Connecting to Spark SQL

For information on the available WHL and TAR.GZ files for supported environments, and how to install the appropriate file for your Python distribution, see Package Installation.

For information on the module to import, and how to configure the necessary connection properties in a connection string, see Establishing a Connection.

Other available connection properties can be used to configure other aspects of the connector capabilities.

Python Version Support

The CData Python Connector for Spark SQL can be installed and used in various Python 3.8, 3.9, 3.10, and 3.11 distributions.

Spark SQL Version Support

The connector leverages Spark Thrift to enable bidirectional SQL access to Spark SQL data. It supports Spark SQL version 1.6 and above.

See Also

• Using the Connector: Establish connections and query Spark SQL through Python code.
• From SQLAlchemy: Use SQLAlchemy to establish a connection with dialect URL, and interact with Spark SQL data using mapped classes and Sessions.