0001 00:00:00 +0000

Grants membership in a role to a user or role. Input Parameter Description Name Type Description role string Name of the role in which membership will be granted. Must be an existing role. member string Name of the user or role that will be granted membership in input parameter role. Must be an existing user or role. options map of string to strings Optional parameters. The default value is an empty map ( {} ).

Grant Role

Mon, 01 Jan 0001 00:00:00 +0000

Grant System Permission

Mon, 01 Jan 0001 00:00:00 +0000

Grants a system-level permission to a user or role. Input Parameter Description Name Type Description name string Name of the user or role to which the permission will be granted. Must be an existing user or role. permission string Permission to grant to the user or role. Supported Values Description system_admin Full access to all data and system functions. system_user_admin Access to administer users and roles that do not have system_admin permission.

Grant System Permission

Mon, 01 Jan 0001 00:00:00 +0000

Grant Table Permission

Mon, 01 Jan 0001 00:00:00 +0000

Grants a table-level permission to a user or role. Input Parameter Description Name Type Description name string Name of the user or role to which the permission will be granted. Must be an existing user or role. permission string Permission to grant to the user or role. Supported Values Description table_admin Full read/write and administrative access to the table. table_insert Insert access to the table. table_update Update access to the table.

Grant Table Permission

Mon, 01 Jan 0001 00:00:00 +0000

Grouping Sets

Mon, 01 Jan 0001 00:00:00 +0000

The grouping sets operation calculates aggregates over any user-specified dimensions. It offers much more flexibility and customizability over the Cube and Rollup functions, while allowing both as possible dimensions over which aggregation can be performed. For example, given grouping sets of B, (D,E), & (ROLLUP(A,C)), it computes the requested aggregates for the following combinations of columns: Group B: { B } - unique B values Group (D,E): { DE} - unique D E pairs Group ROLLUP(A,C): {A C } - unique A C pairs {A } - unique A values { } - all values The grouping sets operation is an aggregate function that can be invoked natively in the options map of the /aggregate/groupby endpoint.

Grouping Sets

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Has Permission

Mon, 01 Jan 0001 00:00:00 +0000

Checks if the specified user has the specified permission on the specified object. Input Parameter Description Name Type Description principal string Name of the user for which the permission is being checked. Must be an existing user. If blank, will use the current user. The default value is ''. object string Name of object to check for the requested permission. It is recommended to use a fully-qualified name when possible.

Has Permission

Mon, 01 Jan 0001 00:00:00 +0000

Has Proc

Mon, 01 Jan 0001 00:00:00 +0000

Checks the existence of a proc with the given name. Input Parameter Description Name Type Description proc_name string Name of the proc to check for existence. options map of string to strings Optional parameters. The default value is an empty map ( {} ). Output Parameter Description Name Type Description proc_name string Value of input parameter proc_name proc_exists boolean Indicates whether the proc exists or not. Possible values are:

Has Proc

Mon, 01 Jan 0001 00:00:00 +0000

Has Role

Mon, 01 Jan 0001 00:00:00 +0000

Checks if the specified user has the specified role. Input Parameter Description Name Type Description principal string Name of the user for which role membersih is being checked. Must be an existing user. If blank, will use the current user. The default value is ''. role string Name of role to check for membership. options map of string to strings Optional parameters. The default value is an empty map ( {} ).

Has Role

Mon, 01 Jan 0001 00:00:00 +0000

Has Schema

Mon, 01 Jan 0001 00:00:00 +0000

Checks for the existence of a schema with the given name. Input Parameter Description Name Type Description schema_name string Name of the schema to check for existence, in root, using standard name resolution rules. options map of string to strings Optional parameters. The default value is an empty map ( {} ). Output Parameter Description Name Type Description schema_name string Value of input parameter schema_name schema_exists boolean Indicates whether the schema exists or not.

Has Schema

Mon, 01 Jan 0001 00:00:00 +0000

Has Table

Mon, 01 Jan 0001 00:00:00 +0000

Checks for the existence of a table with the given name. Input Parameter Description Name Type Description table_name string Name of the table to check for existence, in [schema_name.]table_name format, using standard name resolution rules. options map of string to strings Optional parameters. The default value is an empty map ( {} ). Output Parameter Description Name Type Description table_name string Value of input parameter table_name table_exists boolean Indicates whether the table exists or not.

Has Table

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Has Type

Mon, 01 Jan 0001 00:00:00 +0000

Check for the existence of a type. Input Parameter Description Name Type Description type_id string Id of the type returned in response to Create Type request. options map of string to strings Optional parameters. The default value is an empty map ( {} ). Output Parameter Description Name Type Description type_id string Value of input parameter type_id. type_exists boolean Indicates whether the type exists or not. Possible values are:

Has Type

Mon, 01 Jan 0001 00:00:00 +0000

HDFS Import

Mon, 01 Jan 0001 00:00:00 +0000

Import Overview Setup Source Destination Configure Summary Using the HDFS Import wizard, files located in HDFS can be imported into Kinetica. To import a file from HDFS into Kinetica, click on the HDFS panel on the Import landing page in Workbench. The HDFS Import wizard appears in the right-hand pane. HDFS Import Wizard The wizard has two tabs: Import - contains the 5-step process for importing files from HDFS History - lists all of your previous HDFS import attempts Import Overview When importing, the following five steps will need to be completed:

HDFS Import

Mon, 01 Jan 0001 00:00:00 +0000

High Availability Architecture

Mon, 01 Jan 0001 00:00:00 +0000

Failover Modes Failure and Recovery High Availability Processing Operation Handling Synchronous Operations Asynchronous Operations Queries Eventual Consistency Data Synchronization Recovery The Kinetica HA eliminates the single point of failure in a standard Kinetica cluster and provides recovery from failure. It is implemented within the cluster to utilize multiple replicas of data and provides an eventually consistent data store, by default. Through modification of the configuration, immediate consistency can also be achieved, though at a performance cost.

High Availability Configuration & Management

Mon, 01 Jan 0001 00:00:00 +0000

Pre-requisites Configuration Enable HA Config HA APIs Connectors External Data Management Pre-requisites An HA installation requires the following components: Two or more clusters with matching Kinetica installations managed by KAgent Note If the clusters are not managed, KAgent should be installed and then the clusters should be added to it. Two nodes (across the clusters) have RabbitMQ installed etcd The KAgent UI Configuration Enable HA HA is enabled on a ring using the KAgent UI.

Home

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Home serves as the landing page for Workbench. Workbench Home Page This landing page can be reached at any time by clicking on the Home menu item at the top. This will open several options in the right-hand pane, including: Getting Started - links to various tutorials native API reference, and native API downloads Import - links to the import & external table wizards, as well as to the various data source specific import wizards Connect - sample code blocks for connecting to Kinetica with the various native API languages and JDBC Resources - links to video tutorials

Home

Mon, 01 Jan 0001 00:00:00 +0000

Host Manager

Mon, 01 Jan 0001 00:00:00 +0000

Host Manager is a supervisor process that manages several processes that are part of each Kinetica install. The following processes are managed by Host Manager and will be restarted if they fail unexpectedly: Database Services Text Search ODBC Server HTTPD Note Read more about managing the Host Manager process on Managing Kinetica Services. The Host Manager also serves the following endpoints: /admin/add/host /admin/alter/host /admin/remove/host /admin/show/alerts /admin/switchover

Host Manager

Mon, 01 Jan 0001 00:00:00 +0000

HTTPD "Data" Configuration

Mon, 01 Jan 0001 00:00:00 +0000

Navigate to /opt/gpudb/httpd/conf/data.conf and uncomment the following settings, ensuring you replace the SSLCertificateFile and SSLCertificateKeyFile setting values with the proper file paths. Read the Apache HTTPD SSL Docs for more information SSLEngine On ... SSLCertificateFile </path/to/cert> SSLCertificateKeyFile </path/to/key> SSLProxyEngine On RequestHeader set X-Forwarded-Proto "https" Important The following settings are optional but provide greater security. Depending on what version of OpenSSL is installed on the system, the TLS version should be updated.

HTTPD "NoAuth" Configuration

Mon, 01 Jan 0001 00:00:00 +0000

Navigate to /opt/gpudb/httpd/conf/noauth.conf and uncomment the following settings, ensuring you replace the SSLCertificateFile and SSLCertificateKeyFile setting values with the proper file paths. Read the Apache HTTPD SSL Docs for more information SSLEngine On ... SSLCertificateFile </path/to/cert> SSLCertificateKeyFile </path/to/key> SSLProxyEngine On RequestHeader set X-Forwarded-Proto "https" Important The following settings are optional but provide greater security. Depending on what version of OpenSSL is installed on the system, the TLS version should be updated.

Indexes

Mon, 01 Jan 0001 00:00:00 +0000

An index is used to improve the performance of data access within the system. There are several types of indexes: Primary Key Index Relational Index Column Index Chunk Skip Index Geospatial Index Primary Key Index A primary key index is created by default when a table is created with a primary key specified. It will match the primary key in nature, in that it will be a single-column index if the primary key is on a single column and a multi-column composite index if the primary key is a composite primary key.

Indexes

Mon, 01 Jan 0001 00:00:00 +0000

Info (Instance Information)

Mon, 01 Jan 0001 00:00:00 +0000

Click Info in the top navigation menu to access several methods for monitoring & checking the health of the system. Status Diagnostics Info Status Status will display the main set of Kinetica metrics. Diagnostics Diagnostics will perform several tests on the Kinetica server/cluster to determine whether or not the system is functioning properly. The result should look similar to this: Info Info will show you configuration and version information about your instance of Kinetica.

Insert JSON Records

Mon, 01 Jan 0001 00:00:00 +0000

Overview Usage Examples Responses Overview Kinetica provides a direct JSON ingest service to allow raw JSON to be translated into records and inserted into the database. If the target table exists, inserted records will be appended to it. If the target table does not exist, it will be created automatically, with type inferencing used to determine column types & sizes, before inserting data. Tip To ensure a particular column ordering with a created target table, use the columns_to_load parameter, specifying all columns in the desired order.

Insert JSON Records

Mon, 01 Jan 0001 00:00:00 +0000

Insert Records

Mon, 01 Jan 0001 00:00:00 +0000

Adds multiple records to the specified table. The operation is synchronous, meaning that a response will not be returned until all the records are fully inserted and available. The response payload provides the counts of the number of records actually inserted and/or updated, and can provide the unique identifier of each added record. The input parameter options parameter can be used to customize this function's behavior. The update_on_existing_pk option specifies the record collision policy for inserting into a table with a primary key, but is ignored if no primary key exists.

Insert Records

Mon, 01 Jan 0001 00:00:00 +0000

Insert Records from external database

Mon, 01 Jan 0001 00:00:00 +0000

Computes remote query result and inserts the result data into a new or existing table Input Parameter Description Name Type Description table_name string Name of the table into which the data will be inserted, in [schema_name.]table_name format, using standard name resolution rules. If the table does not exist, the table will be created using either an existing type_id or the type inferred from the remote query, and the new table name will have to meet standard table naming criteria.

Insert Records from external database

Mon, 01 Jan 0001 00:00:00 +0000

Insert Records from File(s)

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Reads from one or more files and inserts the data into a new or existing table. The source data can be located either in KiFS; on the cluster, accessible to the database; or remotely, accessible via a pre-defined external data source. For delimited text files, there are two loading schemes: positional and name-based. The name-based loading scheme is enabled when the file has a header present and text_has_header is set to true.

Insert Records from File(s)

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Insert Records from Payload

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Reads from the given text-based or binary payload and inserts the data into a new or existing table. The table will be created if it doesn't already exist. Returns once all records are processed. Input Parameter Description Name Type Description table_name string Name of the table into which the data will be inserted, in [schema_name.]table_name format, using standard name resolution rules. If the table does not exist, the table will be created using either an existing type_id or the type inferred from the payload, and the new table name will have to meet standard table naming criteria.

Insert Records from Payload

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Insert Records Random

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Generates a specified number of random records and adds them to the given table. There is an optional parameter that allows the user to customize the ranges of the column values. It also allows the user to specify linear profiles for some or all columns in which case linear values are generated rather than random ones. Only individual tables are supported for this operation. This operation is synchronous, meaning that a response will not be returned until all random records are fully available.

Insert Records Random

Mon, 01 Jan 0001 00:00:00 +0000

Insert Records to table in external database

Mon, 01 Jan 0001 00:00:00 +0000

Exports records from source table to the specified target table in an external database Input Parameter Description Name Type Description table_name string Name of the table from which the data will be exported to remote database, in [schema_name.]table_name format, using standard name resolution rules. remote_query string Parameterized insert query to export gpudb table data into remote database. The default value is ''. options map of string to strings Optional parameters.

Insert Records to table in external database

Mon, 01 Jan 0001 00:00:00 +0000

Insert Symbol

Mon, 01 Jan 0001 00:00:00 +0000

Adds a symbol or icon (i.e. an image) to represent data points when data is rendered visually. Users must provide the symbol identifier (string), a format (currently supported: 'svg' and 'svg_path'), the data for the symbol, and any additional optional parameter (e.g. color). To have a symbol used for rendering create a table with a string column named 'SYMBOLCODE' (along with 'x' or 'y' for example). Then when the table is rendered (via WMS) if the 'dosymbology' parameter is 'true' then the value of the 'SYMBOLCODE' column is used to pick the symbol displayed for each point.

Insert Symbol

Mon, 01 Jan 0001 00:00:00 +0000

Install Nvidia Drivers on Debian/Ubuntu

Mon, 01 Jan 0001 00:00:00 +0000

This section will provide instructions on installing Nvidia drivers in a Debian/Ubuntu environment, if the target servers have Nvidia GPUs. Ensure the GPUs are Installed Ensure that the lspci command is installed (which lists the PCI devices connected to the server): sudo apt-get -y install pciutils Perform a quick check to determine what Nvidia cards have been installed: lspci | grep VGA The output of the lspci command above should be something similar to:

Install Nvidia Drivers on RHEL

Mon, 01 Jan 0001 00:00:00 +0000

This section will provide instructions on installing Nvidia drivers in an RHEL environment, if the target servers have Nvidia GPUs. Disable Secure Boot and SELinux Note Disabling Secure Boot and SELinux may not be necessary for every setup. The Nvidia drivers are installed by compiling and installing kernel modules. If they are not signed by a trusted source, then you will not be able to use secure boot. Consequently, you will likely want to disable secure boot in the BIOS of your server.

Installation Options

Mon, 01 Jan 0001 00:00:00 +0000

There are two methods for installing Kinetica on-premises: KAgent -- The preferred method for installing Kinetica. KAgent automates the installation and configuration of Kinetica, Active Analytics Workbench (AAW) and Kubernetes, rings (High Availability), and more. Manual -- Kinetica can be installed manually via command line using common Linux-based package managers. Note Kinetica can be installed on pre-provisioned instances in AWS, Azure, or GCP via KAgent. For offerings provisioned within cloud environments directly, see Cloud-Ready.

