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. 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

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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