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Table of Contents

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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

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Match Mapping Performance

Match Mapping Performance

You can preview the data factors that determine the performance of the Match transformation before you run the mapping that contains the transformation. You can verify that the system has the resources to run the mapping. You can also verify that you configured the transformation correctly to measure the levels of similarity in the input data.
Use the
Match Performance Analysis
 option to verify that the system has the required resources. Use the
Match Cluster Analysis
 option to verify that the mapping can accurately measure the levels of similarity in the input data.
Run match performance analysis and match cluster analysis on any Match transformation that reads a single data source. Run match performance analysis on any Match transformation that performs dual-source field match analysis. Do not run match performance analysis or match cluster analysis on an identity match strategy that connects to index tables.

Drill-down on Match Performance Analysis

You can drill down on the match analysis data to view the record pairs that meet or exceed the match threshold. Double-click a record in the
Details
 view, and use the Data Viewer to view the records that match the record that you select. The Data Viewer displays the data for each pair of records on a single row. The row contains the row identifier of each record in the pair.

Drill-down on Match Cluster Analysis

You can drill down on the cluster analysis data to view the records in each cluster. Double-click a cluster in the
Details
 view and read the data in the Data Viewer. The Data Viewer displays one cluster at a time. The cluster data includes the score options that you selected, such as the driver score, link score, driver identifier, or link identifier.

Match Transformation Logging

When you run a mapping that uses a Match transformation, the Developer tool log tracks the number of comparison calculations that the mapping performs. To view the log data, select the
Show Log
 option in the Data Viewer.
The mapping updates the log every 100,000 calculations.
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