Table of Contents


  1. Preface
  2. Introduction to Informatica Data Engineering Integration
  3. Mappings
  4. Mapping Optimization
  5. Sources
  6. Targets
  7. Transformations
  8. Python Transformation
  9. Data Preview
  10. Cluster Workflows
  11. Profiles
  12. Monitoring
  13. Hierarchical Data Processing
  14. Hierarchical Data Processing Configuration
  15. Hierarchical Data Processing with Schema Changes
  16. Intelligent Structure Models
  17. Blockchain
  18. Stateful Computing
  19. Appendix A: Connections Reference
  20. Appendix B: Data Type Reference
  21. Appendix C: Function Reference

Processing Data on Partitions

Processing Data on Partitions

You can run a Model repository mapping with partitioning to increase performance. When you run a mapping configured with partitioning, the Data Integration Service performs the extract, transformation, and load for each partition in parallel.
Mappings that process large data sets can take a long time to process and can cause low data throughput. When you configure partitioning, the Data Integration Service uses additional threads to process the session or mapping which can increase performance.
If the nodes where mappings run have multiple CPUs, you can enable the Data Integration Service to maximize parallelism when it runs mappings. When you maximize parallelism, the Data Integration Service dynamically divides the underlying data into partitions and processes all of the partitions concurrently.
Optionally, developers can set a maximum parallelism value for a mapping in the Developer tool. By default, the maximum parallelism for each mapping is set to Auto. Each mapping uses the maximum parallelism value defined for the Data Integration Service. Developers can change the maximum parallelism value in the mapping run-time properties to define a maximum value for a particular mapping. When maximum parallelism is set to different integer values for the Data Integration Service and the mapping, the Data Integration Service uses the minimum value.
For more information, see the
Informatica Application Services Guide
and the
Informatica Developer Mapping Guide


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