/7.1/guide-tags/sql/Recent content in SQL on Kinetica DocsHugo -- gohugo.ioen/7.1/guides/quickstart-guide/Mon, 01 Jan 0001 00:00:00 +0000/7.1/guides/quickstart-guide/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./7.1/guides/sql_guide/Mon, 01 Jan 0001 00:00:00 +0000/7.1/guides/sql_guide/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./7.1/guides/udf-sql-sentence-transformers/Mon, 01 Jan 0001 00:00:00 +0000/7.1/guides/udf-sql-sentence-transformers/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./7.1/guides/wkt_data_geo_functions/Mon, 01 Jan 0001 00:00:00 +0000/7.1/guides/wkt_data_geo_functions/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.