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: Spark is the default running environment for Hadoop job execution in Release 4.0 and later. Unless you are upgrading from a pre-Release 4.0 environment, no additional configuration is required.
Known Limitations and Issues
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 running environment during Hadoop job execution. In these cases, please execute the job on the Trifacta® Server.
- You cannot publish through Cloudera Navigator for Spark jobs.
Enable Spark Execution 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.
NOTE: If you have upgraded from a pre-Release 4.0 system, your running environment may default to the one defined in your previous release. For more information on enabling, see Running Environment Options.
Use Spark Execution Environment
When Spark execution is enabled, it is available like any other execution environment in the application. When executing a job, select the Run on Hadoop 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.
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