Spark ODBC

Type of Support:	Read & Write; In-Database
Validated On:	Spark 1.2.0; Simba Spark Driver 1.02.04.1005
Connection Type:	ODBC (32- and 64-bit)
Driver Details:	The ODBC driver can be downloaded here. In-Database processing requires 64-bit database drivers.
Driver Configuration Requirements:	For optimal performance, you must enable the Fast SQLPrepare option within the driver Advanced Options to allow Alteryx to retrieve metadata without running a query.

Alteryx tools used to connect

Input Data Tool and Output Data Tool (Standard workflow processing)
Connect In-DB Tool and Data Stream In Tool (In-database workflow processing)

Additional Details

To use the Spark ODBC, you must have Spark SQL enabled. Not all Hadoop distributions support Spark. If you are unable to connect using Spark ODBC, contact your Hadoop vendor for instructions on how to set up the Spark server correctly.

If you have issues with reading or writing Unicode characters, select the âUse SQL Unicode Typesâ option within the Simba Impala ODBC driver Advanced Options.

Read Support

Install and configure the Spark ODBC driver:

Spark Server Type: Select the appropriate server type for the version of Spark that you are running. If you are running Spark 1.1 and later, then select SparkThriftServer.
Authentication Mechanism: See the installation guide downloaded with the Simba Spark driver to configure this setting based on your setup.

To set up the driver Advanced Options, see the installation guide downloaded with the Simba Spark driver.

Write Support

For both standard and in-database workflows, use the Data Stream In Tool to write to Spark. Write support is via HDFS.
If you are writing with HDFS Avro, you must select the Default WebHDFS (50070) port option in the HDFS Avro Connection properties window.

To write a table with field names that total more than 4000 characters, use CSV instead of Avro.