Table of Contents

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  1. Preface
  2. Transformations
  3. Source transformation
  4. Target transformation
  5. Access Policy transformation
  6. Aggregator transformation
  7. B2B transformation
  8. Chunking transformation
  9. Cleanse transformation
  10. Data Masking transformation
  11. Data Services transformation
  12. Deduplicate transformation
  13. Expression transformation
  14. Filter transformation
  15. Hierarchy Builder transformation
  16. Hierarchy Parser transformation
  17. Hierarchy Processor transformation
  18. Input transformation
  19. Java transformation
  20. Java transformation API reference
  21. Joiner transformation
  22. Labeler transformation
  23. Lookup transformation
  24. Machine Learning transformation
  25. Mapplet transformation
  26. Normalizer transformation
  27. Output transformation
  28. Parse transformation
  29. Python transformation
  30. Rank transformation
  31. Router transformation
  32. Rule Specification transformation
  33. Sequence transformation
  34. Sorter transformation
  35. SQL transformation
  36. Structure Parser transformation
  37. Transaction Control transformation
  38. Union transformation
  39. Vector Embedding transformation
  40. Velocity transformation
  41. Verifier transformation
  42. Web Services transformation

Transformations

Transformations

Creating a Joiner transformation

Creating a Joiner transformation

Use a Joiner transformation to join data from two related heterogenous sources.
Before you create a Joiner transformation, add Source transformations to the mapping to represent source data. Include any other upstream transformations that you want to use.
If the data in the two pipelines include matching field names, rename one set of fields in a transformation upstream from the Joiner transformation.
  1. In the
    Transformation palette
    , drag a Joiner transformation onto the mapping canvas.
  2. Connect an upstream transformation that represents one data set to the Master group of the Joiner transformation.
    To improve job performance, use the transformation that represents the smaller data set.
  3. Connect an upstream transformation that represents the other data set to the Detail group of the Joiner transformation.
  4. On the
    General
    tab, enter a name and optional description for the transformation.
  5. On the
    Incoming Fields
    tab, configure the field rules that define the data that enters the transformation.
  6. On the
    Join Condition
    tab, select the join yype.
  7. To configure a join condition, select Simple for the join condition. Click
    Add New Join Condition
    , and then select the master and detail fields to use and the operator. You can create multiple join conditions.
    Alternatively, to use a parameter for the join condition, select Completely Parameterized for the join condition.
You can add downstream transformations to the mapping and configure them. When the mapping is complete, you can validate and save the mapping.

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