This section provides information on how to enable and configure the Spark running environment, which leverages Spark's faster in-memory processing to deliver better execution performance.
NOTE: When a recipe containing a user-defined function is applied to text data, any non-printing (control) characters cause records to be truncated by the Spark running environment during job execution. In these cases, please execute the job on the running environment.
The Spark execution environment is enabled by default.
NOTE: If you have not done so already, please enable and configure the Spark Job Service. See Configure for Spark.
When Spark execution is enabled, it is available like any other execution environment in the application. When executing a job, select the Spark option from the drop-down in the Run Job page. See Run Job Page.
For more information on changing limits and other tuning parameters, see Configure for Spark.
You can enable a set of Spark properties that users are permitted to override on individual jobs. For more information, see Enable Spark Job Overrides.
You can also enable user-specific overrides for Spark jobs executed on the cluster.
NOTE: The user-specific overrides take precedence over the Spark settings applied to the output objects.
For more information, see Configure User-Specific Props for Cluster Jobs.