Integrate

Mon, 01 Jan 0001 00:00:00 +0000

Topics APIs C++ API C# API Java API JavaScript API Node.js API Python API REST API Connecting via API Compatibility Matrix Connectors SQL Connectors Geospatial Connector Data Connecctors Compatibility Matrix Downloads API Downloads UDF API Downloads Connector Downloads User-Defined Function Implementation UDF Tutorials UDF Prerequisites UDF Deveopment Performance Optimization Distributed Ingest Distributed Key Lookup Sharding Geospatial Kinetica Tools KiFS KiSQL

Integrate

Mon, 01 Jan 0001 00:00:00 +0000

Intersect

Mon, 01 Jan 0001 00:00:00 +0000

An intersect is a representation of all rows that appear in both of a pair of specified data sets (tables or views). See INTERSECT for the SQL version of this operation. An intersect is performed via the /create/union endpoint using the intersect or intersect_all mode: Intersect -- all unique rows that exist in both specified data sets Intersect All -- all rows (including duplicates) that exist in both specified data sets You can only perform an intersect two data sets, and the columns between the two must have similar data types.

Intersect

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Iteration

Mon, 01 Jan 0001 00:00:00 +0000

Overview Examples Geospatial Point Extraction - Variable Iteration (in SQL) Line Segment Extraction - Variable Iteration (in Python) Endpoint Extraction - Fixed Iteration (in SQL) Non-Geospatial Letter Counting - Variable Iteration (in SQL) Data Duplication - Fixed Iteration (in Python) Limitations Overview Kinetica supports arbitrary iteration over records within a data set for the purpose of generating 0 to N result records per iterated record. The primary use case for this is in returning sub-elements of a given geospatial column as individual records; e.

Iteration

Mon, 01 Jan 0001 00:00:00 +0000

Java

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Java

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Javascript

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Javascript

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JDBC Data Source Import

Mon, 01 Jan 0001 00:00:00 +0000

Import Overview Setup Source Destination Configure Summary Using the JDBC Data Source Import wizard, tables located in another database can be imported into Kinetica via JDBC. To import a table from a remote database into Kinetica, click on any of the data source panels listed under JDBC Data Sources on the Import landing page in Workbench. The JDBC Data Source Import wizard appears in the right-hand pane, noting the specific source selected.

JDBC Data Source Import

Mon, 01 Jan 0001 00:00:00 +0000

JDBC Import

Mon, 01 Jan 0001 00:00:00 +0000

Import Overview Setup Source Destination Configure Summary Using the JDBC Import wizard, tables located in another database can be imported into Kinetica via JDBC. To import a table from a remote database into Kinetica, click on the Generic JDBC panel on the Import landing page in Workbench. The JDBC Import wizard appears in the right-hand pane. JDBC Import Wizard The wizard has two tabs: Import - contains the 5-step process for importing files from remote databases using JDBC History - lists all of your previous JDBC import attempts Import Overview When importing, the following five steps will need to be completed:

JDBC Import

Mon, 01 Jan 0001 00:00:00 +0000

Job Manager

Mon, 01 Jan 0001 00:00:00 +0000

The Job Manager maintains request ordering across the nodes in your Kinetica cluster at the cost of some performance. All read requests (/show/table, /get/records, etc.) are processed simultaneously. When a write request (/insert/records, /delete/records, etc.) is made, all subsequent read and write requests are blocked until the current write request is finished. If Job Manager is disabled, all inbound requests are broadcasted to all worker nodes and can be executed in any order.

Job Manager

Mon, 01 Jan 0001 00:00:00 +0000

The Job Manager maintains request ordering across the nodes in your Kinetica cluster at the cost of some performance. All read requests (/show/table, /get/records, etc.) are processed simultaneously. When a write request (/insert/records, /delete/records, etc.) is made, all subsequent read and write requests are blocked until the current write request is finished. Because read requests are processed simultaneously, read jobs can only be cancelled while a preceding write request is being processed, which is also referred to as a checkpoint.

Jobs

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Click Jobs in the top navigation menu to access the Job Manager interface. Important The Jobs section is only available to users with the System Admin permission. Running Recent Running The Running page shows a list of currently executing jobs. Jobs can be cancelled by selecting them and then clicking Cancel Jobs, though most jobs are processed quickly enough to be finished by the time they appear in the job listing.

Jobs

Mon, 01 Jan 0001 00:00:00 +0000

The Jobs interface is situated in the right-hand pane of Kinetica's Workbench administration application. It can be used to view the status of the user-initiated and system-level jobs running within the database. Jobs Page To access the Jobs page, in Workbench, click the Jobs menu item. This will open the list of running jobs in the right-hand pane. Additionally, there are several action buttons: Cancel Selected - stop any selected jobs from running - refresh the displayed list of jobs Three tabs allow separate viewing of the different job types:

Jobs

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Joins

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Join Execution Types Native Joins SQL Joins Join Distribution Types Node-Local Joins Distributed Joins Equality-Based Join Rules Inequality-Based Join Rules Creating a Join View Examples Inner Join Outer Join Operating on a Join View Examples SQL Conversion Example Performance Optimization Limitations & Cautions Memory Implications Operations on Underlying Tables Kinetica supports the SQL concept of joining data sets, via join views, connecting related records between two or more tables.

Joins

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Kafka Stream Import

Mon, 01 Jan 0001 00:00:00 +0000

Import Overview Setup Source Destination Configure Summary Using the Kafka Stream Import wizard, data from a Kafka topic can be streamed into Kinetica. To stream data from Kafka into Kinetica, click on the Kafka Stream panel on the Import landing page in Workbench. The Kafka Stream Import wizard appears in the right-hand pane. Kafka Stream Import Wizard The wizard has two tabs: Import - contains the 5-step process for streaming data from Kafka History - lists all of your previous Kafka stream attempts Import Overview When importing, the following five steps will need to be completed:

Kafka Stream Import

Mon, 01 Jan 0001 00:00:00 +0000

KAgent

Mon, 01 Jan 0001 00:00:00 +0000

KAgent is a multi-faceted administration, installation, and configuration management tool. It provides a centralized way to perform a consistent install across an existing or yet-to-be-cloud-provisioned cluster of computers. KAgent can also assist in automating tasks such as provisioning cloud hardware, configuring cluster security, adding and removing nodes, data backup and restoration, monitoring cluster health, managing and configuring cluster high availability. It has both a graphical (web) interface as well as a command line interface.

KAgent

Mon, 01 Jan 0001 00:00:00 +0000

KAgent Installation

KAgent can be deployed as a RHEL or Debian/Ubuntu installation package on any server inside or outside the cluster. After copying the KAgent package to the target server, deploy it using the standard procedures for a local package:

On RHEL:

sudo yum install ./kagent-<version>.<architecture>.rpm

On Debian/Ubuntu:

sudo apt install ./kagent-<version>.<architecture>.deb

This installs the package to the directory /opt/gpudb/kagent and registers and starts the kagent_ui service. KAgent will open port 8081 on the local firewall (if enabled).

Note

If Kinetica is to be installed via KAgent, but managed via command line, the etcd configuration management service will need to be managed separately from the database & system management processes. See Managing Kinetica Services for details.

KiFS API Support

Mon, 01 Jan 0001 00:00:00 +0000

API Initialization Directories Creating Directories Showing Directories Deleting Directories Files Uploading Files Listing Files Downloading Files Deleting Files KiFS Endpoints KiFS, while able to be managed in all native APIs, has enhanced support in the Java API. API Initialization When using KiFS via the Java API, the handler class must be initialized. The examples in the following sections make use of this interface and assume these steps have been taken.

KiFS API Support

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Kill Proc

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Kills a running proc instance. Input Parameter Description Name Type Description run_id string The run ID of a running proc instance. If a proc with a matching run ID is not found or the proc instance has already completed, no procs will be killed. If not specified, all running proc instances will be killed. The default value is ''. options map of string to strings Optional parameters. The default value is an empty map ( {} ).

Kill Proc

Mon, 01 Jan 0001 00:00:00 +0000

Kinetica Blackbox Software Development Kit (SDK) Guide

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The Kinetica Blackbox SDK assists users in creating blackbox models to wrap existing code/functionality and make it deployable within the Kinetica system. The Active Analytics Workbench (AAW) currently can only import blackbox models that have been containerized and implement the BlackBox SDK. Users provide the Python module scripts, modify some SDK files, and the SDK will build a Docker Container from the files and publish it to a given Docker Registry (private or public).

Kinetica Components Configuration

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Reveal Navigate to /opt/gpudb/connectors/reveal/etc/default.json and update the url setting: "gadmin": { "url": "https://localhost:8443/gadmin" }, GAdmin Navigate to the /opt/gpudb/tomcat/webapps/gadmin/js/settings.js file and update the REVEAL_PORT variable to the secured Reveal port (default 8444): var REVEAL_PORT = '8444'; Navigate to the /opt/gpudb/tomcat/webapps/gadmin/WEB-INF/classes/gaia.properties file and update the following settings to https, ensuring the host is correct for your setup gpudb_ext_url = https://<hostname>:8082/gpudb-0 ... gpudb_ext_hm_url = https://<hostname>:8082/gpudb-host-manager In the /opt/gpudb/tomcat/conf/catalina.properties file at the bottom:

Kinetica File System (KiFS)

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The Kinetica File System (KiFS) is a file system interface that's packaged with Kinetica. It provides a repository for users to store and make use of files within the database. KiFS can be leveraged by several Kinetica features: UDFs (in SQL) External tables (in SQL) /insert/records/fromfiles API calls (SQL LOAD INTO) KiFS files can be referenced with the following URI: kifs://<kifs directory><kifs file> For example, the following URI can be broken down into three components:

Kinetica File System (KiFS)

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Kinetica FileSystem Import

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Import Overview Setup Source Destination Configure Summary Using the Kinetica FileSystem (KiFS) Import wizard, files staged in KiFS can be imported into Kinetica. To import a file from KiFS into Kinetica, click on the Kinetica FileSystem panel on the Import landing page in Workbench. The Kinetica FileSystem Import wizard appears in the right-hand pane. Kinetica FileSystem Import Wizard The wizard has two tabs: Import - contains the 5-step process for importing files from KiFS History - lists all of your previous KiFS import attempts Import Overview When importing, the following five steps will need to be completed:

Kinetica FileSystem Import

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Kinetica Geospatial Visualization for Tableau

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Kinetica offers a geospatial visualization extension for Tableau that allows users to visualize maps from Kinetica-hosted datasets. There are four integral parts to this extension: The manifest file, KineticaTableauMapExt.trex A Tableau instance (Tableau Desktop, Tableau Online, or Tableau Server are all applicable) A Kinetica instance An extension server that connects the Tableau extension to Kinetica This document will walk through installation and configuration of the extension within your Tableau instance.

Kinetica Geospatial Visualization for Tableau

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Kinetica Import

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Import Overview Setup Source Destination Configure Summary Using the Kinetica Import wizard, tables located in another Kinetica cluster can be imported into Kinetica. To import a table from a remote Kinetica into a local one, click on the Kinetica panel on the Import landing page in Workbench. The Kinetica Import wizard appears in the right-hand pane. Kinetica Import Wizard The wizard has two tabs: Import - contains the 5-step process for importing files from Kinetica History - lists all of your previous Kinetica import attempts Import Overview When importing, the following five steps will need to be completed:

Kinetica Import

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Kinetica Installation with KAgent

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Kinetica installation and configuration instructions using KAgent for On-Premise hardware. Note Kinetica can be installed on pre-provisioned instances in AWS, Azure, or GCP via KAgent. For offerings provisioned within cloud environments directly, see Cloud-Ready. System Requirements Certified OS List Minimum Hardware Requirements GPU Driver Matrix Cards Active Directory KAgent Installation Kinetica Installation KAgent UI Cluster Deployment Security Nodes Credentials Installation Validation Curl Test API Test GAdmin Status Test Ingest/Read Test Core Utilities Environment Configuration and Tools Helper Scripts Logging Additional Configuration Uninstallation System Requirements Operating system, hardware, and network requirements to run Kinetica.

Kinetica Kickbox.js Mapbox GL

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Library Overview Kinetica Kickbox.js is a client-side code-accelerator library aimed at getting you up and running with Kinetica and Mapbox GL as quickly as possible. Purpose While Mapbox is fully interoperable with Kinetica natively, the workflow for displaying Kinetica's WMS layers can be tricky to implement without knowing the best practices regarding their integration. Furthermore, there are common patterns that begin to emerge and this library aims to reduce the amount of code required to simply connect Kinetica's WMS output to Mapbox.

Kinetica Kickbox.js Mapbox GL

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Kinetica Reader/Writer for FME

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Overview This Kinetica reader and writer plug-in enables FME to read attribute data from Kinetica and write attribute data to Kinetica. General geometric data can be stored as WKT in a standard string field and geometric points can be stored as a pair of float fields. While there are no specific geometric field types, Kinetica can render WKT and coordinates as WMS maps and have functions which operate on them.

Kinetica Reader/Writer for FME

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Kinetica Spark Guide

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Spark via JDBC Spark Egress Spark Ingest Spark Logging Mapping Spark to Kinetica The following guide provides step by step instructions to get started using Spark with Kinetica. Spark via JDBC SQL can be issued against Kinetica through the Spark JDBC interface. This not only allows for data ingest/egress, but provides access to native Kinetica functions in queries, including geospatial operations. See Connecting via JDBC for obtaining the JDBC driver.

Kinetica Spark Guide

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Kinetica SQL (KiSQL)

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KiSQL allows SQL queries to be performed against the data in Kinetica from the command line. GitHub has the latest release of KiSQL for download. KiSQL exposes the complete Kinetica SQL interface, as given in the SQL section, including: Ingestion of local file data into tables (INSERT INTO ... SELECT ... FROM FILE) Uploading of local files into the Kinetica File System (KiFS) for later ingestion (UPLOAD FILE) Downloading of Kinetica File System (KiFS) files to local storage (DOWNLOAD FILE) For a graphical SQL interface, see SQL Blocks in Workbench Workbooks.

Kinetica SQL (KiSQL)

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KiSQL allows SQL queries to be performed against the data in Kinetica from the command line. GitHub has the latest release of KiSQL for download. It is also bundled with Kinetica and is located at /opt/gpudb/bin/kisql on default installations. KiSQL exposes the complete Kinetica SQL interface, as given in the SQL section, including: Ingestion of local file data into tables (INSERT INTO ... SELECT ... FROM FILE) Uploading of local files into the Kinetica File System (KiFS) for later ingestion (UPLOAD FILE) Downloading of Kinetica File System (KiFS) files to local storage (DOWNLOAD FILE) For a graphical SQL interface, see GAdmin.

