Configure a Precisely Agent pipeline engine - Precisely Data Integrity Suite

Data Integrity Suite

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Spatial_Analytics
Data_Integration
Data_Enrichment
Data_Governance
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Data_Observability
Data_Quality
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Services
Spatial Analytics
Data Integration
Data Enrichment
Data Governance
Geo Addressing
Data Observability
Data Quality
Core Foundation
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Data Integrity Suite
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2000
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2026

Configure a Precisely Agent pipeline engine to run quality pipelines on-premises. This is useful when you work with local databases that cannot access cloud environments or when you want to run pipelines within a JDBC Agent-enabled private environment.

Before you configure a Precisely Agent pipeline engine, ensure that you have set up your Agent and configured it properly.

Note: To run a data quality pipeline on-premises using an Oracle connection, contact Precisely to set up your Agent on your Virtual Machine and to download the new version of the Oracle driver.

When you configure a Precisely Agent pipeline engine, you specify the agent, driver memory, executor settings, and optional Spark properties to optimize performance for your on-premises workloads.

  1. In the Pipeline engine name field, enter a meaningful name for the pipeline engine.
  2. Verify that Type is set to Precisely Agent.
  3. In the Agent dropdown, select the agent you want to use.
    What's changed: In the new user experience, Agent appears as Precisely Agent. For more information on the new experience, see About the new user experience.
    Only registered agents are listed, regardless of their status. Agents that are created but not registered do not appear in the list.
  4. In the Driver memory field, specify the amount of memory that will be used by the driver.
    The default value is 1 GB. The minimum value must be an integer greater than or equal to 1.
  5. In the Number of executors field, specify the number of executors that will be used by the pipeline engine.
    Each executor represents a separate unit of work that can run in parallel. More executors allow more concurrent tasks to execute, which can improve performance. The default value is 1. The minimum value must be an integer greater than or equal to 1.
  6. In the Executor memory field, specify the amount of memory that will be allocated to each worker.
    This memory is used to store data and intermediate results during pipeline execution. The default value is 3 GB. The minimum value must be an integer greater than or equal to 1. The value must be greater than or equal to 128 MB but less than or equal to 20,000 MB. For Gigabytes, the value must be greater than or equal to 1 GB but less than or equal to 20 GB.
  7. In the Executor cores field, specify the number of CPU cores that will be allocated to each worker.
    This determines the number of concurrent tasks that can be executed by each worker. The default value is 3. The minimum value must be an integer greater than or equal to 1.
  8. In Spark properties, click Add Property to add key-value pairs that determine compute, memory, and disk resources for Agent batch workloads.
    For example, spark.driver.cores with a value of 8. For more information, see Spark Properties in the Apache Spark documentation.
  9. Click Create or Save.
    The Precisely Agent pipeline engine is configured and ready to use in run configurations.

Suggested Spark properties to reduce disk usage

Consider implementing the following Spark properties to help minimize disk requirements during on-premises agent profile executions:

  • spark.shuffle.compress: Set to true
  • spark.shuffle.spill.compress: Set to true
  • spark.io.compression.codec: Use zstd
  • spark.io.compression.zstd.level: Set to 3

Enabling these properties ensures that data written to disk during Spark jobs is compressed, effectively reducing overall disk usage.