Table of Contents

Search

  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. Match Transformation
  30. Match Transformations in Field Analysis
  31. Match Transformations in Identity Analysis
  32. Normalizer Transformation
  33. Merge Transformation
  34. Parser Transformation
  35. Python Transformation
  36. Rank Transformation
  37. Read Transformation
  38. Relational to Hierarchical Transformation
  39. REST Web Service Consumer Transformation
  40. Router Transformation
  41. Sequence Generator Transformation
  42. Sorter Transformation
  43. SQL Transformation
  44. Standardizer Transformation
  45. Union Transformation
  46. Update Strategy Transformation
  47. Web Service Consumer Transformation
  48. Parsing Web Service SOAP Messages
  49. Generating Web Service SOAP Messages
  50. Weighted Average Transformation
  51. Window Transformation
  52. Write Transformation
  53. Appendix A: Transformation Delimiters

Developer Transformation Guide

Developer Transformation Guide

Aggregator Transformation Overview

Aggregator Transformation Overview

Configure an Aggregator transformation to perform aggregate calculations, such as averages and sums, against groups of data. You can use an Aggregator transformation to remove duplicate rows. The Aggregator transformation is an active transformation.
The Aggregator transformation is different from the Expression transformation because you can configure the Aggregator transformation to perform calculations on groups of data. An Expression transformation returns a result on a row by row basis.
For example, you can calculate the average salary for employees in each department of a organization. Configure a group by department number. Configure an expression to calculate the average salary and to return the result for each unique department number.
Use the transformation language to create aggregate expressions.
The Data Integration Service performs aggregate calculations as it reads data and stores the data in an aggregate cache. You can sort the input data to increase performance. The Data Integration Service does not create the cache if you sort the input data.

0 COMMENTS

We’d like to hear from you!