LinkedIn
Copied!

Table of Contents

Case archiving and purging overview

Version:

Only available versions of this content are shown in the dropdown

Use case archiving to archive and purge cases to improve the performance of your cloud-based instance of Pega Platform. Understand how case archiving and purge works to effectively plan and perform case archiving and purge.

Case hierarchy requirements for case archiving and purge

Case hierarchy requirements fall under the following categories of case structures:
Stand-alone case
This type of case contains neither a child nor a parent with a corresponding case type that uses an archival policy. You must set an archival policy on the corresponding case type. Pega Platform can archive stand-alone cases if the case has been resolved for at least as long as the archival policy.
Case hierarchy
This category is a case unit that contains parent cases, child cases, or both. Pega Platform performs a case archival policy on the entire hierarchy. You must set an archival policy for the top-level case. The case type of the top-level case of the hierarchy determines the archival policy of the whole hierarchy. Pega Platform can archive all cases in the hierarchy if they meet the following conditions:
  • The top-level case has been resolved for at least as long as its archival policy.
  • All sub-level parent and child cases are resolved:
    • Sub-level parent and child cases do not need to have an archival policy defined.
    • Sub-level parent and child cases can be resolved anytime before the archival job.

If the case structure does not meet these conditions, the archival job cannot process that case structure.

Examine an application with the following case types:
Top-level case type Archival policy
ServiceRequest (S prefix) 1 year
Job (J prefix) 6 months
TASKS (Task prefix) 3 months

In the following examples, all cases are archived if they meet the specified conditions:

Case hierarchy with sub-level parent and child cases

Case hierarchy with sub-level child cases

Stand-alone case

Artifacts that are archived during an archival process

The process archives certain artifacts within a case. The following table shows the artifacts that Pega Platform can archive:

Artifacts that are archived in Pega Platform

Archived artifacts Non-archived artifacts
  • Child cases
  • Declarative indexes
  • Work history
  • Pulse replies, including link attachments
  • Attachments
    If an attachment is shared between two cases and both cases are not archived, the shared attachment will not be archived.
  • Ad hoc subcases
  • Bookmarked messages
  • Custom associations
  • Documents
  • Followed users
  • Liked messages
  • Links to folders
  • Links to top cases
  • Social reference
  • Tags
  • Workbaskets
  • Worklists

Case archiving process

To archive cases, Pega Platform uses different jobs that you set up through Job Schedulers to copy, index, and purge specific artifacts in stand-alone cases and case hierarchies.

Case archiving pipeline

Pega Platform uses the following jobs during the archive process:

Archive and purge jobs and processes

Job Scheduler Implementation and description
pyPegaArchiver

The pyPegaArchiver Job Scheduler (default short description: Archival_Copier) copies files to Pega Cloud File Storage through the following steps

  1. The job uses a crawler to identify in bulk cases that are eligible for archiving.
  2. The crawler adds the cases to the archiving pipeline.
  3. The crawler validates the resolution of all subcases.
  4. The job copies the cases and their artifacts to Pega Cloud File Storage.
pyPegaIndexer The pyPegaIndexer Job Scheduler (default short description: Archival_Indexer) indexes the copied files into Elasticsearch. The index keeps the association between an archived case and its archived file in Pega Cloud File Storage.
pyPegaPurger The pyPegaPurger Job Scheduler (default short description: Archival_Purger) deletes cases and their associated data from the primary database. The job also integrates a SQL VACUUM command to process deleted space and reclaim the irrelevant empty database tables.
Optional: pyArchival_ReIndexer The Archival_ReIndexer (default short description: Archival_ReIndexer) Job Scheduler fixes corrupted Elasticsearch indexes. This job follows a case archival and purge job when trying to fix case archives.

    100% found this useful

    Have a question? Get answers now.

    Visit the Collaboration Center to ask questions, engage in discussions, share ideas, and help others.