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Table of Contents

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  1. Preface
  2. Working with Transformations
  3. Address Validator Transformation
  4. Aggregator Transformation
  5. Association Transformation
  6. Bad Record Exception Transformation
  7. Case Converter Transformation
  8. Classifier Transformation
  9. Cleanse transformation
  10. Comparison Transformation
  11. Custom Transformation
  12. Custom Transformation Functions
  13. Consolidation Transformation
  14. Data Masking Transformation
  15. Data Masking Examples
  16. Decision Transformation
  17. Duplicate Record Exception Transformation
  18. Dynamic Lookup Cache
  19. Expression Transformation
  20. External Procedure Transformation
  21. Filter Transformation
  22. HTTP Transformation
  23. Identity Resolution Transformation
  24. Java Transformation
  25. Java Transformation API Reference
  26. Java Expressions
  27. Java Transformation Example
  28. Joiner Transformation
  29. Key Generator Transformation
  30. Labeler Transformation
  31. Lookup Transformation
  32. Lookup Caches
  33. Match Transformation
  34. Match Transformations in Field Analysis
  35. Match Transformations in Identity Analysis
  36. Merge Transformation
  37. Normalizer Transformation
  38. Parser Transformation
  39. Rank Transformation
  40. Router Transformation
  41. Sequence Generator Transformation
  42. Sorter Transformation
  43. Source Qualifier Transformation
  44. SQL Transformation
  45. Using the SQL Transformation in a Mapping
  46. Stored Procedure Transformation
  47. Standardizer Transformation
  48. Transaction Control Transformation
  49. Union Transformation
  50. Unstructured Data Transformation
  51. Update Strategy Transformation
  52. Weighted Average Transformation
  53. XML Transformations

Transformation Guide

Transformation Guide

Store Values Across Rows

Store Values Across Rows

You can configure variables in transformations to store data from source rows. You can use the variables in transformation expressions.
For example, a source file contains the following rows:
California California California Hawaii Hawaii New Mexico New Mexico New Mexico
Each row contains a state. You need to count the number of rows and return the row count for each state:
California,3 Hawaii ,2 New Mexico,3
You can configure an Aggregator transformation to group the source rows by state and count the number of rows in each group. Configure a variable in the Aggregator transformation to store the row count. Define another variable to store the state name from the previous row.
The Aggregator transformation has the following ports:
Port
Port Type
Expression
Description
State
Pass-through
n/a
The name of a state. The source rows are grouped by the state name. The Aggregator transformation returns one row for each state.
State_Count
Variable
IIF (PREVIOUS_STATE = STATE, STATE_COUNT +1, 1)
The row count for the current State. When the value of the current State column is the same as the Previous_State column, the Integration Service increments State_Count. Otherwise, it resets the State_Count to 1.
Previous_State
Variable
State
The value of the State column in the previous row. When the Integration Service processes a row, it moves the State value to Previous_State.
State_Counter
Output
State_Count
The number of rows the Aggregator transformation processed for a state. The Integration Service returns State_Counter once for each state.

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