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

Filter transformation

Filter transformation

The Filter transformation filters data out of the data flow based on a specified filter condition. To improve job performance, place the Filter transformation close to mapping sources to remove unnecessary data from the data flow.
A filter condition is an expression that returns TRUE or FALSE. When the filter condition returns TRUE for a row, the Filter transformation passes the row to the rest of the data flow. When the filter condition returns FALSE, the Filter transformation drops the row.
You can filter data based on one or more conditions. For example, to work with data within a data range, you can create conditions to remove data before and after specified dates.
Link a single transformation to the Filter transformation. You cannot merge transformations into the Filter transformation.