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

Constraints

Constraints

A constraint is a conditional expression that the values on a data row must satisfy.
When you set a constraint, you enter an expression that evaluates to TRUE for each data row.
The Data Integration Service can read constraints from relational sources, logical data objects, physical data objects, or virtual tables. To set a constraint on a reusable physical data object, create a customized data object.
When the Data Integration Service reads constraints, it might drop the rows that do not evaluate to TRUE for the data rows based on the optimization method applied.
Before you set a constraint, you must verify that the source data satisfies the condition set by the constraint. For example, a source database has an AGE column that appears to have rows with AGE < 70. You can set a constraint with AGE < 70 on the source database. The Data Integration reads records from the source database with the constraint AGE < 70. If the Data Integration Service reads records with AGE >= 70, it might drop the rows with AGE >= 70.
In the database, you can use SQL commands to set constraints on the database environment when you connect to the database. The Data Integration Service runs the connection environment SQL each time it connects to the database.

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