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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

Dynamic Update Example

Dynamic Update Example

This example shows how to configure an Expression transformation and an SQL transformation to generate SQL queries based on the value of a column in a source file.
In this example, you have a database table that contains product prices. You need to update the prices from a transaction file. Each transaction row updates the wholesale, retail, or manufacturing prices in the database based on a price code column.
The source file is a flat file. You can configure an Expression transformation to return the column names to update based on the value of a price code column in each source row. The Expression transformation passes the column names to the SQL transformation. The SQL transformation runs a dynamic SQL query that updates columns in the Prod_Cost table based on the column names it receives. The SQL transformation returns database errors to the Error_File target.
The following figure shows the how the Expression transformation passes column names to the SQL transformation:
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The mapping contains the following components:
  • PPrices source definition.
    The PPrices flat file contains a product ID, package price, unit price, and price code. The price code defines whether the package price and unit price are wholesale, retail, or manufactured prices.
  • Error_File flat file target definition
    . The target contains the Datastring field that receives database errors from the SQL transformation.
  • Exp_Dynamic_Expression transformation.
    The Expression transformation defines which Prod_Cost column names to update based on the value of the PriceCode column. It returns the column names in the UnitPrice_Query and PkgPrice_Query ports.
  • SQL_Dynamic_Query transformation
    . The SQL transformation has a dynamic SQL query to update a UnitPrice column and a PkgPrice column in the Prod_Cost table. It updates the columns named in the UnitPrice_Query and PkgPrice_Query columns.
The mapping does not contain a relational table definition for the Prod_Cost table
.
The SQL transformation has a static connection to the database that contains the Prod_Cost table. The transformation generates the SQL statements to update the unit prices and package prices in the table.

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