Limitations

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Unlimited-Width Strings Partially Applicable Operations Inapplicable Operations Store-Only Columns Inapplicable Operations Correlated Subqueries Not Yet Supported SQL Kinetica has some limitations for any columns marked as store-only and string columns lacking a charN attribute. Unlimited-Width Strings String columns with no charN attribute are stored in whole on disk and in hashed form in memory. Because the strings are only available for processing as hashes, only equality-based operations can be applied to them.

Limitations

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Load Data from Apache Kafka

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Create Credential Create Data Source Ingest Data Considerations Error Handling Load Specific Columns DateTime Formatting Null Value Handling Avro w/ Schema Registry Loading data from Apache Kafka can be done in three easy steps: Create a credential - holds Kafka account authentication information Create a data source - holds Kafka connection information; uses the credential for authentication Ingest the data - Load data from Kafka; uses the data source to identify the Kafka source Note

Load Data from Apache Kafka

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Load Data from Azure Blob

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Create Credential Create Data Source Ingest Data Considerations Error Handling Load Specific Columns DateTime Formatting Loading data from Azure Blob Storage can be done in three easy steps: Create a credential - holds Azure account authentication information Create a data source - holds Azure Blob Storage connection information; uses the credential for authentication Ingest the data - Load data from Azure; uses the data source to identify the Azure source Create Credential To store the access details for your data source, first create a credential with the CREATE CREDENTIAL command, and reference it in your CREATE DATA SOURCE statement.

Load Data from Azure Blob

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Load Data from CData JDBC Drivers

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Before You Begin Create Data Source Ingest Data Considerations Error Handling Load Specific Columns Loading data from a CData data source can be done in two easy steps: Create a data source: Create a data source that holds the connection information. Ingest the data: Load data from the data source using a remote JDBC query. Kinetica provides pre-packaged, third-party JDBC drivers, out of the box, that allow you to connect to varied and popular data sources.

Load Data from CData JDBC Drivers

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Load Data from Confluent Kafka

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Create Credential Create Data Source Ingest Data Considerations Error Handling Load Specific Columns DateTime Formatting Null Value Handling Avro w/ Schema Registry Loading data from Confluent Kafka can be done in three easy steps: Create a credential - holds Kafka account authentication information Create a data source - holds Kafka connection information; uses the credential for authentication Ingest the data - Load data from Kafka; uses the data source to identify the Kafka source Note

Load Data from Confluent Kafka

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Create Credential Create Data Source Ingest Data Considerations Error Handling Load Specific Columns DateTime Formatting Null Value Handling Avro w/ Schema Registry Loading data from Confluent Kafka can be done in three easy steps: Create a credential - holds Kafka account authentication information Create a data source - holds Kafka connection information; uses the credential for authentication Ingest the data - Load data from Kafka; uses the data source to identify the Kafka source Note

Load Data from GCS

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Create Credential Create Data Source Ingest Data Considerations Error Handling Load Specific Columns DateTime Formatting Loading data from Google Cloud Storage can be done in three easy steps: Create a credential - holds GCS account authentication information Create a data source - holds GCS connection information; uses the credential for authentication Ingest the data - Load data from GCS; uses the data source to identify the GCS source Create Credential To store the access details for your data source, first create a credential with the CREATE CREDENTIAL command, and reference it in your CREATE DATA SOURCE statement.

Load Data from GCS

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Load Data from HDFS

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Create Credential Create Data Source Ingest Data Considerations Wildcard Ingest Error Handling Load Specific Columns DateTime Formatting Loading data from HDFS can be done in three easy steps: Create a credential - holds HDFS account authentication information Create a data source - holds HDFS connection information; uses the credential for authentication Ingest the data - Load data from HDFS; uses the data source to identify the HDFS source Create Credential To store the access details for your data source, first create a credential with the CREATE CREDENTIAL command, and reference it in your CREATE DATA SOURCE statement.

Load Data from HDFS

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Load Data from JDBC

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Before You Begin Upload JDBC Driver Kinetica Workbench KiSQL Create Data Source Ingest Data Considerations Error Handling Loading data from a JDBC data source can be done in three easy steps: Load the JDBC Driver into KiFS: Load the JDBC driver for the specified data source into the Kinetica File System (KiFS). Create a data source: Create a data source that holds JDBC connection information. Ingest the data: Load data from your data source over JDBC using a remote query.

Load Data from JDBC

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Before You Begin Upload JDBC Driver KiSQL Create Data Source Ingest Data Considerations Error Handling Loading data from a JDBC data source can be done in three easy steps: Load the JDBC Driver into KiFS: Load the JDBC driver for the specified data source into the Kinetica File System (KiFS). Create a data source: Create a data source that holds JDBC connection information. Ingest the data: Load data from your data source over JDBC using a remote query.

Load Data from KiFS

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Ingest Data Considerations Error Handling Load Specific Columns DateTime Formatting Unlike other data sources, you do not need to first create a credential and a data source object in Kinetica before ingesting data from KiFS. Ingest Data To initiate the ingest of data into a Kinetica table, use the LOAD INTO command for a one-time batch load. To reference files in KiFS, you can use a URL that looks like this:

Load Data from KiFS

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Load Data from Local File

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Kinetica Workbench KiSQL Considerations Error Handling Load Specific Columns DateTime Formatting To load data from your local computer, you can: Follow the Import Wizard in the Workbench UI to upload your file into the Kinetica File System (KiFS) and load the data in the same workflow. Use the command line from your computer with Kinetica's KiSQL tool that allows you to upload the file to the Kinetica File System (KiFS) and initiate the load into the table with SQL.

Load Data from Local File

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KiSQL Considerations Error Handling Load Specific Columns DateTime Formatting To load data from your local computer, you can: Use the command line from your computer with Kinetica's KiSQL tool that allows you to upload the file to the Kinetica File System (KiFS) and initiate the load into the table with SQL. Or, use a third party SQL tool like DBeaver with Kinetica's JDBC driver and follow the same instructions for KiSQL.

Load Data from S3

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Create Credential Create Data Source Ingest Data Considerations Error Handling Load Specific Columns DateTime Formatting Loading data from Amazon S3 can be done in three easy steps: Create a credential - holds S3 account authentication information Create a data source - holds S3 connection information; uses the credential for authentication Ingest the data - Load data from S3; uses the data source to identify the S3 source Create Credential To store the access details for your data source, first create a credential with the CREATE CREDENTIAL command, and reference it in your CREATE DATA SOURCE statement.

Load Data from S3

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Loading Data

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LOAD INTO Delimited Text Options Delimited Text Option Characters Load Options Table Property Clause Examples File Paths File Formats Table Options Column Options Dry Run Data Sources Change Data Capture INSERT INTO ... SELECT ... FROM FILE Options Option Characters Examples File Paths Options Considerations Kinetica supports loading of data via SQL from a variety of file types and through several mechanisms. There are two primary paths: Loading server-accessible data sets via SQL (or the /execute/sql endpoint call) that either: can be reached by Kinetica via an external data source object have been uploaded to Kinetica via SQL, Workbench, or API Loading client-side files via ODBC/JDBC LOAD INTO Kinetica can load either internal or external data into a table, using a LOAD INTO statement.

Loading Data

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LOAD INTO Delimited Text Options Delimited Text Option Characters Load Options Table Property Clause Examples File Paths File Formats Table Options Column Options Dry Run Data Sources Change Data Capture INSERT INTO ... SELECT ... FROM FILE Options Option Characters Examples File Paths Options Considerations Kinetica supports loading of data via SQL from a variety of file types and through several mechanisms. There are two primary paths: Loading server-accessible data sets via SQL (or the /execute/sql endpoint call) that either: can be reached by Kinetica via an external data source object have been uploaded to Kinetica via SQL or API Loading client-side files via ODBC/JDBC LOAD INTO Kinetica can load either internal or external data into a table, using a LOAD INTO statement.

Lock Table

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Manages global access to a table's data. By default a table has a input parameter lock_type of read_write, indicating all operations are permitted. A user may request a read_only or a write_only lock, after which only read or write operations, respectively, are permitted on the table until the lock is removed. When input parameter lock_type is no_access then no operations are permitted on the table. The lock status can be queried by setting input parameter lock_type to status.

Lock Table

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Logging in AWS

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Kinetica logs and metrics are sent to AWS CloudWatch so that you can monitor Kinetica's health and performance alongside other components of your analytic pipelines. Application Logs To view the logs, click on the link in the applicationLogs key in the CloudFormation stack outputs: In the search box (Filter log streams or try prefix search), type gpudb to search for Kinetica log events: Logs Insights Alternatively, you can use CloudWatch Logs Insights to craft specific log queries.

Machine Learning (ML)

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CREATE CONTAINER REGISTRY DROP CONTAINER REGISTRY SHOW CONTAINER REGISTRY IMPORT MODEL EVALUATE_MODEL ALTER MODEL REFRESH MODEL DROP MODEL SHOW MODEL DESCRIBE MODEL Kinetica provides support for Machine Learning (ML) container registry & model creation and management in SQL. A Docker registry serves as a container for ML models, while an ML model represents a function from which an inference can be computed. Note For statistical analysis functions that don't require a model, see ML Functions.

Machine Learning (ML)

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Machine Learning Concepts

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Kinetica provides a machine learning (ML) capability for simplifying and accelerating data science in a scalable fashion. With ML, users can ingest data, train models, make inferences (answers/output from models), and even audit models. ML leverages Kubernetes to deploy, train, and test models. Note To work with models in SQL, see Machine Learning (ML). For statistical analysis functions that don't require a model, see ML Functions. Concepts Registries Data Models Deployments Audits Concepts The ML workflow is defined by five key concepts:

Manage

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The Manage page allows users to install new clusters, add existing clusters, review KAgent logs and jobs, manage cluster high availability rings, and more. The Manage page has two main views depending on whether there is a cluster in KAgent or not. If no clusters have been added to KAgent yet, the Welcome page will appear by default allowing you to quickly jump into adding a cluster. If there are clusters in KAgent, the Clusters page will appear by default.

Manage > Cluster

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Title Controls Overview Upgrade Snapshots The cluster management interface is situated in the right-hand pane of Kinetica's Workbench administration application. It consists of three main features: Overview Upgrade Snapshots To access the cluster management page, in Workbench, select Cluster from the Manage menu item drop-down. Title Controls At the top of the page is the name of the Kinetica cluster instance and several action buttons: || Suspend - stops the cluster, but leaves Workbench running, so that the cluster can be managed offline > Resume - starts a suspended cluster Refresh icon - refreshes the displayed page's contents Overview The Cluster Overview page lists several categories of helpful information for managing the cluster.

Manage > Users & Roles

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Users Creating or Modifying a User User Attributes User Permissions Roles Creating or Modifying a Role Role Attributes Role Permissions The user & role interface is situated in the right-hand pane of Kinetica's Workbench administration application. It can be used to manage users, roles, and privileges to all objects in the database. To access the user & role management page, in Workbench, select Users & Roles from the Manage menu item drop-down.

Managing Kinetica in Workbench

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Suspending & Resuming the Cluster Auto Suspend Feature Backing-up & Restoring the Cluster Managing Users & Roles Upgrading Kinetica Changing the Administrator Password Workbench not only provides a means for accessing data within Kinetica, but can also manage the database itself. Suspending & Resuming the Cluster You can suspend and resume Kinetica through the Workbench. Suspending the cluster will allow you to reduce compute costs by releasing compute nodes that are not used.

Managing Kinetica Services

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Managing Database Services Start Database Services Database Services Startup Stop Database Services GUI Stop Command-Line Stop Managing System Processes Start System Management Processes Stop System Management Processes Managing All Services Start All Processes Stop All Processes Managing Individual Components System Status Checks Processes GAdmin API Statuses System Node Rank Typical maintenance of the system may require starting & stopping of Kinetica services. Managing Database Services Managing System Processes Managing All Services Note

Manual Kinetica Installation

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Kinetica manual installation and configuration instructions. Note Kinetica can be installed manually on pre-provisioned instances in AWS, Azure, or GCP. For offerings provisioned within cloud environments directly, see Cloud-Ready. System Requirements Certified OS List Minimum Hardware Requirements GPU Driver Matrix Cards Cluster Preparation Networking Configuration Default Ports Port Usage Scenarios Firewall Settings System Settings Transparent Huge Pages Active Directory Nvidia Drivers Installation Configuration Initialization Visual Initialization Console Initialization Passwordless SSH Validation Curl Test API Test GAdmin Status Test Ingest/Read Test Core Utilities Environment Configuration and Tools Helper Scripts Logging Uninstallation System Requirements Operating system, hardware, and network requirements to run Kinetica.

Match Graph

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Matches a directed route implied by a given set of latitude/longitude points to an existing underlying road network graph using a given solution type. IMPORTANT: It's highly recommended that you review the Network Graphs & Solvers concepts documentation, the Graph REST Tutorial, and/or some /match/graph examples before using this endpoint. Input Parameter Description Name Type Description graph_name string Name of the underlying geospatial graph resource to match to using input parameter sample_points.

Match Graph

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Materialized Views

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Refresh Manual Refresh Manual Mode On Change Mode On Query Mode Periodic Mode Creating a Materialized View Examples Limitations and Cautions Kinetica supports the concept of a materialized view, which is a greater-performant query across one or more tables. For details on interfacing with materialized views from SQL, see CREATE MATERIALIZED VIEW. A materialized view name must adhere to the standard naming criteria. Each materialized view exists within a schema and follows the standard name resolution rules for tables.

Materialized Views

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Memory-Only Tables

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Memory-only tables are not persisted by default like a regular table. You can add, modify, or delete records in a memory-only table. A memory-only table name must adhere to the standard naming criteria. Each memory-only table exists within a schema and follows the standard name resolution rules for persisted tables. The following scenarios/endpoints will create a memory-only table (unless persistence is specified): Using the /aggregate/groupby, /aggregate/unique, or /aggregate/unpivot endpoints with the result_table option specified Projection -- created from /create/projection Union (also includes intersect and except operations) -- created from /create/union Creating a table using /create/table with the is_result_table option set to true Considerations Ingestion speed is better than persisted tables, as there are no disk writes.

Memory-Only Tables

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Merge Records

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Create a new empty result table (specified by input parameter table_name), and insert all records from source tables (specified by input parameter source_table_names) based on the field mapping information (specified by input parameter field_maps). For merge records details and examples, see Merge Records. For limitations, see Merge Records Limitations and Cautions. The field map (specified by input parameter field_maps) holds the user-specified maps of target table column names to source table columns.

Merge Records

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Merge Records Tables

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Merging Records is similar to a union in that multiple tables or views are merged together to create a new merge records table. Since a table is created by the merge records operation, records can be added, modified, or deleted. If you want to duplicate the records in a table or view, merging a table or view with itself is also possible, but the data set will need to be listed twice in the source_table_names parameter.

