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

Transformations

Transformations

Structure Parser transformation

Structure Parser transformation

The Structure Parser transformation transforms your input data into a user-defined structured format based on an
intelligent structure model
. You can use the Structure Parser transformation to analyze data such as log files, clickstreams, XML or JSON files, Word tables, and other unstructured or semi-structured formats.
To create an
intelligent structure model
, use
Intelligent Structure Discovery
.
Intelligent Structure Discovery
determines the underlying structure of a sample data file and creates a model of the structure.
Intelligent Structure Discovery
creates the
intelligent structure model
based on a sample of your input data. You can create models from the following input types:
  • Delimited files, for example, CSV files
  • Machine generated files such as weblogs and clickstreams
  • JSON files
  • XML files
  • ORC files
  • Avro files
  • Parquet files
  • Microsoft Excel files
  • Data within PDF form fields
  • Data within Microsoft Word tables
  • XSD files
  • Cobol copybooks
Creating intelligent structure models based on XSD files and on Cobol copybooks is available for preview.
Preview functionality is supported for evaluation purposes but is unwarranted and is not supported in production environments or any environment that you plan to push to production. Informatica intends to include the preview functionality in an upcoming release for production use, but might choose not to in accordance with changing market or technical circumstances. For more information, contact Informatica Global Customer Support.
You can refine the
intelligent structure model
and customize the structure of the output data. You can edit the nodes in the model to combine, exclude, flatten, or collapse them.
The Structure Parser transformation can process input from source transformations efficiently and seamlessly based on the
intelligent structure model
that you select. When you add a Structure Parser transformation to a mapping, you associate it with the
intelligent structure model
.
When you use a Structure Parser transformation in a mapping you can select a Source transformation based on a flat file to process local input files. Or you can select a Source transformation based on a Hadoop Files V2 connection to stream input files in HDFS, using Hortonworks Data Platform or Cloudera connection, or to process input from local file systems.
To use the Structure Parser transformation, you need the appropriate license.