Table of Contents

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  1. Preface
  2. Components
  3. API collections
  4. Business services
  5. File listeners
  6. Fixed-width file formats
  7. Hierarchical schemas
  8. Industry data service customizer
  9. Intelligent structure models
  10. Refining intelligent structure models
  11. Mapplets
  12. Saved queries
  13. Shared sequences
  14. User-defined functions

Components

Components

Using intelligent structure models in mappings

Using
intelligent structure model
s in mappings

To use an
intelligent structure model
in a mapping, add a Structure Parser transformation or a Hierarchy Builder transformation to the mapping.
An
intelligent structure model
is required for Structure Parser transformations and is optional for Hierarchy Builder transformations.
When you configure the transformation, select or create an
intelligent structure model
, select the type of input that the transformation expects to receive, and select the output that you pass to downstream transformations. The model can generate relational, XML, JSON, JSON Lines, or Hadoop format output.
If the output contains data of type DATE,
Intelligent Structure Discovery
represents the data in the mapping as String, not as Date or DateTime.
Models that you use with a Structure Parser transformation in a mapping can contain up to 12,000 fields. The Structure Parser transformation might fail to load models that contain more than 12,000 fields.
When you create a model that isn't JSON, XML, or XSD-based, and the model contains nested repeating groups, you can reduce the number of fields in the model by normalizing the output data.
Intelligent Structure Discovery
normalizes the input data by default for JSON, XML, and XSD-based models that contain nested repeating groups.
For more information about the Structure Parser and Hierarchy Builder transformations, see
Transformations
.

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