Table of Contents

Search

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

0 COMMENTS

We’d like to hear from you!