Table of Contents

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  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

Joiner Transformation in a Streaming Mapping

Joiner Transformation in a Streaming Mapping

Streaming mappings have additional processing rules that do not apply to batch mappings.

Mapping Validation

Mapping validation fails in the following situations:
  • A Joiner transformation is downstream from an Aggregator transformation.
  • A Joiner transformation is downstream from a Rank transformation.
  • A streaming pipeline contains more than one Joiner transformation.
  • A Joiner transformation joins data from streaming and non-streaming pipelines.

General Guidelines

To specify a join condition, select the TIME_RANGE function from the Advanced condition type on the Join tab and enter a join condition expression. The TIME_RANGE function determines the time range for the streaming events to be joined.


Updated September 28, 2020