Apache Spark SQL

Capabilities

Capability	Support	Notes
Tables, views & columns	Supported
Keys, constraints & indexes	Not available
Procedures & functions	Not available
Data lineage	Partial
Lineage from query history	Not available
Business glossary links	Supported
Data quality probes	Supported
Data profiling	Supported
Data classification	Supported
Chat with your data	Supported

Connection settings

Create the connection on the Blindata Agent from Settings > Agents > Connections with the connection wizard, choosing Apache Hive in the technology step.

Driver class	org.apache.hive.jdbc.HiveDriver
JDBC URL	jdbc:hive2://localhost:10000/default
Authentication	Service principal (shared technical user) User principal (personal credentials, BYOC) Ephemeral credentials (asked at each run)
Crawling strategy	JDBC

The Blindata Agent does not include this driver: download the vendor JDBC driver and copy the .jar into the agent drivers folder, as described in Add JDBC drivers. Driver properties can be added under Advanced settings in the connection wizard.

Prerequisites & permissions

• A Blindata Agent installed with network access to Apache Spark SQL.
• The vendor JDBC driver installed on the agent (see Add JDBC drivers).
• A user allowed to list databases and describe tables through the Thrift Server.

Set up metadata crawling

1. Create the connection to Apache Spark SQL on the agent (see Connection settings) and use Test to verify it.
2. Create or open the system that represents Apache Spark SQL in the catalog and link it to the connection.
3. In the CRAWLING tab add a crawling job with strategy JDBC.
4. Run a TEST to check the number of extracted objects, then RUN or schedule the job.

The job options and the column aliases of every extraction query are described in the Generic JDBC reference.

Related guides

• Metadata import with interface tables
• Data quality probes
• Automated SQL lineage
• Scheduling agent jobs

Updated on 16 Oct 2026