Table of Contents

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  1. Preface
  2. Transformations
  3. Source transformation
  4. Target transformation
  5. Access Policy transformation
  6. B2B transformation
  7. Aggregator 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 Generator 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

Editing native data types in complex file sources

Editing native data types in complex file sources

Data Integration
processes native data types in complex file sources differently on an
advanced cluster
and on the Data Integration Server.
On an
advanced cluster
, hierarchical data types such as array, map, and struct are assigned those native types. For example, a map field in an Amazon S3 source might have the native data type "map (string_integer)." You cannot edit the metadata for array, map, or struct fields.
On the Data Integration Server, Data Integration flattens complex hierarchical data types into native string datatypes with precision up to 4000 characters. Some native data types come from the connector, and others come from the parser that
Data Integration
uses when it reads the source data. Parser data types are prefixed with the format type. For example, in an Amazon S3 source with the Avro format, a map field that comes from the parser has the native data type avro_string. You can change the native data type for the connector and parser fields.
To change the native data type, edit the metadata for the source, and select the appropriate data type in the
Native Type
column.
When you change the native data type, you cannot change a non-parser data type to a parser data type. For example, in an Amazon S3 source,
Data Integration
sets the native data type for the FileName field to string. You can change the native data type to nstring but not to avro_string. Similarly, you cannot change a parser data type to a non-parser data type.
For more information about editing native data types in complex file sources, see the help for the appropriate connector.

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