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  1. Preface
  2. Introduction to Transformations
  3. Transformation Ports
  4. Transformation Caches
  5. Address Validator Transformation
  6. Aggregator Transformation
  7. Association Transformation
  8. Bad Record Exception Transformation
  9. Case Converter Transformation
  10. Classifier Transformation
  11. Comparison Transformation
  12. Consolidation Transformation
  13. Data Masking Transformation
  14. Data Processor Transformation
  15. Decision Transformation
  16. Duplicate Record Exception Transformation
  17. Expression Transformation
  18. Filter Transformation
  19. Hierarchical to Relational Transformation
  20. Java Transformation
  21. Java Transformation API Reference
  22. Java Expressions
  23. Joiner Transformation
  24. Key Generator Transformation
  25. Labeler Transformation
  26. Lookup Transformation
  27. Lookup Caches
  28. Dynamic Lookup Cache
  29. Macro Transformation
  30. Match Transformation
  31. Match Transformations in Field Analysis
  32. Match Transformations in Identity Analysis
  33. Normalizer Transformation
  34. Merge Transformation
  35. Parser Transformation
  36. Python Transformation
  37. Rank Transformation
  38. Read Transformation
  39. Relational to Hierarchical Transformation
  40. REST Web Service Consumer Transformation
  41. Router Transformation
  42. Sequence Generator Transformation
  43. Sorter Transformation
  44. SQL Transformation
  45. Standardizer Transformation
  46. Union Transformation
  47. Update Strategy Transformation
  48. Web Service Consumer Transformation
  49. Parsing Web Service SOAP Messages
  50. Generating Web Service SOAP Messages
  51. Weighted Average Transformation
  52. Window Transformation
  53. Write Transformation
  54. Appendix A: Transformation Delimiters

Developer Transformation Guide

Developer Transformation Guide

Identity Match Advanced Properties

Identity Match Advanced Properties

The transformation includes advanced properties that determine the number of execution instances, whether the transformation analyzes identical rows, and the tracing level for log data.
You can configure the following advanced properties:
Execution Instances
Specifies the number of threads that the Data Integration Service tries to create for the current transformation at run time. The Data Integration Service considers the Execution Instances value if you override the Maximum Parallelism run-time property on the mapping that contains the transformation. The default Execution Instances value is Auto.
The Data Integration Service considers multiple factors to determine the number of threads to assign to the transformation. The principal factors are the Execution Instances value and the values on the mapping and on the associated application services in the domain.
The Data Integration Service that runs the mapping reads the following values to determine the number of threads to use for the transformation:
  • The
    Maximum Parallelism
    value on the Data Integration Service. Default is 1.
  • Any
    Maximum Parallelism
    value that you set at the mapping level. Default is Auto.
  • The
    Execution Instances
    value on the transformation. Default is Auto.
If you override the Maximum Parallelism value at the mapping level, the Data Integration Service attempts to use the lowest value across the properties to determine the number of threads.
If you use the default Maximum Parallelism value at the mapping level, the Data Integration Service ignores the Execution Instances value.
Consider the following rules and guidelines when you set the number of execution instances:
  • Multiple users might run concurrent mappings on a Data Integration Service. To calculate the correct number of threads, divide the number of central processing units that the Data Integration Service can access by the number of concurrent mappings.
  • When you use the default Execution Instances value and the default Maximum Parallelism values, the transformation operations are not partitionable.
Filter Exact Match
Determines whether the transformation applies the comparison algorithm in a match strategy to pairs of identical records in the input data.
When the transformation finds a pair of identical records, the algorithm does not need to analyze the levels of similarity between the records. The transformation can pass the records directly to the output stage without additional analysis. To configure the transformation to pass the identical records directly to the output stage, select Filter Exact Match. When the input data contains many identical rows, the comparison algorithm performs fewer calculations, and the mapping runs faster.
Select the option when the input data contains many identical rows. Do not select the option if the input data does not contain many identical rows, as the transformation might run more slowly.
The transformation output contains the same record data when you select or clear the option. The transformation might assign different link scores and driver scores to the output records when you select and clear the option.
Tracing Level
Amount of detail that appears in the log for this transformation. You can choose terse, normal, verbose initialization, or verbose data. Default is normal.

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