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. Chunking transformation
  9. Cleanse transformation
  10. Data Masking transformation
  11. Data Services transformation
  12. Deduplicate transformation
  13. Expression transformation
  14. Filter transformation
  15. Hierarchy Builder transformation
  16. Hierarchy Parser transformation
  17. Hierarchy Processor transformation
  18. Input transformation
  19. Java transformation
  20. Java transformation API reference
  21. Joiner transformation
  22. Labeler transformation
  23. Lookup transformation
  24. Machine Learning transformation
  25. Mapplet transformation
  26. Normalizer transformation
  27. Output transformation
  28. Parse transformation
  29. Python transformation
  30. Rank transformation
  31. Router transformation
  32. Rule Specification transformation
  33. Sequence transformation
  34. Sorter transformation
  35. SQL transformation
  36. Structure Parser transformation
  37. Transaction Control transformation
  38. Union transformation
  39. Vector Embedding transformation
  40. Velocity transformation
  41. Verifier transformation
  42. 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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