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

Filter Condition

Filter Condition

The filter condition is an expression that returns TRUE or FALSE.
Enter conditions in the Expression editor. The filter condition is case sensitive.
You can use any expression that returns a single value as a filter. For example, if you want to filter out rows for employees whose salary is less than or equal to $30,000, enter the following condition:
SALARY > 30000
You can specify multiple components of the condition, using the AND and OR logical operators. If you want to filter out employees who make less than $30,000 and more than $100,000, enter the following condition:
SALARY > 30000 AND SALARY < 100000
You can use ports, parameters, dynamic ports, and generated ports in the filter condition. Select the ports and the parameters in the Expression editor.
If you use a dynamic port in the filter condition, the filter condition expands to include all the generated ports in the dynamic port. For example, the dynamic port, MyDynamicPort, contains three decimal ports:
Salary Bonus Stock
If you configure the following filter condition:
MyDynamicPort > 100
The filter condition expands to the following expression:
Salary > 100 AND Bonus > 100 AND Stock > 100
You can enter a constant for the filter condition. The numeric equivalent of FALSE is zero (0). Any non zero value is the equivalent of TRUE. For example, the transformation contains a port named NUMBER_OF_UNITS with a numeric data type. You configure a filter condition to return FALSE if the value of NUMBER_OF_UNITS equals zero. Otherwise, the condition returns TRUE.
You cannot use a single port selector or dynamic port as a boolean value.
You do not need to specify TRUE or FALSE as values in the expression. TRUE and FALSE are implicit return values from any condition you set. If the filter condition evaluates to NULL, the row is FALSE.

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