Table of Contents

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

Transformations

Transformations

Partitioning rules and guidelines

Partitioning rules and guidelines

Before you partition a mapping, note the following rules and guidelines:
  • Consider the types of transformations in the mapping and the order in which transformations appear so that you do not get unexpected results. You can partition a mapping if the
    mapping
    task can maintain data consistency when it processes the partitioned data.
  • For flat file partitioning, session performance is optimal with large source files. The load may be unbalanced if the amount of input data is small.
  • When a Sequence Generator transformation is in a mapping with partitioning enabled, ensure that you set up caching in the Sequence Generator transformation. Otherwise, the sequence numbers the task generates for each partition are not consecutive.
  • Sequence numbers generated by Normalizer and Sequence Generator transformations might not be sequential for a partitioned source, but they are unique.
  • When a Sorter transformation is in a mapping with partitioning enabled, the task sorts data in each partition separately.
  • A Sorter transformation must be placed before any Joiner transformation or Aggregator transformation that is configured to use sorted data.
  • You cannot use in-out parameters for key range values.
  • If your mapping has more than eight partitions,
    mapping
    task performance might degrade. You can configure the Buffer Block Size and DTM Buffer Size advanced properties in the
    mapping
    task to improve performance.
  • On Linux, if a target table name includes a unicode character, you need to set the default locale to UTF-8 to support multibyte data. To set the default locale to UTF-8, see the following examples:
    • For bash and related UNIX shells:
      export LC_ALL=en_US.UTF-8
    • For csh and related UNIX shells:
      setenv LC_ALL en_US.UTF-8