/7.1/connectors/Recent content in Connectors on Kinetica DocsHugo -- gohugo.ioen/7.1/connectors/kickbox_api/Mon, 01 Jan 0001 00:00:00 +0000/7.1/connectors/kickbox_api/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./7.1/connectors/beam_guide/Mon, 01 Jan 0001 00:00:00 +0000/7.1/connectors/beam_guide/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./7.1/connectors/kickbox/Mon, 01 Jan 0001 00:00:00 +0000/7.1/connectors/kickbox/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./7.1/connectors/fme_kinetica_format/Mon, 01 Jan 0001 00:00:00 +0000/7.1/connectors/fme_kinetica_format/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./7.1/connectors/spark_guide/Mon, 01 Jan 0001 00:00:00 +0000/7.1/connectors/spark_guide/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./7.1/connectors/nifi_guide/Mon, 01 Jan 0001 00:00:00 +0000/7.1/connectors/nifi_guide/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:/7.1/connectors/sql_guide/Mon, 01 Jan 0001 00:00:00 +0000/7.1/connectors/sql_guide/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./7.1/connectors/kickbox_clustering/Mon, 01 Jan 0001 00:00:00 +0000/7.1/connectors/kickbox_clustering/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./7.1/connectors/psql_wire_protocol/Mon, 01 Jan 0001 00:00:00 +0000/7.1/connectors/psql_wire_protocol/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./7.1/connectors/r_guide/Mon, 01 Jan 0001 00:00:00 +0000/7.1/connectors/r_guide/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./7.1/connectors/storm_guide/Mon, 01 Jan 0001 00:00:00 +0000/7.1/connectors/storm_guide/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:/7.1/connectors/kickbox_wms/Mon, 01 Jan 0001 00:00:00 +0000/7.1/connectors/kickbox_wms/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.