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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

Defining a Join Condition

Defining a Join Condition

The join condition contains ports from both input sources that must match for the Integration Service to join two rows. Depending on the type of join selected, the Integration Service either adds the row to the result set or discards the row. The Joiner transformation produces result sets based on the join type, condition, and input data sources.
Before you define a join condition, verify that the master and detail sources are configured for optimal performance. During a session, the Integration Service compares each row of the master source against the detail source. To improve performance for an unsorted Joiner transformation, use the source with fewer rows as the master source. To improve performance for a sorted Joiner transformation, use the source with fewer duplicate key values as the master.
By default, when you add ports to a Joiner transformation, the ports from the first source pipeline display as detail sources. Adding the ports from the second source pipeline sets them as master sources. To change these settings, click the M column on the Ports tab for the ports you want to set as the master source. This sets ports from this source as master ports and ports from the other source as detail ports.
You define one or more conditions based on equality between the specified master and detail sources. For example, if two sources with tables called EMPLOYEE_AGE and EMPLOYEE_POSITION both contain employee ID numbers, the following condition matches rows with employees listed in both sources:
EMP_ID1 = EMP_ID2
Use one or more ports from the input sources of a Joiner transformation in the join condition. Additional ports increase the time necessary to join two sources. The order of the ports in the condition can impact the performance of the Joiner transformation. If you use multiple ports in the join condition, the Integration Service compares the ports in the order you specify.
The Designer validates datatypes in a condition. Both ports in a condition must have the same datatype. If you need to use two ports in the condition with non-matching datatypes, convert the datatypes so they match.
If you join Char and Varchar datatypes, the Integration Service counts any spaces that pad Char values as part of the string:
Char(40) = "abcd" Varchar(40) = "abcd"
The Char value is “abcd” padded with 36 blank spaces, and the Integration Service does not join the two fields because the Char field contains trailing spaces.
The Joiner transformation does not match null values. For example, if both EMP_ID1 and EMP_ID2 contain a row with a null value, the Integration Service does not consider them a match and does not join the two rows. To join rows with null values, replace null input with default values, and then join on the default values.

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