Table of Contents

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  1. Preface
  2. Analyst Service
  3. Catalog Service
  4. Content Management Service
  5. Data Integration Service
  6. Data Integration Service Architecture
  7. Data Integration Service Management
  8. Data Integration Service Grid
  9. Data Integration Service Applications
  10. Interactive Data Preparation Service
  11. Enterprise Data Preparation Service
  12. Informatica Cluster Service
  13. Mass Ingestion Service
  14. Metadata Access Service
  15. Metadata Manager Service
  16. Model Repository Service
  17. PowerCenter Integration Service
  18. PowerCenter Integration Service Architecture
  19. High Availability for the PowerCenter Integration Service
  20. PowerCenter Repository Service
  21. PowerCenter Repository Management
  22. PowerExchange Listener Service
  23. PowerExchange Logger Service
  24. SAP BW Service
  25. Search Service
  26. System Services
  27. Test Data Manager Service
  28. Test Data Warehouse Service
  29. Web Services Hub
  30. Application Service Upgrade
  31. Appendix A: Application Service Databases
  32. Appendix B: Connecting to Databases from Windows
  33. Appendix C: Connecting to Databases
  34. Appendix D: Updating the DynamicSections Parameter of a DB2 Database

Processing Threads

Processing Threads

When the DTM runs mappings, it uses reader, transformation, and writer pipelines that run in parallel to extract, transform, and load data.
The DTM separates a mapping into pipeline stages and uses one reader thread, one transformation stage, and one writer thread to process each stage. Each pipeline stage runs in one of the following threads:
  • Reader thread that controls how the DTM extracts data from the source.
  • Transformation thread that controls how the DTM processes data in the pipeline.
  • Writer thread that controls how the DTM loads data to the target.
Because the pipeline contains three stages, the DTM can process three sets of rows concurrently and optimize mapping performance. For example, while the reader thread processes the third row set, the transformation thread processes the second row set, and the writer thread processes the first row set.
If you have the partitioning option, the Data Integration Service can maximize parallelism for mappings and profiles. When you maximize parallelism, the DTM separates a mapping into pipeline stages and uses multiple threads to process each stage.