Table of Contents

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  1. Preface
  2. Introduction to Test Data Management
  3. Test Data Manager
  4. Projects
  5. Policies
  6. Data Discovery
  7. Creating a Data Subset
  8. Performing a Data Masking Operation
  9. Data Masking Techniques and Parameters
  10. Data Generation
  11. Data Generation Techniques and Parameters
  12. Working with Test Data Warehouse
  13. Analyzing Test Data with Data Coverage
  14. Plans and Workflows
  15. Monitor
  16. Reports
  17. ilmcmd
  18. tdwcmd
  19. tdwquery
  20. Appendix A: Data Type Reference
  21. Appendix B: Data Type Reference for Test Data Warehouse
  22. Appendix C: Data Type Reference for Hadoop
  23. Appendix D: Glossary

Sequence Generation

Sequence Generation

A sequence generation rule is a global or ad hoc rule that generates numeric and date values in a sequence.
You select a beginning value and an increment value when you create a sequence generation rule.
When you create a sequence generation rule for a numeric data type, you can choose to start the sequence from the last output value. When you run the plan again, the sequence continues to generate numbers from the previous output value
If you try to generate numbers in a column with string data type and if you choose to start the sequence from the last value, TDM generates values from the beginning when you run the plan again.
The following image shows the sequence generation parameters:
The New Generation Rule dialog box shows the sequence generation parameters for the numeric data type. The sequence generation parameters are start value, increment value, null values, and invalid values.

Sequence Generation Example

You want to generate ticket numbers in ascending order. The target table has a TICKET_NUMBER column. You create a sequence generation rule with the numeric data type. You enter a start value of 1000 and an increment value of one (1).

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