1 of 1

Spark

Pinot supports Apache spark as a processor to create and push segment files to the database. Pinot distribution is bundled with the Spark code to process your files and convert and upload them to Pinot.

You can follow the wiki to build pinot distribution from source. The resulting JAR file can be found in pinot/target/pinot-all-${PINOT_VERSION}-jar-with-dependencies.jar

Next, you need to change the execution config in the job spec to the following -

You can check out the sample job spec here.

To run Spark ingestion, you need the following jars in your classpath

pinot-batch-ingestion-spark plugin jar - available in plugins-external directory in the package
pinot-all jar - available in lib directory in the package

These jars can be specified using spark.driver.extraClassPath or any other option.

For loading any other plugins that you want to use, you can use -

The complete spark-submit command should look as follows

Please ensure environment variables PINOT_ROOT_DIR and PINOT_VERSION are set properly.

Note: You should change the master to yarn and deploy-mode to cluster for production environments

We have stopped including spark-core dependency in our jars post 0.10.0 release. Users can try 0.11.0-SNAPSHOT and later versions of pinot-batch-ingestion-spark in case of any runtime issues. You can either or .

For Pinot version prior to 0.10.0, the spark plugin is located in ${PINOT_DISTRIBUTION_DIR}/plugins/pinot-batch-ingestion/pinot-batch-ingestion-spark/pinot-batch-ingestion-spark-${PINOT_VERSION}-shaded.jar