Table of Contents

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  1. Preface
  2. Introduction
  3. Accessing Data Archive
  4. Working with Data Archive
  5. Scheduling Jobs
  6. Viewing the Dashboard
  7. Creating Data Archive Projects
  8. Salesforce Archiving
  9. SAP Application Retirement
  10. Creating Retirement Archive Projects
  11. Integrated Validation for Archive and Retirement Projects
  12. Retention Management
  13. External Attachments
  14. Data Archive Restore
  15. Data Discovery Portal
  16. Data Visualization
  17. Oracle E-Business Suite Retirement Reports
  18. JD Edwards Enterprise Retirement Reports
  19. Oracle PeopleSoft Applications Retirement Reports
  20. Smart Partitioning
  21. Smart Partitioning Data Classifications
  22. Smart Partitioning Segmentation Policies
  23. Smart Partitioning Access Policies
  24. Language Settings
  25. Appendix A: Data Vault Datatype Conversion
  26. Appendix B: Special Characters in Data Vault
  27. Appendix C: SAP Application Retirement Supported HR Clusters
  28. Appendix D: Glossary

Clean Up After Merge Partitions

Clean Up After Merge Partitions

After you run the merge partitions into single partition job, run the clean up after merge partition job. The clean up after merge partitions job drops the empty partitions and tablespaces, and merges the partition metadata.
Only run the clean up job after you have merged all of the segments that you want to merge for a data classification. After you run the clean up after merge partitions job, you cannot replace the merged partitions with the original partitions.
Provide the following information to run this job:
SourceRep
Source connection for the segmentation group. Choose from available source connections.
DataClassificationName
Name of the data classification that contains the segments that you merged. Choose from available data classifications.

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