Merge Records Tables

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Migrating To Kinetica 7.1

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While any version of Kinetica can be upgraded to the latest version using KAgent, there are several aspects of upgrading that should be considered before doing so, as well as a number of steps that should be taken after installing Kinetica 7.1. Database Clients Database Connectors Database Drivers Core Schemas/Collections Protection SQL Support Schemas/Collections AAW UDF Database Clients The native API is not backward compatible with prior releases; any clients that make use of these interfaces need to be updated after installation.

Models + Analytics

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A model is a mathematical or programmatical representation of a real-world process. Point to + Add Model then click one of the options to begin the model setup/import process. New Blackbox -- create a new Blackbox model Type into Filter to filter down the models Click to display any archived models. Click to refresh the table Click to export the table's values as JSON or CSV Click an existing model to display additional actions.

Modify Graph

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Update an existing graph network using given nodes, edges, weights, restrictions, and options. IMPORTANT: It's highly recommended that you review the Network Graphs & Solvers concepts documentation, and Graph REST Tutorial before using this endpoint. Input Parameter Description Name Type Description graph_name string Name of the graph resource to modify. nodes array of strings Nodes with which to update existing input parameter nodes in graph specified by input parameter graph_name.

Modify Graph

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Monitoring and Alerting

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Kinetica's monitoring and alerting features are available via the KAgent application. Detailed cluster, usage, and query statistics and metrics are available to assist administrators in monitoring their Kinetica environment. Administrators can configure alerts that are triggered when specific performance metric thresholds are exceeded (Metric Alerts) or by specific system events (Event Alerts). Administrators can then choose who should be notified when those alerts fire by configuring Recipients and Delivery Channels for alert delivery.

Multi-Head Egress

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Multi-Head Egress (Distributed Key Lookup) is a mechanism that allows sharded data to be retrieved directly from cluster nodes, bypassing the overhead of pulling the data through the head node from the cluster nodes. This greatly increases the speed of retrieval by spreading the network traffic across multiple nodes. Operationally, the egress mechanism is a lookup of a given shard key value in a given table or view, filtering out any records that don't match an optional expression.

Multi-Head Egress

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Multi-Head Ingest

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Multi-Head Ingest (Distributed Ingest) is a mechanism that allows sharded data to be ingested directly into cluster nodes, bypassing the overhead of pushing the data through the head node to the cluster nodes. Operationally, the ingest mechanism calculates the target shard of each record to insert, and sends batches of would-be co-located records to their respective target nodes. To fully utilize multi-head ingest, the ingestion process should use a multi-node parallel processing framework, such as MapReduce, Storm, or Spark.

Multi-Head Ingest

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Multi-Head Use Case

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A common, highly-performant use case for Kinetica is multi-head ingest into a fact table and multi-head egress from a materialized view created from that fact table, periodically refreshed at some interval. The example given below can be downloaded & run to demonstrate the use case on a local Kinetica instance. This guide will demonstrate a simple use case, implemented in Java & SQL, consisting of four entities: Multi-Head Ingest Client Fact Table (ingestion target) Materialized View from Fact Table (egress source) Multi-Head Egress Client Multi-Head Ingest/Egress

Multi-Head Use Case

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Naming

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Name Resolution Naming Criteria Reserved Words Name Resolution Most database objects (tables, views, etc.) can be addressed using a qualified name, by prefixing the name of the object with the name of its containing schema, separated by a dot; e.g.: 1 <schema name>.<table/view name> For the full list of schema-contained objects, see CREATE SCHEMA. If these objects are referenced without a schema, they will be looked for in the user's default schema, if one has been assigned.

Naming

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Network Graphs

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CREATE GRAPH SOLVE_GRAPH QUERY_GRAPH MATCH_GRAPH ALTER GRAPH DROP GRAPH SHOW GRAPH DESCRIBE GRAPH Kinetica provides support for graph creation and management in SQL. Graphs represent topological relationships (both geospatial and non-geospatial) via nodes that are connected by edges. Graph features accessible via SQL include: CREATE GRAPH SOLVE_GRAPH QUERY_GRAPH MATCH_GRAPH ALTER GRAPH DROP GRAPH SHOW GRAPH DESCRIBE GRAPH CREATE GRAPH Creates a new graph. The nodes and edges of a graph are optionally weighted and/or restricted to aid in calculating various ways to traverse the graph.

Network Graphs

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Network Graphs & Solvers Concepts

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Graphs in Kinetica A Brief Intro Graphs in Kinetica × Kinetica provides a generic and extensible design of networks with the aim of being tailored or used for various real-life applications, such as transportation, utility, social, and geospatial. Networks comprise a graph and a solver. A graph represents topological relationships via nodes that are connected by edges; a solver represents the type of solution appropriate for the issue the graph was made to illustrate.

Network Graphs & Solvers Concepts

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NiFi Connector Developer Manual

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The following guide provides step by step instructions to get started using Kinetica as a data source to read from and write to. Source code for the connector can be found at: <https://github.com/kineticadb/kinetica-connector-nifi> Building the Kinetica NiFi Connector The connector jar can be built with Maven. Download the connector source: $ git clone https://github.com/kineticadb/kinetica-connector-nifi.git $ cd kinetica-connector-nifi If using a version of NiFi other than 1.3.0, update the pom.xml file with the correct version of NiFi in this block:

NiFi Connector Developer Manual

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NodeJS

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NodeJS

Mon, 01 Jan 0001 00:00:00 +0000

Nulls

Mon, 01 Jan 0001 00:00:00 +0000

Setting Nullability SQL REST C++ C# Java JavaScript Node.js Python Using Nulls Examples Aggregates and Nulls Example Using nulls begins with setting nullability of type fields at creation time. Each database API has a language-specific means for assigning nullability when creating a type. Null values and nullability are also supported for SQL. Setting Nullability Setting nullability is possible using three different methods: Workbench Native API (using the /create/type endpoint) SQL The process for specifying nullability varies between the different API languages and SQL; the process for each language is outlined below.

Nulls

Mon, 01 Jan 0001 00:00:00 +0000

Setting Nullability SQL REST C++ C# Java JavaScript Node.js Python Using Nulls Examples Aggregates and Nulls Example Using nulls begins with setting nullability of type fields at creation time. Each database API has a language-specific means for assigning nullability when creating a type. Null values and nullability are also supported for SQL. Setting Nullability Setting nullability is possible using three different methods: GAdmin Native API (using the /create/type endpoint) SQL The process for specifying nullability varies between the different API languages and SQL; the process for each language is outlined below.

Obfuscating Plain-Text Passwords

Mon, 01 Jan 0001 00:00:00 +0000

Overview Utilities Example Overview Some deployments of Kinetica may require that plain-text passwords in configuration files be obfuscated, for security reasons. A method for doing so has been made available via a set of scripts. The encryption key generated for performing the obfuscation will be available to the root and gpudb users to encrypt/decrypt passwords, as necessary. Utilities Three utilities are provided to enable obfuscation of plain-text passwords in configuration files.

ODBC/JDBC Connector Guide

Mon, 01 Jan 0001 00:00:00 +0000

Kinetica provides a SQL interface through its ODBC & JDBC drivers, which run on Linux, Mac, & Windows. For details on the extent of SQL compliance, see the SQL section. Connecting KiSQL JDBC Applications JDBC Clients ODBC Tableau Excel DBeaver Other JDBC Clients ODBC/JDBC Configuration Standard Parameters Server Override Parameters Client Parameters SSL Parameters Connecting KiSQL KiSQL is a Kinetica JDBC-based SQL CLI client that is available on GitHub. Details can be found on the Kinetica SQL (KiSQL) page.

ODBC/JDBC Connector Guide

Mon, 01 Jan 0001 00:00:00 +0000

Kinetica provides a SQL interface through its ODBC & JDBC drivers, which run on Linux, Mac, & Windows. For details on the extent of SQL compliance, see the SQL section. Connecting KiSQL JDBC Applications JDBC Clients ODBC Tableau Excel DBeaver Other JDBC Clients ODBC/JDBC Configuration Standard Parameters Server Override Parameters Client Parameters SSL Parameters Logging Connecting KiSQL KiSQL is a Kinetica JDBC-based SQL CLI client that is available on GitHub.

Pivot

Mon, 01 Jan 0001 00:00:00 +0000

The pivot operation works much the same as the SQL concept: "rotating" and expanding single columns of values into multiple columns (one for each value), creating a wider but shorter table. It is nearly the opposite of the unpivot operation, though it will merge duplicates and drop null values, which unpivot cannot undo. You can perform pivot operations using the pivot and pivot_values parameters in the options map of /aggregate/groupby or via the SQL PIVOT function.

Pivot

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Point Clustering

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Example Visualizing Point Clusters Initializing the Map Adding a Point Cluster Layer Full Code Example A Note About Data Design Example An example of point clustering is available below: Point Cluster Note You will need a current Mapbox API key and some minor modifications will be required in order to run each example. At a minimum, you will need a Kinetica table with latitude/longitude values. Visualizing Point Clusters This example demonstrates the power of Kinetica to aggregate millions of records into granular clusters (thousands as a result) and send them to the browser.

Point Clustering

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Ports

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Default Ports The default ports used for communication with KAgent, Kinetica (and between servers, if operating in a cluster), and various important services follow. The Nodes column will list either Head--that the corresponding port only needs to be opened on the head node, or All--that the corresponding port needs to be opened on the head node & worker nodes. Important While the table below lists KAgent and the graph server as being on the head node, these features could be kept on machines entirely separate from Kinetica if desired.

PostgreSQL Wire Protocol

Mon, 01 Jan 0001 00:00:00 +0000

Kinetica has support for PostgreSQL Wire Protocol connections. PostgreSQL simple query syntax is fully supported, while PostgreSQL extended query syntax is largely supported. Connecting PSQL Psycopg Connecting Point any client able to make use of PostgreSQL Wire Protocol at Kinetica on port 5432 to connect. PSQL PSQL is a PostgreSQL CLI for connecting over PostgreSQL Wire Protocol. Connect 1 psql -h <aws.cluster.id>.cloud.kinetica.com -U <username> SELECT 1 => SELECT * FROM example.

PostgreSQL Wire Protocol

Mon, 01 Jan 0001 00:00:00 +0000

Kinetica has support for PostgreSQL Wire Protocol connections. PostgreSQL simple query syntax is fully supported, while PostgreSQL extended query syntax is largely supported. Connecting PSQL Psycopg Connecting Point any client able to make use of PostgreSQL Wire Protocol at Kinetica on port 5432 to connect. PSQL PSQL is a PostgreSQL CLI for connecting over PostgreSQL Wire Protocol. Connect 1 psql -h <db.host> -U <username> SELECT 1 => SELECT * FROM example.

Prepare Environment

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This example runs inside a Conda environment. The environment can be automatically configured using the conda_env_py3.yml file found in the Python UDF API repository. In the same directory you cloned the API, change directory into the root folder of the Python UDF API repository: cd kinetica-udf-api-python/ Create the Conda environment, replacing <environment name> with the desired name: conda env create --name <environment name> --file conda_env_py3.yml Note It may take a few minutes to create the environment.

Prepare Environment

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Projections

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A projection is a concept unique to Kinetica. A projection is created through the /create/projection endpoint and represents a set of columns from and/or column expressions applied to a source data set (table or view). Projections are memory-only tables by default, but can be persisted (like a table) using the persist option. While projections can simply represent a whole-cloth cross-section of an existing table, filtering clauses can be applied before creating the column to create an entirely new data set.

Projections

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Provisioning Kinetica in AWS

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Before You Start Pre-requisites AWS Account AWS Service Quota AWS Permissions Provisioning Choose an Offer Subscribe to the Product Review Terms and Conditions Configure the Software Launch the Software Create Stack Specify Stack Details Configure Stack Options Review Get the Workbench URL Appendix Network & Architecture Diagrams Security Information and Considerations Troubleshooting Managing Kinetica Support Deployed Resources Operating Costs Before You Start Note that provisioning Kinetica through the AWS Marketplace will incur charges in your AWS account.

Python

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Python

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Python UDF API

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The information below includes all the information one needs to know to begin writing UDFs using the Python UDF API. For more information on running Python UDFs, see Running Python UDFs. Dependencies UDF API Installation Python UDF Function Environments Pre-installed Libraries on the Cluster Initializing Column Types Reading Input Data Accessing Input Values Request Info Keys Writing Output Data Setting Output Values Status Reporting Complete Logging Dependencies To begin writing Python UDFs, access to the Kinetica Python UDF API is required.

Python UDF API

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Queries

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The Queries page in KAgent hosts a running log of all queries made against the database. Actions The available actions on the Queries page are as follows: Refresh the list of queries by clicking Refresh Update any of the Advanced Filter fields and click Apply Filter to filter the queries list based on the provided values. Click Clear to remove the filter. Open a detailed view of a query by clicking Detail next to the desired query:

Queries (SQL)

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Tableless Query Join ASOF Aggregation Grouping ROLLUP CUBE GROUPING SETS Window Aggregate Functions Ranking Functions Examples PIVOT UNPIVOT Set Operations UNION INTERSECT EXCEPT WITH (Common Table Expressions) Iteration Constants Numeric Constants String-Based Constants Binary Constants Date/Time Constants Expressions Conditional Functions CASE Conversion Functions Date/Time Conversion Codes Date/Time Functions Date/Time Base Functions Date/Time Complex Conversion Functions Geospatial/Geometry Functions Enhanced Performance Scalar Functions Scalar Functions Aggregation Functions Track Functions H3 Functions Math Functions Null Functions String Functions CharN Functions LIKE FILTER_BY_STRING User/Security Functions Aggregation Functions Grouping Functions ML Functions PREDICT OUTLIERS Distribution Functions Sharding Example Predicates Predicate Operators Predicate Clauses Compound Predicate Operators Subqueries Non-Correlated Subqueries Correlated Subqueries Hints EXPLAIN SELECT Statement Syntax 1 2 3 4 5 6 7 8 9 SELECT [DISTINCT | TOP <n>] <column expression> [EXCLUDE(<column exclusion list>)],.

Queries (SQL)

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Query

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Click Query in the top navigation menu to access several data management tools. SQL Tool Explain SQL Procedures Create Permissions API Tool Builder JSON DDL Tool SQL Tool The SQL Tool allows you to perform SQL queries against the data in Kinetica from GAdmin. The SQL Tool works similarly to the SQL Lab in Reveal but has fewer restrictions. To read more about using the SQL Tool from the command line (also known as KiSQL), review Kinetica SQL (KiSQL).

Query Graph

Mon, 01 Jan 0001 00:00:00 +0000

Employs a topological query on a network graph generated a-priori by Create Graph and returns a list of adjacent edge(s) or node(s), also known as an adjacency list, depending on what's been provided to the endpoint; providing edges will return nodes and providing nodes will return edges. To determine the node(s) or edge(s) adjacent to a value from a given column, provide a list of values to input parameter queries.

