Collibra DQ User Guide

Time Based Data Retention

Setup and Configuration
We've moved! To improve customer experience, the Collibra Data Quality User Guide has moved to the Collibra Documentation Center as part of the Collibra Data Quality 2022.11 release. To ensure a seamless transition, will remain accessible, but the DQ User Guide is now maintained exclusively in the Documentation Center.

Setting up Retention Based Data Purge

Retention based purge of data can be turned on to allow data to automatically be cleaned based on an organization's data retention policy.


Once enabled, what type of data is removed?
  • data_preview (Drill-in records for rules, outliers, shapes, etc.)
  • dataset_field (profiling stats)
  • rule_breaks (Rule Exception records)
  • dataset_scan (Job Ledger)


In order to set up retention based data purge, three (3) environment variables need to be set up in the configuration script. Note: a restart of the webapp is required for this configuration to take place.
  • cleaner_retention_enabled
    • TRUE or FALSE on whether this feature is enabled
  • cleaner_retention_days
    • Number of days to retain data
  • cleaner_retention_field
    • Controls which field to use to select eligible dataset runs
    • Potential values
      • updt_ts: consider the last time a dataset run was updated
      • run_id: consider the run id field of the dataset


Example configuration in
Organization wants to purge data where the updt_ts is more than 1 year old
In, add the following lines
export cleaner_retention_enabled=TRUE
export cleaner_retention_days=365
export cleaner_retention_field="updt_ts"

Config Map

autoClean: "false"
cleaner_retention_days: "180"
cleaner_retention_field: updt_ts
cleaner_retention_enabled: "true"

Defaults for Auto Clean Process

This is a separate rolling purge that is distinct from the time-based retention. This is on by default and uses the pre-defined limits below. You will see audit records for this clean-up process in the audit history of the admin console.
Separate from the time-based retention there is also a default auto clean mechanism that actively purges your old records. This is enabled by default and can be modified by use of the autoClean (AUTOCLEAN) boolean parameter.
AUTOCLEAN=false or autoClean="false"
### Depending whether this is part of
### or the configMap of the web pod
These are the defaults. The row count threshold is the global limit when this is triggered. This is based on the records in the data_preview table. The runs threshold and the dataset per row threshold are dataset-level limits that require a dataset to have at least 4 scans and at least 1000 rows.
This is an example using the file to control these settings.
export AUTOCLEAN=true
export DATASETS_PER_ROW=1000
For example (using the settings above):
When data_preivew table has 200k rows Look for datasets with 1000+ rows in data_prevew table And have at least 4 scans Then delete the oldest scan for those datasets
Auto clean and time-based retention run on a routine thread that triggers while the web application is running. It looks for clean-up candidates every few minutes when AUTOCLEAN=true or cleaner_retention_enabled=TRUE.