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Table of Contents

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  1. Preface
  2. Transformations
  3. Source transformation
  4. Target transformation
  5. Aggregator transformation
  6. Expression transformation
  7. Filter transformation
  8. Input transformation
  9. Joiner transformation
  10. Lookup transformation
  11. Mapplet transformation
  12. Normalizer transformation
  13. Output transformation
  14. Rank transformation
  15. Router transformation
  16. Sequence transformation
  17. Sorter transformation
  18. SQL transformation
  19. Union transformation

Transformations

Transformations

Join condition

Join condition

The join condition defines when incoming rows are joined. It includes fields from both sources that must match to join source rows.
You define one or more conditions based on equality between the master and detail data. For example, if two sets of employee data contain employee ID numbers, the following condition matches rows with the same employee IDs in both sets of data:
EMP_ID1 = EMP_ID2
Use one or more join conditions. Additional join conditions increase the time necessary to join the data. When you use multiple join conditions, the
mapping
task evaluates the conditions in the order that you specify.
Both fields in a condition must have the same data type. If you need to use two fields with non-matching data types, convert the data types so they match.
For example, when you try to join Char and Varchar data, any spaces that pad Char values are included as part of the string. Both fields might include the value "Shoes," but because the Char(40) field includes 35 trailing spaces, the values do not match. To ensure that the values match, change the data type of one field to match the other.
The Joiner transformation does not match null values. To join rows with null values, you can replace null values with default values, and then join on the default values.

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