Query Graph

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RAPIDS Notebook Workspace

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The RAPIDS Notebook Workspace is a custom JupyterLab environment integrated within AAW. From the workspace, users can import, create, and develop Jupyter notebooks directly on top of the data necessary for machine learning workflows; monitor GPU processes and hardware; interact with and track in-depth Python workflow analytics; and much more. Prerequisites At least 1 GPU must be available to start a RAPIDS Notebook Workspace session (Kubernetes uses 1 GPU)

Removing a Kinetica in AWS Deployment

Mon, 01 Jan 0001 00:00:00 +0000

Kinetica in AWS is deployed as a CloudFormation stack and deleting the stack will remove all associated resources and costs. To delete the stack through the AWS Console: Sign into the AWS Console at: https://aws.amazon.com/console Search for CloudFormation in the console search bar. Choose the AWS Region where you originally deployed the stack (e.g., us-west-2). Select the original stack you created (not the nested stacks), and then click Delete.

Repartition Graph

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Rebalances an existing partitioned graph. IMPORTANT: It's highly recommended that you review the Network Graphs & Solvers concepts documentation, the Graph REST Tutorial, and/or some graph examples before using this endpoint. Input Parameter Description Name Type Description graph_name string Name of the graph resource to rebalance. options map of string to strings Optional parameters. The default value is an empty map ( {} ). Supported Parameters (keys) Parameter Description new_graph_name If a non-empty value is specified, the original graph will be kept (non-default behaviour) and a new balanced graph will be created under this given name.

Repartition Graph

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Resource

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All resource management related information can be found in the Resource section of GAdmin, including tier definitions, resource groups, and resource statistics. From this section, resource groups can be created and managed. Consult Resource Management for more information. Important The Resource section is only available to users with the System Admin permission. Tiers Groups Creating Groups Editing Groups Deleting Groups Statistics Tiers The Tiers page displays a summary of all tiers defined in /opt/gpudb/core/etc/gpudb.

Resource Management

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CREATE RESOURCE GROUP ALTER RESOURCE GROUP DROP RESOURCE GROUP SHOW RESOURCE GROUP Kinetica provides a SQL interface for managing resource groups, which can be used to limit memory and thread usage, and execution priority for a user or group of users. The ability to manage resource groups is available through SQL, using the following commands: CREATE RESOURCE GROUP ALTER RESOURCE GROUP DROP RESOURCE GROUP SHOW RESOURCE GROUP See Security for details on assigning resource groups to users and roles.

Resource Management

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Resource Management Concepts

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Overview Storage Tiers VRAM RAM Disk Cache Persist Cold Storage Eviction Evictability Request-Based Eviction Watermark-Based Eviction Eviction Priority Examples Request-Based Eviction Processing Watermark-Based Eviction Processing Data Movement Upward Downward Expiration On Startup Tier Strategies Tier Strategy Predicates Resource Groups Ranking and Effective Resource Groups Scheduling Scheduling Priority Overview Resource management is a feature within Kinetica designed to meet three goals: Expand the operating capacity of a cluster by backing the in-memory database with several layers of disk-based storage Allow the prioritization of data within those layers Allow the prioritization of user requests Three components are involved in managing resources:

Resource Management Concepts

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Resource Management Configuration

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Overview Tiered Storage Global Tier Parameters Tier-Specific Parameters VRAM Tier RAM Tier Disk Cache Tier Persist Tier Cold Storage Tier Default Resource Group Tier Strategy Default Tier Strategy Tier Strategy Predicate Evaluation Interval Overview Within Resource Management, there are three main areas of configuration that take place while the database is offline: Tiered Storage Default Resource Group Tier Strategy For configuration that can be performed while the database is online, see Resource Management Usage.

Resource Management Usage

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Overview Tiered Storage Altering a Tier Viewing a Tier Viewing a Table's Tier Distribution Resource Groups Managing Resource Groups Assigning Resource Groups to Users Assigning Resource Groups to Roles Tier Strategies Overview Within Resource Management, there are three main areas of usage that take place while the database is online: Tiered Storage Resource Groups Tier Strategies For configuration that must be performed while the database is offline, see Resource Management Configuration.

Reveal

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LOAD DASHBOARD Kinetica provides a SQL interface for loading Reveal dashboards from a variety of sources: KiFS path Cloud provider via data source Public URL (GitHub, etc.) LOAD DASHBOARD Syntax 1 2 3 LOAD DASHBOARD "<dashboard name>" FROM FILE PATH '<file path>' [WITH OPTIONS (DATASOURCE = '<data source name>')] Parameters Description <dashboard name> Name of the dashboard. Important This name must match the name of the dashboard in the file.

Reveal

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Reveal SDK

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Introduction Software Stack React ECMAScript 2015 (or ES6) webpack D3/NVD3 OpenLayers Architecture Data Flow Summary API/WMS Requests SDK Concepts Node Project File Python Slice Class Fieldsets Custom Fields JavaScript Slice Renderer Libraries and Modules Thumbnail Icon Cascading Style Sheets Setup/Installation Development Workflow Deployment Workflow White Labeling Brand Logo Brand Style Login Screen Title/Subtitle Theme Backup Theme Restore Upgrades Extras Connect Reveal to External Kinetica Instance Pub/Sub Data Communication Introduction Reveal is a web-based visual data exploration and insight discovery tool.

Reveal User/Role Management

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Overview Reveal manages its own application database. In addition to storing data about dashboards and slices, it also manages users, roles, and permissions for accessing those entities specific to Reveal. As a result, Reveal user management is distinct from Kinetica user management such that operations on either system will not automatically sync with the other. Authentication Reveal will need to pass credentials to support services. The credentials it will pass are those used to authenticate to it, so the users & passwords will need to be kept in sync between Reveal and the database.

Reveal User/Role Management

Mon, 01 Jan 0001 00:00:00 +0000

Overview Reveal manages its own application database. In addition to storing data about dashboards and slices, it also manages users, roles, and permissions for accessing those entities specific to Reveal. As a result, Reveal user management is distinct from Kinetica user management such that operations on either system will not automatically sync with the other. Authentication Kinetica can run with or without required client authentication; for details, see Security Configuration.

Revoke Credential Permission

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Revokes a credential-level permission from a user or role. Input Parameter Description Name Type Description name string Name of the user or role from which the permission will be revoked. Must be an existing user or role. permission string Permission to revoke from the user or role. Supported Values Description credential_admin Full read/write and administrative access on the credential. credential_read Ability to read and use the credential. credential_name string Name of the credential on which the permission will be revoked.

Revoke Credential Permission

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Revoke Data Source Permission

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Revokes a data source permission from a user or role. Input Parameter Description Name Type Description name string Name of the user or role from which the permission will be revoked. Must be an existing user or role. permission string Permission to revoke from the user or role Supported Values Description admin Admin access on the given data source connect Connect access on the given data source datasource_name string Name of the data source on which the permission will be revoked.

Revoke Data Source Permission

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Revoke Directory Permission

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Revokes a KiFS directory-level permission from a user or role. Input Parameter Description Name Type Description name string Name of the user or role from which the permission will be revoked. Must be an existing user or role. permission string Permission to revoke from the user or role. Supported Values Description directory_read For files in the directory, access to list files, download files, or use files in server side functions directory_write Access to upload files to, or delete files from, the directory.

Revoke Directory Permission

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Revoke Permission

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Revoke user or role the specified permission on the specified object. Input Parameter Description Name Type Description principal string Name of the user or role for which the permission is being revoked. Must be an existing user or role. The default value is ''. object string Name of object permission is being revoked from. It is recommended to use a fully-qualified name when possible. object_type string The type of object being revoked

Revoke Permission

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Revoke Proc Permission

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Revokes a proc-level permission from a user or role. Input Parameter Description Name Type Description name string Name of the user or role from which the permission will be revoked. Must be an existing user or role. permission string Permission to revoke from the user or role. Supported Values Description proc_admin Admin access to the proc. proc_execute Execute access to the proc. proc_name string Name of the proc to which the permission grants access.

Revoke Proc Permission

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Revoke Role

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Revokes membership in a role from a user or role. Input Parameter Description Name Type Description role string Name of the role in which membership will be revoked. Must be an existing role. member string Name of the user or role that will be revoked membership in input parameter role. Must be an existing user or role. options map of string to strings Optional parameters. The default value is an empty map ( {} ).

Revoke Role

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Revoke System Permission

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Revokes a system-level permission from a user or role. Input Parameter Description Name Type Description name string Name of the user or role from which the permission will be revoked. Must be an existing user or role. permission string Permission to revoke from the user or role. Supported Values Description system_admin Full access to all data and system functions. system_user_admin Access to administer users and roles that do not have system_admin permission.

Revoke System Permission

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Revoke Table Permission

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Revokes a table-level permission from a user or role. Input Parameter Description Name Type Description name string Name of the user or role from which the permission will be revoked. Must be an existing user or role. permission string Permission to revoke from the user or role. Supported Values Description table_admin Full read/write and administrative access to the table. table_insert Insert access to the table. table_update Update access to the table.

Revoke Table Permission

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RKinetica Connector Guide

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The following guide provides step by step instructions to get started using R with Kinetica. The RKinetica connector provides access to the Kinetica database through a REST interface. The RKinetica package can be built locally from source or a prebuilt package release can be downloaded from the release page. Kinetica strongly recommends that release builds be used instead of building the package locally. RKinetica interfaces with Kinetica similarly to other R-database interactions: using the DBI and dplyr packages.

RKinetica Connector Guide

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Rollup

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The rollup operation takes n number of columns and produces n + 1 aggregates. For example, given a rollup on columns A, B, & C, it computes the requested aggregates for the following combinations of columns: {ABC} - unique A B C triplets {AB } - unique A B pairs {A } - unique A values { } - all values The rollup operation is an aggregate function that can be invoked natively in the options map of the /aggregate/groupby endpoint.

Rollup

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Running C++ UDFs

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The information below includes all information one needs to know to begin running C++ UDFs. For more information on writing C++ UDFs, see C++ UDF API; for more information on simulating running UDFs, see UDF Simulator. Example C++ UDFs can be found here. Important Though any of the native APIs, SQL, or GAdmin can be used for deploying and executing UDFs written in any UDF API language, all the examples below are written using the native Python API for convenience.

Running Python UDFs

Mon, 01 Jan 0001 00:00:00 +0000

The information below includes all information one needs to know to begin running Python UDFs. For more information on writing Python UDFs, see Python UDF API; for more information on simulating running UDFs, see UDF Simulator. Example Python UDFs can be found here. Important Though any of the native APIs or SQL can be used for deploying and executing UDFs written in any UDF API language, all the examples below are written using the native Python API for convenience.

Running Python UDFs

Mon, 01 Jan 0001 00:00:00 +0000

The information below includes all information one needs to know to begin running Python UDFs. For more information on writing Python UDFs, see Python UDF API; for more information on simulating running UDFs, see UDF Simulator. Example Python UDFs can be found here. Important Though any of the native APIs, SQL, or GAdmin can be used for deploying and executing UDFs written in any UDF API language, all the examples below are written using the native Python API for convenience.

Schemas

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A schema is a container for all database objects. It provides namespacing for several categories of those contained database objects: Tables ( tables, external tables, views ) Credentials Data sinks Data sources Graphs Memory-only tables created by various operations Table monitors Namespacing occurs at the schema level and at the category level, meaning that: One schema could contain a table with the same name as a table in another schema.

Schemas

Mon, 01 Jan 0001 00:00:00 +0000

A schema (formerly collection) is a container for all database objects. It provides namespacing for several categories of those contained database objects: Tables ( tables, external tables, views ) Credentials Data sinks Data sources Graphs Memory-only tables created by various operations Table monitors Namespacing occurs at the schema level and at the category level, meaning that: One schema could contain a table with the same name as a table in another schema.

Security

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All credentials stored in AAW are accessible through the Security page. Credentials provide a means for AAW to access various third-party/external resources for ingestion, model, and deployment purposes, e.g., AWS S3, Docker, the Kinetica database, etc. Click Add New Credential to begin the credential setup process Type into Filter to filter down the credentials Click to display any archived credentials. Click to refresh the table Click to export the table's values as JSON or CSV Click an existing credential to display additional actions: Click View Selection to open the Credential Details page Click Export Entity to export the credential as a JSON object Click Archive to archive the credential; it will be hidden from the list of credentials Details The Credential Details page provides a detailed look at a given credential, including login information, pertinent URLs/URIs, and creation information.

Security

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User Security Detail SHOW SECURITY FOR User Role Security Detail SHOW SECURITY FOR Role Privilege Management GRANT SYSTEM Permission GRANT Schema Permission GRANT Table Permission GRANT Credential Permission GRANT Data Source Permission GRANT Data Sink Permission GRANT Directory Permission GRANT Function (UDF/UDTF) Permission GRANT Graph Permission GRANT Procedure Permission GRANT SQL-GPT Context Permission GRANT Stream Permission REVOKE SYSTEM Permission REVOKE Schema Permission REVOKE Table Permission REVOKE Credential Permission REVOKE Data Source Permission REVOKE Data Sink Permission REVOKE Directory Permission REVOKE Function (UDF/UDTF) Permission REVOKE Graph Permission REVOKE Procedure Permission REVOKE SQL-GPT Context Permission REVOKE Stream Permission SHOW SECURITY CHECK Impersonation (Execute As.

Security

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User Management CREATE USER ALTER USER DROP USER SHOW SECURITY FOR User Role Management CREATE ROLE ALTER ROLE DROP ROLE SHOW SECURITY FOR Role Privilege Management GRANT Role GRANT SYSTEM Permission GRANT Schema Permission GRANT Table Permission GRANT Credential Permission GRANT Data Source Permission GRANT Data Sink Permission GRANT Directory Permission GRANT Function (UDF/UDTF) Permission GRANT Graph Permission GRANT Procedure Permission GRANT SQL-GPT Context Permission GRANT Stream Permission REVOKE Role REVOKE SYSTEM Permission REVOKE Schema Permission REVOKE Table Permission REVOKE Credential Permission REVOKE Data Source Permission REVOKE Data Sink Permission REVOKE Directory Permission REVOKE Function (UDF/UDTF) Permission REVOKE Graph Permission REVOKE Procedure Permission REVOKE SQL-GPT Context Permission REVOKE Stream Permission SHOW SECURITY CHECK Impersonation (Execute As.

Security (User/Role Management)

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All of your user and role management can be completed using GAdmin. Important The Security section is only available to users with the system_admin or system_user_admin permission. Users Creating Users Editing Users Changing Passwords Deleting Users Roles Creating Roles Editing Roles Deleting Roles Users The Users page lists the users in the system, whether they're internal or externally authenticated, and a brief window into their access rights. Creating Users When Kinetica has been configured to authenticate and/or authorize users, user accounts can be created to allow access based on specific needs.

Security Concepts

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Overview Users Default Users Roles Default Roles Permissions System Permissions Schema Permissions Table Permissions Row-Level Security Column-Level Security Column-Level Security Functions Credential Permissions Data Source Permissions Data Sink Permissions Function Permissions Graph Permissions KiFS Permissions Procedure Permissions Table Monitor (SQL Stream) Permissions Permission Endpoints Overview Kinetica provides secured access to data and data services by means of role-based access control (RBAC). Permissions are assigned at the table level, schema level, or globally, and can be assigned either directly or grouped into roles for assignment.

