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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

Example

Example

You want to use transaction control to write order information based on the order entry date. You want to ensure that all orders entered on any given date are committed to the target in the same transaction. To accomplish this, you can create a mapping with the following transformations:
  • Sorter transformation.
    Sort the source data by order entry date.
  • Expression transformation.
    Use local variables to determine whether the date entered is a new date.
    The following table describes the ports in the Expression transformation:
    Port Name
    Expression
    Description
    DATE_ENTERED
    DATE_ENTERED
    Input/Output port.
    Receives and passes the date entered.
    NEW_DATE
    IIF(DATE_ENTERED=PREVDATE, 0,1)
    Variable port.
    Tests current value for DATE_ENTERED against the stored value for DATE_ENTERED in the variable port, PREV_DATE.
    PREV_DATE
    DATE_ENTERED
    Variable port.
    Receives the value for DATE_ENTERED after the Integration Service evaluates the NEW_DATE port.
    DATE_OUT
    NEW_DATE
    Output port.
    Passes the flag from NEW_DATE to the Transaction Control transformation.
    The Integration Service evaluates ports by dependency. The order in which ports display in a transformation must match the order of evaluation: input ports, variable ports, output ports.
  • Transaction Control transformation.
    Create the following transaction control expression to commit data when the Integration Service encounters a new order entry date:
    IIF(NEW_DATE = 1, TC_COMMIT_BEFORE, TC_CONTINUE_TRANSACTION)
    The following figure shows a sample mapping using a Transaction Control transformation:
    The mapping contains two sources joined to one source qualifier, a Sorter transformation, Expression transformation, Transaction Control transformation, and a target.

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