Table of Contents

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  1. Preface
  2. Introduction to Transformations
  3. Transformation Ports
  4. Transformation Caches
  5. Address Validator Transformation
  6. Aggregator Transformation
  7. Association Transformation
  8. Bad Record Exception Transformation
  9. Case Converter Transformation
  10. Classifier Transformation
  11. Comparison Transformation
  12. Consolidation Transformation
  13. Data Masking Transformation
  14. Data Processor Transformation
  15. Decision Transformation
  16. Duplicate Record Exception Transformation
  17. Expression Transformation
  18. Filter Transformation
  19. Hierarchical to Relational Transformation
  20. Java Transformation
  21. Java Transformation API Reference
  22. Java Expressions
  23. Joiner Transformation
  24. Key Generator Transformation
  25. Labeler Transformation
  26. Lookup Transformation
  27. Lookup Caches
  28. Dynamic Lookup Cache
  29. Match Transformation
  30. Match Transformations in Field Analysis
  31. Match Transformations in Identity Analysis
  32. Normalizer Transformation
  33. Merge Transformation
  34. Parser Transformation
  35. Python Transformation
  36. Rank Transformation
  37. Read Transformation
  38. Relational to Hierarchical Transformation
  39. REST Web Service Consumer Transformation
  40. Router Transformation
  41. Sequence Generator Transformation
  42. Sorter Transformation
  43. SQL Transformation
  44. Standardizer Transformation
  45. Union Transformation
  46. Update Strategy Transformation
  47. Web Service Consumer Transformation
  48. Parsing Web Service SOAP Messages
  49. Generating Web Service SOAP Messages
  50. Weighted Average Transformation
  51. Window Transformation
  52. Write Transformation
  53. Appendix A: Transformation Delimiters

Developer Transformation Guide

Developer Transformation Guide

Push-Into Optimization with the SQL Transformation

Push-Into Optimization with the SQL Transformation

With push-into optimization, the Data Integration Service pushes the filter logic from a Filter transformation in the mapping to the query in the SQL transformation.
Use the following rules and guidelines when you enable push-into optimization with the SQL transformation:
  • The transformation SQL query must only contain SELECT statements.
  • The transformation SQL query must be a valid subquery.
  • The filter condition cannot refer to the SQL Error or NumRowsAffected fields.
  • The names of the output ports must match the names of the columns in the SQL SELECT statement. When you reference an output port in a filter condition, the Data Integration Service pushes the corresponding port name to the SQL query. You can add aliases to the SQL if the columns in the query do not match the output port names. For example,
    SELECT mycolname1 AS portname1, mycolname2 AS portname2
    .
  • The transformation cannot have side effects.

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