Table of Contents

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  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

SQL Transformation Overview

SQL Transformation Overview

The SQL transformation processes SQL queries midstream in a mapping. You can run SQL queries from the SQL transformation or you can configure the SQL transformation to run stored procedures from a database.
You can pass input port values to parameters in the query or stored procedure. The transformation can insert, delete, update, and retrieve rows from a database. You can run SQL DDL statements to create a table or drop a table midstream in a mapping. The SQL transformation is an active transformation. The transformation can return multiple rows for each input row.
You can import a stored procedure from a database to the SQL transformation. When you import the stored procedure, the Developer tool creates the transformation ports that correspond to the parameters in the stored procedure. The Developer tool also creates the stored procedure call for you.
To configure an SQL transformation to run a stored procedure, perform the following tasks:
  1. Define the transformation properties including the database type to connect to.
  2. Import a stored procedure to define the ports and create the stored procedure call.
  3. Manually define ports for result sets or additional stored procedures that you need to run.
  4. Add the additional stored procedure calls in the SQL Editor.
You can configure an SQL query in the transformation SQL Editor. When you run the SQL transformation, the transformation processes the query, returns rows, and returns any database error.
To configure an SQL transformation to run a query, perform the following tasks:
  1. Define the transformation properties including the database type to connect to.
  2. Define the input and output ports.
  3. Create an SQL query in the SQL Editor.
After you configure the transformation, configure the SQL transformation in a mapping and connect the upstream ports. Preview the data to verify the results.

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