Table of Contents

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  1. Preface
  2. Working with Transformations
  3. Aggregator Transformation
  4. Custom Transformation
  5. Custom Transformation Functions
  6. Data Masking Transformation
  7. Data Masking Examples
  8. Expression Transformation
  9. External Procedure Transformation
  10. Filter Transformation
  11. HTTP Transformation
  12. Identity Resolution Transformation
  13. Java Transformation
  14. Java Transformation API Reference
  15. Java Expressions
  16. Java Transformation Example
  17. Joiner Transformation
  18. Lookup Transformation
  19. Lookup Caches
  20. Dynamic Lookup Cache
  21. Normalizer Transformation
  22. Rank Transformation
  23. Router Transformation
  24. Sequence Generator Transformation
  25. Sorter Transformation
  26. Source Qualifier Transformation
  27. SQL Transformation
  28. Using the SQL Transformation in a Mapping
  29. Stored Procedure Transformation
  30. Transaction Control Transformation
  31. Union Transformation
  32. Unstructured Data Transformation
  33. Update Strategy Transformation
  34. XML Transformations

Transformation Guide

Transformation Guide

Generating Key Values

Generating Key Values

The Normalizer transformation creates a generated key when the COBOL source contains a group of multiple-occurring columns. You can pass a group of multiple-occurring columns to a different target than the other columns in the row. You can create a primary-foreign key relationship between the targets with the generated key.
The following figure shows a COBOL source definition that contains a multiple-occurring group of columns:
The COBOL source is open and displays the port name, level, occurs, datatype, and length columns.
In this example, the Detail_Suppliers group of columns occurs four times in the Detail_Record.
The Normalizer transformation generates a GK_Detail_Sales key for each source row. The GK_Detail_Sales key represents one Detail_Record source row.
The following figure shows the primary foreign key relationships between the targets:
Two targets are open and display the key types, port name, datatype, and length columns. The first target displays the foreign key in the key types column and the second target displays the primary key in the key types column.
Multiple-occurring Detail_Supplier rows have a foreign key linking them to the same Detail_Sales row. The Detail_Sales target has a one-to-many relationship to the Detail_Suppliers target.
The following figure shows the GK_Detail_Sales generated key connected to primary and foreign keys in the target:
The mapping contains a source, a Normalizer transformation, an Aggregator transformation, and two targets. The targets are open to display the key types and port names. The Normalizer transformation is open to display the port names and datatypes. The source and the Aggregator transformation are iconized.
Pass GK_Detail_Sales to the primary key of Detail_Sales and the foreign key of Detail_Suppliers.
Link the Normalizer output columns to the following objects:
  • Detail_Sales_Target.
    Pass the Detail_Item, Detail_Desc, Detail_Price, and Detail_Qty columns to a Detail_Sales target. Pass the GK_Detail_Sales key to the Detail_Sales primary key.
  • Aggregator Transformation.
    Pass each Detail_Sales row through an Aggregator transformation to remove duplicate rows. The Normalizer returns duplicate Detail_Sales columns for each occurrence of Detail_Suppliers.
  • Detail_Suppliers.
    Pass each instance of the Detail_Suppliers columns to a the Detail_Suppliers target. Pass the GK_Detail_Sales key to the Detail_Suppliers foreign key. Each instance of the Detail_Suppliers columns has a foreign key that relates the Detail_Suppliers row to the Detail_Sales row.

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