Cleaning up old data to improve performance

Some tables in Hue retain data indefinitely resulting in slower performance or application crashes. Hue does not automatically clean up data from these tables. You can configure Hue to retain the data for a specific number of days and then schedule a cron job to clean up these tables at regular intervals for improved performance.

Consider cleaning up old data from the backend Hue database if you face the following problems while using Hue:
  • Upgrade times out
  • Performance is slower than expected
  • Long time to log in to Hue
  • SQL query shows a large number of documents in tables
  • Hue crashes while trying to access saved documents
Back up your database before starting the cleanup activity. Check the saved documents such as Queries and Workflows for a few users to prevent data loss. You can also note the sizes of the tables you want to clean up as a reference by running the following queries:
select count(*) from desktop_document;
select count(*) from desktop_document2;
select count(*) from beeswax_session;
select count(*) from beeswax_savedquery;
select count(*) from beeswax_queryhistory;
select count(*) from oozie_job;
  1. SSH into an active Hue instance.
  2. Change to the Hue home directory:
    cd /opt/cloudera/parcels/CDH/lib/hue
  3. Run the following command as the root user:
    ./build/env/bin/hue desktop_document_cleanup --keep-days x --cm-managed
    The --keep-days property is used to specify the number of days for which Hue will retain the data in the backend database.
    (Optional) Specify DESKTOP_DEBUG=True if you want to log information for troubleshooting purposes.
    DESKTOP_DEBUG=True ./build/env/bin/hue desktop_document_cleanup --keep-days 30 --cm-managed
    In this case, Hue will retain data for 30 days.
    The logs are displayed on the console because DESKTOP_DEBUG is set to True. Alternatively, you can view the logs from the following location:
    The first run can typically take around 1 minute per 1000 entries in each table.
  4. Check whether the table size has decreased by running a query as follows:
    select count(*) from desktop_document;
    If the desktop_document_cleanup command has run successfully, the table size should decrease.
Set up a cron job that runs at regular intervals to automate the database cleanup. For example, you can set up a cron job to run daily and it purges data older than x number of days.