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

Transformations

Transformations

Rules and guidelines for query processing

Rules and guidelines for query processing

Use the following rules and guidelines when you configure the SQL transformation to process a query:
  • The number and the order of the output fields must match the number and order of the fields in the query SELECT clause.
  • The native data type of an output field in the transformation must match the data type of the corresponding column in the database.
    Data Integration
    generates a row error when the data types do not match.
  • When the SQL query contains an INSERT, UPDATE, or DELETE clause, the transformation returns data to the SQLError field, the pass-through fields, and the NumRowsAffected field when it is enabled. If you add output fields, the fields receive NULL data values.
  • When the SQL query contains a SELECT statement and the transformation has a pass-through field, the transformation returns data to the pass-through field whether or not the query returns database data. The SQL transformation returns a row with NULL data in the output fields.
  • When the number of output fields is more than the number of columns in the SELECT clause, the extra fields receive a NULL value.
  • When the number of output fields is less than the number of columns in the SELECT clause,
    Data Integration
    generates a row error.
  • You can use string substitution instead of parameter binding in a query. However, the input fields must be string data types.

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