Security Concepts

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Overview Users Internal Users External Users Default Users User Endpoints Roles Default Roles Role Endpoints Permissions System Permissions Schema Permissions Table Permissions Row-Level Security Column-Level Security Column-Level Security Functions Credential Permissions Data Source Permissions Data Sink Permissions Function Permissions Graph Permissions KiFS Permissions Procedure Permissions Table Monitor (SQL Stream) Permissions Permission Endpoints Overview Kinetica provides secured access to data and data services by means of role-based access control (RBAC). Permissions are assigned at the table level, schema level, or globally, and can be assigned either directly or grouped into roles for assignment.

Security Configuration

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Kinetica comes equipped with several configuration options and some software to help secure and protect your data. Currently, there are several paths to securing the database in some fashion: HTTPD -- Hides internal ports HTTPD with SSL -- Hides internal ports and secures connections HTTPD with External Authentication -- Hides internal ports and enables & configures external authentication HTTPD with SSL and External Authentication -- Hides internal ports, secures connections, and enables & configures external authentication Note

Security Usage

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The examples below use the native API to manage users, roles, and permissions. Generally, the API is symmetric across the endpoint calls, so similarly named calls between API languages should have the same function. The following security-related topics will be covered: Authentication User Management Creating Users Deleting Users Role Management Creating Roles Assigning Roles Unassigning Roles Deleting Roles Permission Management Managing System Permissions Managing Table Permissions Managing Table Permissions at the Row Level Managing Table Permissions at the Column Level Managing Credential Permissions Managing Data Source Permissions Managing Data Sink Permissions Managing Graph Permissions Managing Directory Permissions Managing Procedure Permissions Managing Table Monitor Permissions Security Information Retrieval Basic Security Information Table-Level Security Information External (LDAP) Users Global Session Timeout Configuration Authentication Connecting & authenticating to a Kinetica instance generally requires four parameters:

Show Credential

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Shows information about a specified credential or all credentials. Input Parameter Description Name Type Description credential_name string Name of the credential on which to retrieve information. The name must refer to a currently existing credential. If '*' is specified, information about all credentials will be returned. options map of string to strings Optional parameters. The default value is an empty map ( {} ). Output Parameter Description Name Type Description credential_names array of strings A list of all credential names.

Show Credential

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Show Data Sink

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Shows information about a specified data sink or all data sinks. Input Parameter Description Name Type Description name string Name of the data sink for which to retrieve information. The name must refer to a currently existing data sink. If '*' is specified, information about all data sinks will be returned. options map of string to strings Optional parameters. The default value is an empty map ( {} ). Output Parameter Description Name Type Description datasink_names array of strings The data sink names.

Show Data Sink

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Show Data Source

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Shows information about a specified data source or all data sources. Input Parameter Description Name Type Description name string Name of the data source for which to retrieve information. The name must refer to a currently existing data source. If '*' is specified, information about all data sources will be returned. options map of string to strings Optional parameters. The default value is an empty map ( {} ). Output Parameter Description Name Type Description datasource_names array of strings The data source names.

Show Data Source

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Show Directories

Mon, 01 Jan 0001 00:00:00 +0000

Shows information about directories in KiFS. Can be used to show a single directory, or all directories. Input Parameter Description Name Type Description directory_name string The KiFS directory name to show. If empty, shows all directories. The default value is ''. options map of string to strings Optional parameters. The default value is an empty map ( {} ). Output Parameter Description Name Type Description directories array of strings KiFS directory names users array of strings User that created each directory for the respective directories in output parameter directories creation_times array of longs The creation time for each directory in milliseconds since epoch, for the respective directories in output parameter directories data_usages array of longs The data usage each directory in bytes, for the respective directories in output parameter directories data_limits array of longs The data limit for each directory in bytes, for the respective directories in output parameter directories permissions array of strings Highest level of permission the calling user has for the respective directories in output parameter directories.

Show Directories

Mon, 01 Jan 0001 00:00:00 +0000

Show Environment

Mon, 01 Jan 0001 00:00:00 +0000

Shows information about a specified user-defined function (UDF) environment or all environments. Returns detailed information about existing environments. Input Parameter Description Name Type Description environment_name string Name of the environment on which to retrieve information. The name must refer to a currently existing environment. If '*' or an empty value is specified, information about all environments will be returned. The default value is ''. options map of string to strings Optional parameters.

Show Environment

Mon, 01 Jan 0001 00:00:00 +0000

Show Files

Mon, 01 Jan 0001 00:00:00 +0000

Shows information about files in KiFS. Can be used for individual files, or to show all files in a given directory. Input Parameter Description Name Type Description paths array of strings File paths to show. Each path can be a KiFS directory name, or a full path to a KiFS file. File paths may contain wildcard characters after the KiFS directory delimeter. Accepted wildcard characters are asterisk (*) to represent any string of zero or more characters, and question mark (?

Show Files

Mon, 01 Jan 0001 00:00:00 +0000

Show Graphs

Mon, 01 Jan 0001 00:00:00 +0000

Shows information and characteristics of graphs that exist on the graph server. Input Parameter Description Name Type Description graph_name string Name of the graph on which to retrieve information. If left as the default value, information about all graphs is returned. The default value is ''. options map of string to strings Optional parameters. The default value is an empty map ( {} ). Supported Parameters (keys) Parameter Description show_original_request If set to true, the request that was originally used to create the graph is also returned as JSON.

Show Graphs

Mon, 01 Jan 0001 00:00:00 +0000

Show Proc

Mon, 01 Jan 0001 00:00:00 +0000

Shows information about a proc. Input Parameter Description Name Type Description proc_name string Name of the proc to show information about. If specified, must be the name of a currently existing proc. If not specified, information about all procs will be returned. The default value is ''. options map of string to strings Optional parameters. The default value is an empty map ( {} ). Supported Parameters (keys) Parameter Description include_files If set to true, the files that make up the proc will be returned.

Show Proc

Mon, 01 Jan 0001 00:00:00 +0000

Show Proc Status

Mon, 01 Jan 0001 00:00:00 +0000

Shows the statuses of running or completed proc instances. Results are grouped by run ID (as returned from Execute Proc) and data segment ID (each invocation of the proc command on a data segment is assigned a data segment ID). Input Parameter Description Name Type Description run_id string The run ID of a specific proc instance for which the status will be returned. If a proc with a matching run ID is not found, the response will be empty.

Show Proc Status

Mon, 01 Jan 0001 00:00:00 +0000

Show Resource Group

Mon, 01 Jan 0001 00:00:00 +0000

Returns information about the internal sub-components (tiered objects) which use resources of the system. The request can either return results from actively used objects (default) or it can be used to query the status of the objects of a given list of tables. Returns detailed information about the requested resource objects. Input Parameter Description Name Type Description options map of string to strings Optional parameters. The default value is an empty map ( {} ).

Show Resource Group

Mon, 01 Jan 0001 00:00:00 +0000

Requests resource group properties. Returns detailed information about the requested resource groups. Input Parameter Description Name Type Description names array of strings List of names of groups to be shown. A single entry with an empty string returns all groups. options map of string to strings Optional parameters. The default value is an empty map ( {} ). Supported Parameters (keys) Parameter Description show_default_values If true include values of fields that are based on the default resource group.

Show Resource Group

Mon, 01 Jan 0001 00:00:00 +0000

Show Resource Group

Mon, 01 Jan 0001 00:00:00 +0000

Show Resource Statistics

Mon, 01 Jan 0001 00:00:00 +0000

Requests various statistics for storage/memory tiers and resource groups. Returns statistics on a per-rank basis. Input Parameter Description Name Type Description options map of string to strings Optional parameters. The default value is an empty map ( {} ). Output Parameter Description Name Type Description statistics_map map of string to strings Map of resource statistics info map of string to strings Additional information.

Show Resource Statistics

Mon, 01 Jan 0001 00:00:00 +0000

Show Schema

Mon, 01 Jan 0001 00:00:00 +0000

Retrieves information about a schema (or all schemas), as specified in input parameter schema_name. Input Parameter Description Name Type Description schema_name string Name of the schema for which to retrieve the information. If blank, then info for all schemas is returned. options map of string to strings Optional parameters. The default value is an empty map ( {} ). Supported Parameters (keys) Parameter Description no_error_if_not_exists If false will return an error if the provided input parameter schema_name does not exist.

Show Schema

Mon, 01 Jan 0001 00:00:00 +0000

Show Security

Mon, 01 Jan 0001 00:00:00 +0000

Shows security information relating to users and/or roles. If the caller is not a system administrator, only information relating to the caller and their roles is returned. Input Parameter Description Name Type Description names array of strings A list of names of users and/or roles about which security information is requested. If none are provided, information about all users and roles will be returned. options map of string to strings Optional parameters.

Show Security

Mon, 01 Jan 0001 00:00:00 +0000

Show SQL Procedure

Mon, 01 Jan 0001 00:00:00 +0000

Shows information about SQL procedures, including the full definition of each requested procedure. Input Parameter Description Name Type Description procedure_name string Name of the procedure for which to retrieve the information. If blank, then information about all procedures is returned. The default value is ''. options map of string to strings Optional parameters. The default value is an empty map ( {} ). Supported Parameters (keys) Parameter Description no_error_if_not_exists If true, no error will be returned if the requested procedure does not exist.

Show SQL Procedure

Mon, 01 Jan 0001 00:00:00 +0000

Show System Properties

Mon, 01 Jan 0001 00:00:00 +0000

Returns server configuration and version related information to the caller. The admin tool uses it to present server related information to the user. Input Parameter Description Name Type Description options map of string to strings Optional parameters. The default value is an empty map ( {} ). Supported Parameters (keys) Parameter Description properties A list of comma separated names of properties requested. If not specified, all properties will be returned.

Show System Properties

Mon, 01 Jan 0001 00:00:00 +0000

Show System Status

Mon, 01 Jan 0001 00:00:00 +0000

Provides server configuration and health related status to the caller. The admin tool uses it to present server related information to the user. Input Parameter Description Name Type Description options map of string to strings Optional parameters, currently unused. The default value is an empty map ( {} ). Output Parameter Description Name Type Description status_map map of string to strings A map of server configuration and health related status.

Show System Status

Mon, 01 Jan 0001 00:00:00 +0000

Show System Timing

Mon, 01 Jan 0001 00:00:00 +0000

Returns the last 100 database requests along with the request timing and internal job id. The admin tool uses it to present request timing information to the user. Input Parameter Description Name Type Description options map of string to strings Optional parameters, currently unused. The default value is an empty map ( {} ). Output Parameter Description Name Type Description endpoints array of strings List of recently called endpoints, most recent first.

Show System Timing

Mon, 01 Jan 0001 00:00:00 +0000

Show Table

Mon, 01 Jan 0001 00:00:00 +0000

Retrieves detailed information about a table, view, or schema, specified in input parameter table_name. If the supplied input parameter table_name is a schema the call can return information about either the schema itself or the tables and views it contains. If input parameter table_name is empty, information about all schemas will be returned. If the option get_sizes is set to true, then the number of records in each table is returned (in output parameter sizes and output parameter full_sizes), along with the total number of objects across all requested tables (in output parameter total_size and output parameter total_full_size).

Show Table

Mon, 01 Jan 0001 00:00:00 +0000

Show Table Metadata

Mon, 01 Jan 0001 00:00:00 +0000

Retrieves the user provided metadata for the specified tables. Input Parameter Description Name Type Description table_names array of strings Names of tables whose metadata will be fetched, in [schema_name.]table_name format, using standard name resolution rules. All provided tables must exist, or an error is returned. options map of string to strings Optional parameters. The default value is an empty map ( {} ). Output Parameter Description Name Type Description table_names array of strings Value of input parameter table_names.

Show Table Metadata

Mon, 01 Jan 0001 00:00:00 +0000

Show Table Monitors

Mon, 01 Jan 0001 00:00:00 +0000

Show table monitors and their properties. Table monitors are created using Create Table Monitor. Returns detailed information about existing table monitors. Input Parameter Description Name Type Description monitor_ids array of strings List of monitors to be shown. An empty list or a single entry with an empty string returns all table monitors. options map of string to strings Optional parameters. The default value is an empty map ( {} ).

Show Table Monitors

Mon, 01 Jan 0001 00:00:00 +0000

Show Table Statistics

Mon, 01 Jan 0001 00:00:00 +0000

Retrieves the collected column statistics for the specified table(s). Input Parameter Description Name Type Description table_names array of strings Names of tables whose metadata will be fetched, each in [schema_name.]table_name format, using standard name resolution rules. All provided tables must exist, or an error is returned. options map of string to strings Optional parameters. The default value is an empty map ( {} ). Output Parameter Description Name Type Description table_names array of strings Value of input parameter table_names.

Show Table Statistics

Mon, 01 Jan 0001 00:00:00 +0000

Show Tables by Type

Mon, 01 Jan 0001 00:00:00 +0000

Gets names of the tables whose type matches the given criteria. Each table has a particular type. This type comprises the schema and properties of the table and sometimes a type label. This function allows a look up of the existing tables based on full or partial type information. The operation is synchronous. Input Parameter Description Name Type Description type_id string Type id returned by a call to Create Type .

Show Tables by Type

Mon, 01 Jan 0001 00:00:00 +0000

Show Triggers

Mon, 01 Jan 0001 00:00:00 +0000

Retrieves information regarding the specified triggers or all existing triggers currently active. Input Parameter Description Name Type Description trigger_ids array of strings List of IDs of the triggers whose information is to be retrieved. An empty list means information will be retrieved on all active triggers. options map of string to strings Optional parameters. The default value is an empty map ( {} ). Output Parameter Description Name Type Description trigger_map map of string to maps of string to strings This dictionary contains (key, value) pairs of (trigger ID, information map/dictionary) where the key is a Unicode string representing a Trigger ID.

Show Triggers

Mon, 01 Jan 0001 00:00:00 +0000

Show Types

Mon, 01 Jan 0001 00:00:00 +0000

Retrieves information for the specified data type ID or type label. For all data types that match the input criteria, the database returns the type ID, the type schema, the label (if available), and the type's column properties. Input Parameter Description Name Type Description type_id string Type Id returned in response to a call to Create Type . label string Option string that was supplied by user in a call to Create Type .

Show Types

Mon, 01 Jan 0001 00:00:00 +0000

Show Video

Mon, 01 Jan 0001 00:00:00 +0000

Retrieves information about rendered videos. Input Parameter Description Name Type Description paths array of strings The fully-qualified KiFS paths for the videos to show. If empty, shows all videos. options map of string to strings Optional parameters. The default value is an empty map ( {} ). Output Parameter Description Name Type Description creation_times array of strings Creation time for each video as an ISO-8601 datetime. elapsed_render_time_seconds array of longs The elapsed time spent rendering each video in seconds.

