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Table of Contents

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  1. Preface
  2. Working with Transformations
  3. Address Validator Transformation
  4. Aggregator Transformation
  5. Association Transformation
  6. Bad Record Exception Transformation
  7. Case Converter Transformation
  8. Classifier Transformation
  9. Cleanse transformation
  10. Comparison Transformation
  11. Custom Transformation
  12. Custom Transformation Functions
  13. Consolidation Transformation
  14. Data Masking Transformation
  15. Data Masking Examples
  16. Decision Transformation
  17. Duplicate Record Exception Transformation
  18. Dynamic Lookup Cache
  19. Expression Transformation
  20. External Procedure Transformation
  21. Filter Transformation
  22. HTTP Transformation
  23. Identity Resolution Transformation
  24. Java Transformation
  25. Java Transformation API Reference
  26. Java Expressions
  27. Java Transformation Example
  28. Joiner Transformation
  29. Key Generator Transformation
  30. Labeler Transformation
  31. Lookup Transformation
  32. Lookup Caches
  33. Match Transformation
  34. Match Transformations in Field Analysis
  35. Match Transformations in Identity Analysis
  36. Merge Transformation
  37. Normalizer Transformation
  38. Parser Transformation
  39. Rank Transformation
  40. Router Transformation
  41. Sequence Generator Transformation
  42. Sorter Transformation
  43. Source Qualifier Transformation
  44. SQL Transformation
  45. Using the SQL Transformation in a Mapping
  46. Stored Procedure Transformation
  47. Standardizer Transformation
  48. Transaction Control Transformation
  49. Union Transformation
  50. Unstructured Data Transformation
  51. Update Strategy Transformation
  52. Weighted Average Transformation
  53. XML Transformations

Transformation Guide

Transformation Guide

Working with Transactions

Working with Transactions

When the Integration Service processes a Joiner transformation, it can apply transformation logic to all data in a transaction, all incoming data, or one row of data at a time. The Integration Service can drop or preserve transaction boundaries depending on the mapping configuration and the transformation scope. You configure how the Integration Service applies transformation logic and handles transaction boundaries using the transformation scope property.
You configure transformation scope values based on the mapping configuration and whether you want to preserve or drop transaction boundaries.
You can preserve transaction boundaries when you join the following sources:
  • You join two branches of the same source pipeline.
    Use the Transaction transformation scope to preserve transaction boundaries.
  • You join two sources, and you want to preserve transaction boundaries for the detail source.
    Use the Row transformation scope to preserve transaction boundaries in the detail pipeline.
You can drop transaction boundaries when you join the following sources:
  • You join two sources or two branches and you want to drop transaction boundaries
    . Use the All Input transformation scope to apply the transformation logic to all incoming data and drop transaction boundaries for both pipelines.
The following table summarizes how to preserve transaction boundaries using transformation scopes with the Joiner transformation:
Transformation Scope
Input Type
Integration Service Behavior
Row
Unsorted
Preserves transaction boundaries in the detail pipeline.
Row
Sorted
Session fails.
Transaction
Sorted
Preserves transaction boundaries when master and detail originate from the same transaction generator. Session fails when master and detail do not originate from the same transaction generator
Transaction
Unsorted
Session fails.
All Input
Sorted, Unsorted
Drops transaction boundaries.
Sessions fail if you use real-time data with All Input or Transaction transformation scopes.

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