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

Java Transformation Overview

Java Transformation Overview

Use the Java transformation to extend Developer tool functionality.
The Java transformation provides a simple native programming interface to define transformation functionality with the Java programming language. You can use the Java transformation to define simple or moderately complex transformation functionality without advanced knowledge of the Java programming language or an external Java development environment. The Java transformation is an active or passive transformation.
The Developer tool uses the Java Development Kit (JDK) to compile the Java code and generate byte code for the transformation. The Developer tool stores the byte code in the Model repository.
The Data Integration Service uses the Java Runtime Environment (JRE) to run generated byte code at run time. When the Data Integration Service runs a mapping with a Java transformation, the Data Integration Service uses the JRE to run the byte code and process input rows and generate output rows.
Create Java transformations by writing Java code snippets that define transformation logic. Define transformation behavior for a Java transformation based on the following events:
  • The transformation receives an input row.
  • The transformation processed all input rows.
In mappings that run on the Spark engine, you can use complex data types in Java transformations to process hierarchical data. With complex data types, the Spark engine directly reads, processes, and writes hierarchical data in Avro, Parquet, and JSON complex files.

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