Show Video

Mon, 01 Jan 0001 00:00:00 +0000

Solve Graph

Mon, 01 Jan 0001 00:00:00 +0000

Solves an existing graph for a type of problem (e.g., shortest path, page rank, travelling salesman, etc.) using source nodes, destination nodes, and additional, optional weights and restrictions. IMPORTANT: It's highly recommended that you review the Network Graphs & Solvers concepts documentation, the Graph REST Tutorial, and/or some /solve/graph examples before using this endpoint. Input Parameter Description Name Type Description graph_name string Name of the graph resource to solve. weights_on_edges array of strings Additional weights to apply to the edges of an existing graph.

Solve Graph

Mon, 01 Jan 0001 00:00:00 +0000

SQL Procedures

Mon, 01 Jan 0001 00:00:00 +0000

Supported Statements CREATE PROCEDURE ALTER PROCEDURE Set Execution User Set Execute Mode EXECUTE PROCEDURE DROP PROCEDURE SHOW PROCEDURE Security Kinetica provides support for basic SQL procedures, as an executable batch of SQL statements. A SQL procedure can be executed by two means: on-demand - called directly by a user scheduled execution - configured, upon creation, to execute at a user-specified interval Note Even if a SQL procedure is configured for scheduled execution, it can still be executed directly by a user in on-demand fashion.

SQL Procedures

Mon, 01 Jan 0001 00:00:00 +0000

SQL Reserved Word List

Mon, 01 Jan 0001 00:00:00 +0000

Kinetica reserves the following words within its SQL context. Any tables, columns, or other named references that conflict with these must be double-quoted to be used. For instance, if using a column name of abs, it must be double-quoted: 1 2 3 4 CREATE TABLE example.quoted_reserved_word_column_name ( "abs" INT ) Jump to Letter A B C D E F G H I J K L M N O P Q R S T U V W A ABS ACCESS ALL ALLOCATE ALLOW ALTER AND ANY ARE ARRAY ARRAY_MAX_CARDINALITY AS ASENSITIVE ASOF ASYMMETRIC ATOMIC AUTHORIZATION AVG B BEGIN BEGIN_FRAME BEGIN_PARTITION BETWEEN BIGINT BINARY BIT BLOB BOOLEAN BOTH BUCKET BY BYTES C CALL CALLED CARDINALITY CASCADED CASE CAST CEIL CEILING CHAR_LENGTH CHARACTER CHARACTER_LENGTH CHECK CLASSIFIER CLOB CLOSE COALESCE COLLATE COLLECT COLLECTION COLUMN COMMIT COMPRESSION CONDITION CONNECT CONSTRAINT CONVERT COPY CORR CORRESPONDING COVAR_POP COVAR_SAMP CREATE CROSS CUBE CUME_DIST CURRENT CURRENT_CATALOG CURRENT_DATE CURRENT_DEFAULT_TRANSFORM_GROUP CURRENT_PATH CURRENT_ROLE CURRENT_ROW CURRENT_SCHEMA CURRENT_TIME CURRENT_TIMESTAMP CURRENT_TRANSFORM_GROUP_FOR_TYPE CURRENT_USER CURSOR CYCLE D DEALLOCATE DEC DECLARE DEFAULT_ DEFAULTVALUE DEFINE DELETE DELIMITED DENSE_RANK DEREF DESCRIBE DETERMINISTIC DICT DISALLOW DISCONNECT DISK_OPTIMIZED DISTINCT DROP DYNAMIC E EACH ELEMENT ELSE EMPTY END END_EXEC END_FRAME END_PARTITION EQUALS ESCAPE EVERY EXCEPT EXEC EXECUTE EXISTS EXP EXPLAIN EXTEND EXTERNAL EXTRACT F FALSE FETCH FIRST_VALUE FLOOR FOR FOREIGN FORMAT FRAME_ROW FREE FROM FULL FUNCTION FUSION G GET GLOBAL GRANT GROUP GROUPING GROUPS H HAVING HOLD I IDENTIFIED IDENTITY IGNORE IMPORT IN INCLUDE INDICATOR INITIAL INNER INOUT INSENSITIVE INSERT INTEGER INTERSECT INTERSECTION INTERVAL INTO IS J JOIN JSON_ARRAY JSON_ARRAYAGG JSON_EXISTS JSON_OBJECT JSON_OBJECTAGG JSON_QUERY JSON_VALUE K KERBEROS L LAG LANGUAGE LARGE LAST_VALUE LATERAL LEAD LEADING LEFT LIKE LIKE_REGEX LIMIT LN LOCAL LOCALTIME LOCALTIMESTAMP LOWER M MATCH MATCH_NUMBER MATCH_RECOGNIZE MAX MEASURES MEMBER MERGE METHOD MIN MINUS MOD MODIFIES MODIFY MODULE MOVE MULTISET N NATIONAL NATURAL NCHAR NCLOB NEW NEXT NO NONE NORMALIZE NOT NTH_VALUE NTILE NULL NULLIF NUMERIC O OCCURRENCES_REGEX OCTET_LENGTH OF OFFSET OLD OMIT ON ONE ONLY OPEN OR ORDER OUT OUTER OVER OVERLAPS OVERLAY P PARAMETER PARTITION PASSWORD PATHS PATTERN PER PERCENT PERCENT_RANK PERCENTILE_CONT PERCENTILE_DISC PERIOD PERMUTE PIVOT PORTION POSITION_REGEX POWER PRECEDES PRECISION PREPARE PREV PRIMARY PRIMARY_KEY PROCEDURE PROTECTED Q QUOTE_ R RANGE RANK READS REAL RECURSIVE REFERENCES REFERENCING REGR_AVGX REGR_AVGY REGR_COUNT REGR_INTERCEPT REGR_R2 REGR_SLOPE REGR_SXX REGR_SXY REGR_SYY RELEASE RENAME REPLICATED RESET RESOURCE_ RESPECT RESULT RETURN REVOKE RIGHT ROLLBACK ROLLUP ROW ROW_NUMBER ROWS RUNNING S SAVEPOINT SCOPE SCROLL SEARCH SECONDS SEEK SELECT SENSITIVE SESSION_USER SET SET_MINUS SHARD SHARD_KEY SHOW SIMILAR SKIP_ SMALLINT SOME SPECIFIC SPECIFICTYPE SQL SQL_DATETIME SQL_TSI_MILLISECOND SQLEXCEPTION SQLSTATE SQLWARNING SQRT START STATIC STATISTICS STDDEV_POP STDDEV_SAMP STREAM SUBMULTISET SUBSET SUBSTR SUBSTRING SUBSTRING_REGEX SUCCEEDS SUM SYMMETRIC SYSTEM_TIME SYSTEM_USER T TABLE TABLESAMPLE TEXT_SEARCH THEN TIMEZONE_HOUR TIMEZONE_MINUTE TINYINT TO TOKEN_ TOP TRAILING TRANSLATE TRANSLATE_REGEX TRANSLATION TREAT TRIGGER TRIM TRIM_ARRAY TRUE TRUNCATE TTL U UESCAPE UNION UNIQUE UNKNOWN UNNEST UNPIVOT UNSIGNED UPDATE UPPER UPSERT USER USING V VALUE_OF VALUES VAR_POP VAR_SAMP VARBINARY VARCHAR VARYING VERSIONING W WHEN WHENEVER WHERE WIDTH_BUCKET WINDOW WITH WITHIN WITHOUT

SQL Reserved Word List

Mon, 01 Jan 0001 00:00:00 +0000

SQL-GPT Concepts

Mon, 01 Jan 0001 00:00:00 +0000

Overview Generating SQL SQL-GPT Context Context Overview Context Syntax Table Definition Clause Sample Definition Clause Rule Definition Clause Context Best Practices Managing Context Size Reducing Ambiguity Managing SQL Generation LLM Options SQL-GPT is a Kinetica generative AI capability that produces SQL based on questions asked in natural language. A SQL-GPT interface is integrated into the top of each Worksheet of every Workbook in Kinetica. The feature provides the option to customize the SQL-GPT context for each Workbook independently.

SQL-GPT Concepts

Mon, 01 Jan 0001 00:00:00 +0000

SQL-GPT Syntax

Mon, 01 Jan 0001 00:00:00 +0000

CREATE CONTEXT Table Definition Clause Sample Definition Clause Rule Definition Clause Example ALTER CONTEXT Add Context Table Drop Context Table Add Context Samples Drop Context Samples Add Context Rules Drop Context Rules DROP CONTEXT SHOW CONTEXT DESCRIBE CONTEXT GENERATE SQL SQL Generation Options SQL Generation Example EXECUTE_AI_QUERY SQL Generation Options SQL Execution Example Kinetica provides support for generative AI via SQL-GPT. SQL-GPT context management features accessible via SQL include:

SQL-GPT Syntax

Mon, 01 Jan 0001 00:00:00 +0000

Stats

Mon, 01 Jan 0001 00:00:00 +0000

Detailed statistics dashboards about Kinetica and its host(s) can be accessed under the Stats menu. Collected statistics are divided into four groups: Kinetica Tiered storage and resource groups System GPU (if the CUDA version of Kinetica is installed) Important The Stats section is only available to users with the System Admin permission. Kinetica Tiered Storage and Resource Groups Systems Overview GPU Overview Kinetica The Kinetica DB Overview dashboard is home to metrics related to the performance and health of your entire Kinetica instance.

Storm Developer Manual

Mon, 01 Jan 0001 00:00:00 +0000

The following guide provides step by step instructions to get started integrating Kinetica with Storm. This project is aimed to make Kinetica accessible via Storm, meaning data can be streamed from a Kinetica table or to a Kinetica table. The custom Storm Spout and Bolt do no additional processing. Source code for the connector can be found at https://github.com/kineticadb/kinetica-connector-storm Connector Classes The two connector classes that integrate Kinetica with Storm are:

Storm Developer Manual

Mon, 01 Jan 0001 00:00:00 +0000

Support

Mon, 01 Jan 0001 00:00:00 +0000

The Support menu contains links to Kinetica documentation, as well as API & driver downloads. Docs APIs Drivers Docs Docs links to Kinetica system & API documentation, covering all facets of using & managing the database and related applications & services. APIs APIs links to the API download page, where both the native database and UDF APIs can be downloaded in each of the supported development languages. Drivers Drivers links to the GitHub projects for each of the Kinetica integration connectors.

System Properties

Mon, 01 Jan 0001 00:00:00 +0000

ALTER SYSTEM SET PROPERTIES SHOW SYSTEM PROPERTIES Kinetica provides a SQL interface for managing system properties, which control everything from GPUs, hostnames, storage, graph server, and more. The ability to manage system properties is available through SQL, using the following commands: ALTER SYSTEM SET PROPERTIES SHOW SYSTEM PROPERTIES ALTER SYSTEM SET PROPERTIES Only a small subset of the system properties can be altered at runtime. See the /alter/system/properties endpoint documentation for the full list.

System Properties

Mon, 01 Jan 0001 00:00:00 +0000

Table Monitors

Mon, 01 Jan 0001 00:00:00 +0000

Overview Configuration Local ZMQ External Consumer Managing Table Monitors Limitations & Cautions Example Overview A table monitor (SQL Stream) is an entity that can be created to watch a target table for inserts, updates, or deletes, and relay notifications for consumption by interested clients to one of the following targets: a local ZMQ message queue (default) an external Apache Kafka broker an external webhook A table monitor is bound to a single type of table operation to monitor, assigned when created, and cannot be changed to monitor other types afterwards.

Table Monitors

Mon, 01 Jan 0001 00:00:00 +0000

Tables

Mon, 01 Jan 0001 00:00:00 +0000

Overview Name Resolution Naming Criteria Example Distribution Sharding Random Sharding Replication Partitioning Range Interval List Hash Series Primary Keys Purpose Designation Relation to Shard Key Relation to Foreign Key Index Creation Shard Keys Purpose Designation Relation to Primary Key Creation Foreign Keys Purpose Designation Relation to Primary Key Relation to Shard Key Creation Overview The concept of tables is at the heart of Kinetica interactions. A table is a data container associated with a specific type (set of columns & properties), much like tables in other database platforms.

Tables

Mon, 01 Jan 0001 00:00:00 +0000

Time Bucketing

Mon, 01 Jan 0001 00:00:00 +0000

Time bucketing is the segmenting of a given data set into "buckets", based on some time-based column value or expression within the set. TIME_BUCKET Time bucketing is accomplished through the use of the TIME_BUCKET function, which calculates the time range in which a given timestamp falls, based on a set of fixed-width "buckets", start-aligned to a date/time, and offset from that start date/time. The basic form of the TIME_BUCKET function is:

Time Bucketing

Mon, 01 Jan 0001 00:00:00 +0000

TTL

Mon, 01 Jan 0001 00:00:00 +0000

Time-to-live (TTL) is a configurable number of minutes since last access before a table or view will expire and be removed from the database. A TTL of -1 will direct that an entity not expire. If a table or view is assigned a TTL, its expiration timer will be reset to the value of its configured TTL each time it is accessed. For instance, a view with a five minute TTL will have its life extended by five minutes from the time it is accessed every time it is accessed.

TTL

Mon, 01 Jan 0001 00:00:00 +0000

Types

Mon, 01 Jan 0001 00:00:00 +0000

Type Label Type Definition Column Types Column Properties Data Types Data Handling Data Keys Data Replacement A type is analogous to a traditional database definition for a table. Before data can be stored in Kinetica, a type must be specified for that data. For every type, Kinetica assigns a unique GUID. Kinetica will use the same GUID for all types with identical characteristics. Every type in Kinetica consists of the following:

Types

Mon, 01 Jan 0001 00:00:00 +0000

UDF

Mon, 01 Jan 0001 00:00:00 +0000

The UDF menu allows you to manage your User-Defined Functions (UDFs). The UDF menu is only available if UDFs have been enabled. See User-Defined Function Implementation for UDF configuration requirements and User-Defined Functions Overview for detail on UDFs themselves. Important The UDF section is only available to users with the system_admin role or the proc_execute permission. UDF Creating Procs Executing UDFs Editing UDFs Deleting UDFs Permissions Status UDF UDF is the UDF homepage and allows executing, creating, editing, and deleting UDFs.

UDF API Download

Mon, 01 Jan 0001 00:00:00 +0000

UDF API Download This example requires local access to the Python UDF API repository. In the desired directory, run the following but be sure to replace <kinetica-version> with the name of the installed Kinetica version, e.g, v7.1: git clone -b release/<kinetica-version> --single-branch https://github.com/kineticadb/kinetica-udf-api-python.git

UDF API Download

Mon, 01 Jan 0001 00:00:00 +0000

UDF Simulator

Mon, 01 Jan 0001 00:00:00 +0000

The UDF simulator simulates the mechanics of the /execute/proc call without the UDF actually having to be created in the database. The simulator reads data out of tables, writes it to files in the correct format, and provides the environment variable that needs to be set for the UDF API. After the UDF code is run, it can optionally read any output that was written and write it back into Kinetica.

