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Table of Contents

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  1. Preface
  2. Working with Transformations
  3. Address Validator Transformation
  4. Aggregator Transformation
  5. Association Transformation
  6. Bad Record Exception Transformation
  7. Case Converter Transformation
  8. Classifier Transformation
  9. Cleanse transformation
  10. Comparison Transformation
  11. Custom Transformation
  12. Custom Transformation Functions
  13. Consolidation Transformation
  14. Data Masking Transformation
  15. Data Masking Examples
  16. Decision Transformation
  17. Duplicate Record Exception Transformation
  18. Dynamic Lookup Cache
  19. Expression Transformation
  20. External Procedure Transformation
  21. Filter Transformation
  22. HTTP Transformation
  23. Identity Resolution Transformation
  24. Java Transformation
  25. Java Transformation API Reference
  26. Java Expressions
  27. Java Transformation Example
  28. Joiner Transformation
  29. Key Generator Transformation
  30. Labeler Transformation
  31. Lookup Transformation
  32. Lookup Caches
  33. Match Transformation
  34. Match Transformations in Field Analysis
  35. Match Transformations in Identity Analysis
  36. Merge Transformation
  37. Normalizer Transformation
  38. Parser Transformation
  39. Rank Transformation
  40. Router Transformation
  41. Sequence Generator Transformation
  42. Sorter Transformation
  43. Source Qualifier Transformation
  44. SQL Transformation
  45. Using the SQL Transformation in a Mapping
  46. Stored Procedure Transformation
  47. Standardizer Transformation
  48. Transaction Control Transformation
  49. Union Transformation
  50. Unstructured Data Transformation
  51. Update Strategy Transformation
  52. Weighted Average Transformation
  53. XML Transformations

Transformation Guide

Transformation Guide

Pattern-Based Parsing Mode

Pattern-Based Parsing Mode

In pattern-based parsing mode, the Parser transformation parses patterns made of multiple strings.
You can use the following methods to define patterns in pattern-based parsing mode:
  • Parse input data using patterns defined in reference tables. You can create a pattern reference table from the profiled output of a Labeler transformation that uses the token labeling mode.
  • Parse input data using patterns that you define.
  • Parse input data using patterns that you import from a reusable pattern set in the Model repository. Changes to the reusable pattern set do not update the data you add in the Parser transformation.
You can use the "
+
" and "
*
" wildcards to define a pattern. Use "
*
" characters to match any string, and "
+
" characters to match one or more instances of the preceding string. For example, use "
WORD+
" to find multiple consecutive instances of a word token, and use "
WORD *
" to find a word token followed by one or more tokens of any type.
You can use multiple instances of these methods within the Parser transformation. The transformation uses the instances in the order in which they are listed on the
Configuration
view.
In pattern-based parsing mode, the Parser transformation requires the output of a Labeler transformation that uses token labeling mode. Create and configure the Labeler transformation before creating a Parser transformation that uses pattern-based parsing mode.

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