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

Joining Two Branches of the Same Pipeline

Joining Two Branches of the Same Pipeline

When you join data from the same source, you can create two branches of the pipeline.
When you branch a pipeline, you must add a transformation between the mapping input and the Joiner transformation in at least one branch of the pipeline. You must join sorted data and configure the Joiner transformation for sorted input.
For example, you have a source with the following ports:
  • Employee
  • Department
  • Total Sales
In the target, you want to view the employees who generated sales that were greater than the average sales for their departments. To do this, you create a mapping with the following transformations:
  • Sorter transformation. Sorts the data.
  • Sorted Aggregator transformation. Averages the sales data and group by department. When you perform this aggregation, you lose the data for individual employees. To maintain employee data, you must pass a branch of the pipeline to the Aggregator transformation and pass a branch with the same data to the Joiner transformation to maintain the original data. When you join both branches of the pipeline, you join the aggregated data with the original data.
  • Sorted Joiner transformation. Joins the sorted aggregated data with the original data.
  • Filter transformation. Compares the average sales data against sales data for each employee and filter out employees with less than above average sales.
The mapping example shows a source called Employees_West, a Sorter transformation, a pipeline branch 1 from the Sorter transformation to a Joiner transformation. It shows a second pipeline branch 2 from the Sorter transformation to an Aggregator transformation and then to the Joiner transformation, and a target called T_Employee_Totals.
  1. Employees_West Source
  2. Pipeline branch 1
  3. Pipeline Branch 2
  4. Sorted Joiner transformation
  5. Filter out employees with less than above average sales
Joining two branches might decrease performance if the Joiner transformation receives data from one branch much later than the other branch. The Joiner transformation caches all the data from the first branch and writes the cache to disk if the cache fills. The Joiner transformation must then read the data from disk when it receives the data from the second branch.

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