UDF Simulator

Mon, 01 Jan 0001 00:00:00 +0000

Union

Mon, 01 Jan 0001 00:00:00 +0000

Kinetica supports the concept of set union, which is a representation of all rows that appear across a group of specified data sets (tables or views). See UNION for the SQL version of this operation. A union is performed using the /create/union endpoint, using one of the following modes: Union -- retains all unique rows from the specified data sets Union Distinct -- alias for Union Union All -- retains all rows from the specified data sets Merge Views -- merge two or more filtered views (or filtered views of filtered views) of the same base data set into a new view.

Union

Mon, 01 Jan 0001 00:00:00 +0000

Unpivot

Mon, 01 Jan 0001 00:00:00 +0000

The unpivot operation works much the same as the SQL concept: "rotating" a set of column headers (and the associated values) into rows to create a more normalized table that's longer and narrower. It is nearly the opposite of the pivot operation, though it will not be able to unmerge records and restore nulls that were aggregated by the pivot operation. You can perform unpivot operations using /aggregate/unpivot or via the SQL UNPIVOT function.

Unpivot

Mon, 01 Jan 0001 00:00:00 +0000

Unpivot Table

Mon, 01 Jan 0001 00:00:00 +0000

Rotate the column values into rows values. For unpivot details and examples, see Unpivot. For limitations, see Unpivot Limitations. Unpivot is used to normalize tables that are built for cross tabular reporting purposes. The unpivot operator rotates the column values for all the pivoted columns. A variable column, value column and all columns from the source table except the unpivot columns are projected into the result table. The variable column and value columns in the result table indicate the pivoted column name and values respectively.

Unpivot Table

Mon, 01 Jan 0001 00:00:00 +0000

Update Records

Mon, 01 Jan 0001 00:00:00 +0000

Runs multiple predicate-based updates in a single call. With the list of given expressions, any matching record's column values will be updated as provided in input parameter new_values_maps. There is also an optional 'upsert' capability where if a particular predicate doesn't match any existing record, then a new record can be inserted. Note that this operation can only be run on an original table and not on a result view.

Update Records

Mon, 01 Jan 0001 00:00:00 +0000

Update Records by Series

Mon, 01 Jan 0001 00:00:00 +0000

Updates the view specified by input parameter table_name to include full series (track) information from the input parameter world_table_name for the series (tracks) present in the input parameter view_name. Input Parameter Description Name Type Description table_name string Name of the view on which the update operation will be performed, in [schema_name.]view_name format, using standard name resolution rules. Must be an existing view. world_table_name string Name of the table containing the complete series (track) information, in [schema_name.

Update Records by Series

Mon, 01 Jan 0001 00:00:00 +0000

Upgrade

Mon, 01 Jan 0001 00:00:00 +0000

Upgrading to Kinetica 7.1 is facilitated through the use of KAgent. KAgent 7.1 provides the ability to upgrade existing Kinetica clusters managed by KAgent 7.0 or clusters that are not managed at all. Upgrading requires the system be Kinetica 7.0.11 or newer. If running Kinetica 6.2 or a 7.0 version prior to that, refer to the Kinetica 7.0 Upgrade instructions for details on upgrading to a 7.0.11 or newer version first, and then refer back to this guide to complete the upgrade to version 7.

Upgrade

Mon, 01 Jan 0001 00:00:00 +0000

If a new version of Kinetica is available, you will see a notification in the upper right hand corner of Workbench. Clicking on Upgrade, you will see a list of available versions. Once you choose to initiate the upgrade, the cluster will be suspended until the upgrade process completes.

Upload Files

Mon, 01 Jan 0001 00:00:00 +0000

Uploads one or more files to KiFS. There are two methods for uploading files: load files in their entirety, or load files in parts. The latter is recommeded for files of approximately 60 MB or larger. To upload files in their entirety, populate input parameter file_names with the file names to upload into on KiFS, and their respective byte content in input parameter file_data. Multiple steps are involved when uploading in multiple parts.

Upload Files

Mon, 01 Jan 0001 00:00:00 +0000

Upload Files From URL

Mon, 01 Jan 0001 00:00:00 +0000

Uploads one or more files to KiFS. Each file path must reside in a top-level KiFS directory, i.e. one of the directories listed in Show Directories. The user must have write permission on the directory. Nested directories are permitted in file name paths. Directories are deliniated with the directory separator of '/'. For example, given the file path '/a/b/c/d.txt', 'a' must be a KiFS directory. These characters are allowed in file name paths: letters, numbers, spaces, the path delimiter of '/', and the characters: '.

Upload Files From URL

Mon, 01 Jan 0001 00:00:00 +0000

Usage

Mon, 01 Jan 0001 00:00:00 +0000

The Usage page in KAgent hosts detailed system and resource group usage statistics and metrics. System Events Timeline Resource Groups System The System tab under the Usage page displays several system usage metric and statistics graphs as well as an Events Timeline. Click one of the timeframe control buttons or select a date-time range to adjust the event timeline and the metric graphs to the selected duration Adjust the Ring, Cluster, and/or Node drop-down menus to filter the graphs for the selected ring / cluster / node Point the cursor to a graph to see the value at that time Events Timeline The Events Timeline displays events that have occurred within the selected timeframe.

User

Mon, 01 Jan 0001 00:00:00 +0000

Click your username in the top navigation menu to review open GAdmin sessions, change your password, or log out of GAdmin. Sessions Change Password Logout Sessions Click Sessions to open the list of currently open GAdmin sessions. Select any of the sessions not designated as Current (displays the logo) and click Terminate to remotely terminate that session. The user for the session will be forced to login again. Change Password Click Change Password to change your password.

User Defined Functions (UDFs)

Mon, 01 Jan 0001 00:00:00 +0000

CREATE FUNCTION Executing Functions Function Parameters Examples DROP FUNCTION SHOW FUNCTION SHOW FUNCTION STATUS DESCRIBE FUNCTION CREATE FUNCTION ENVIRONMENT ALTER FUNCTION ENVIRONMENT DROP FUNCTION ENVIRONMENT SHOW FUNCTION ENVIRONMENT DESCRIBE FUNCTION ENVIRONMENT Kinetica provides support for User-Defined Function (UDF) creation and management in SQL. Unlike conventional UDFs, Kinetica UDFs are external programs that can be managed via SQL and may run in distributed fashion across the cluster. A UDF that is defined to return a specific table type is known as a User-Defined Table Function (UDTF), which can be used within a SELECT statement to return the output of the function as a query result set.

User Defined Functions (UDFs)

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User Management

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Once Kinetica is connected to an external authentication source, the external users can be used for all Kinetica administration. First, a user with administrative permissions that can be tied to an external user will need to be created within Kinetica: Log into Kinetica Administration Application (GAdmin) with an internal Kinetica administration account From the Security menu, select Users Click the New button For Authentication, select External Enter an external user's username, preceded by @.

User-Defined Functions Overview

Mon, 01 Jan 0001 00:00:00 +0000

Kinetica supports the concept of user-defined functions (UDF) via a mechanism similar to stored procedures, being a user-defined sequence of operations on a specified data set. UDFs In-Depth: UDF Implementation -- detail about writing & running and for some examples of UDFs Python UDF Tutorial -- example UDF workflow in Python In Kinetica, there are two types of UDFs: distributed - the procedure will be invoked within the database, executing in parallel against each data shard of the specified tables.

User-Defined Functions Overview

Mon, 01 Jan 0001 00:00:00 +0000

Using Workbooks in Workbench

Mon, 01 Jan 0001 00:00:00 +0000

Explorer Panel Data Explorer Creating and Modifying Data Objects Previewing Objects Deleting Objects Workbook Explorer Creating a New Workbook Example Workbook Exporting/Importing Workbooks File Explorer Uploading a File Importing a File SQL Workbooks and Worksheets Workbooks SQL-GPT SQL Blocks Type-ahead Running Individual Blocks Running All Blocks Canceling Jobs Visual Explain Plan Map Blocks Graph Blocks Graph Example Presentation Blocks Visualizations Bar Chart Line Chart Pie Chart Scatter Plot Big Number Graph Map Importing Data Import Data Wizard Import via SQL Explorer Panel On the left side of the screen, you will see a tabbed panel, which we call the Explorer.

Using Workbooks in Workbench

Mon, 01 Jan 0001 00:00:00 +0000

Vector Tile Service

Mon, 01 Jan 0001 00:00:00 +0000

Overview Configuration Usage Example Limitations and Cautions Overview Kinetica provides a Vector Tile Service (VTS) to generate Vector Tiles and support client-side visualization of the geospatial data contained within the tiles. The Vector Tile format generated follows the open standard Mapbox Vector Tile specification. The Kinetica VTS feeds a client-side Vector Tile renderer, such as Mapbox GL, by adding the VTS URL to the renderer's style configuration as a map layer source.

Vector Tile Service

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Verification

Mon, 01 Jan 0001 00:00:00 +0000

Restart host manager and the database using: service gpudb_host_manager start service gpudb start Run a Host Manager status check: service gpudb_host_manager status Verify the output shows HTTPD is running: ... Httpd : Running (14250 14277 14278 14279 14280 14282) ... Ensure HTTPD is working: curl <hostname>:8082 Ensure Kinetica is running properly: curl <hostname>:8082/gpudb-0 Verify both internal and external users can login to GAdmin at http://<hostname>:8080 Verify both internal and external users can login to Reveal at http://<hostname>:8088

Verification

Mon, 01 Jan 0001 00:00:00 +0000

Verification

Mon, 01 Jan 0001 00:00:00 +0000

Restart host manager and the database using: service gpudb_host_manager start service gpudb start Run a Host Manager status check: service gpudb_host_manager status Verify the output shows HTTPD is running: ... Httpd : Running (14250 14277 14278 14279 14280 14282) ... Ensure Kinetica is running properly: curl -k https://<hostname>:8082/gpudb-0 Verify the output shows Kinetica is running: Kinetica is running! Verify both internal and external users can login to GAdmin at https://<hostname>:8443

Verification

Mon, 01 Jan 0001 00:00:00 +0000

Restart host manager and the database using: service gpudb_host_manager start service gpudb start Run a Host Manager status check: service gpudb_host_manager status Verify the output shows HTTPD is running: ... Httpd : Running (14250 14277 14278 14279 14280 14282) ... Ensure Kinetica is running properly: curl -k https://<hostname>:8082/gpudb-0 Verify the output shows Kinetica is running: Kinetica is running! Login to GAdmin at https://<hostname>:8443 Login to Reveal at https://<hostname>:8444 Login to Workbench at https://<hostname>:8445

Views

Mon, 01 Jan 0001 00:00:00 +0000

Views can be organized into three categories: Filtered Views -- created from: /filter /filter/byarea /filter/bybox /filter/bygeometry /filter/bylist /filter/byradius /filter/byrange /filter/byseries /filter/bystring /filter/bytable /filter/byvalue Join views -- created from: /create/jointable Materialized Views -- created from: /create/materializedview

Views

Mon, 01 Jan 0001 00:00:00 +0000

Virtual Catalogs

Mon, 01 Jan 0001 00:00:00 +0000

Kinetica Virtual Catalog ANSI Virtual Catalog PostgreSQL Virtual Catalog Kinetica provides metadata tables, or virtual catalogs, as a means of querying the database for information about its objects, relationships, and permissions. Virtual catalogs can be used to easily search for database tables & views by name without knowing the containing schema name, or for database columns by name without knowing the containing table or view name. They can be used to generate reports of the database structure or audit the creation & modification of that structure.

Virtual Catalogs

Mon, 01 Jan 0001 00:00:00 +0000

Visualize Image Chart

Mon, 01 Jan 0001 00:00:00 +0000

Scatter plot is the only plot type currently supported. A non-numeric column can be specified as x or y column and jitters can be added to them to avoid excessive overlapping. All color values must be in the format RRGGBB or AARRGGBB (to specify the alpha value). The image is contained in the output parameter image_data field. Input Parameter Description Name Type Description table_name string Name of the table containing the data to be drawn as a chart, in [schema_name.

Visualize Image Chart

Mon, 01 Jan 0001 00:00:00 +0000

Visualize Isochrone

Mon, 01 Jan 0001 00:00:00 +0000

Generate an image containing isolines for travel results using an existing graph. Isolines represent curves of equal cost, with cost typically referring to the time or distance assigned as the weights of the underlying graph. See Network Graphs & Solvers for more information on graphs. Input Parameter Description Name Type Description graph_name string Name of the graph on which the isochrone is to be computed. source_node string Starting vertex on the underlying graph from/to which the isochrones are created.

Visualize Isochrone

Mon, 01 Jan 0001 00:00:00 +0000

Web Map Service

Mon, 01 Jan 0001 00:00:00 +0000

Overview Downloads Required Parameters Optional Parameters Modes RASTER CB_RASTER HEATMAP CONTOUR LABELS ISOCHRONES Overview Kinetica provides a Web Map Service (WMS) for generating image tiles from the geospatial data contained in it. The type of image tiles returned, the data used to generate the tiles, and the graphical styles in the tiles are specified in the query string of the WMS call. These would typically be used as overlays on top of a map.

Web Map Service

Mon, 01 Jan 0001 00:00:00 +0000

Window

Mon, 01 Jan 0001 00:00:00 +0000

Function Details Function Type Aggregate Ranking Window Specification Frame Clauses Range Frames Rows Frames Frame Bounds Examples Limitations Kinetica supports the SQL concept of windows. It can do so through the /create/projection and /get/records/bycolumn endpoints. The window function is specified as a column name in the column_name parameter. A window projection can be created from any table or view. If the source data set is replicated, the resulting window projection will also be replicated.

Window

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WMS Layers

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Examples Initializing the Map Adding a Raster/Heatmap/Contour Layer Adding a Labels Layer Adding a Class Break Raster Layer Resizing the Browser Full Code Example Examples Examples of the following layer types are available below: Raster Heatmap Class Break Raster Contour Labels Note You will need a current Mapbox API key and some minor modifications will be required in order to run each example. At a minimum, you will need a Kinetica table with latitude/longitude values, or WKTs.

WMS Layers

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Workbook Explorer

Mon, 01 Jan 0001 00:00:00 +0000

General Features Workbook Lists The Workbook Explorer can be used to manage Workbooks. Workbook Explorer Tab To access the Workbook Explorer, in Workbench, click the Workbooks tab of the left-hand navigation pane. General Features At the top of the Workbook Explorer tab are several workbook actions: Search box - filters displayed workbooks, by name Refresh icon - refreshes the list of displayed workbooks + icon - adds a new workbook Workbook Lists The Workbook Explorer has two lists of workbooks:

Workbook Explorer

Mon, 01 Jan 0001 00:00:00 +0000