topic Re: Can python fill_summary_index.py be used to backfill an accelerated data model in Splunk Dev

Can python fill_summary_index.py be used to backfill an accelerated data model

bcyates — Tue, 29 Sep 2020 20:48:54 GMT

We have a multisite cluster where the primary site is getting physically reloacted to a new datacenter. There will bbe about a 12 hour gap in our accelerated data models.

Is it possible to backfill the data models without having to do a full rebuild? I found python fill_summary_index.py in docs, but it is not clear if this works on data models. Docs on specifies saved searches

Re: Can python fill_summary_index.py be used to backfill an accelerated data model

somesoni2 — Tue, 29 Sep 2020 20:48:56 GMT

The fill_summary_index.py script is to backup summary index data which is being populated by a scheduled saved search. To rebuild accelerated data models, follow steps from below link

http://docs.splunk.com/Documentation/Splunk/7.1.2/Knowledge/Managedatamodels#Rebuild_a_summary_for_an_accelerated_data_model

Steps

In Splunk Web, go to the Data Models management page.
Find the accelerated data model that needs to have its summary rebuilt, and expand its row.
Click Rebuild. The summary will begin rebuilding.
(Optional) Check the Status of the summary to find out when it is complete.

Re: Can python fill_summary_index.py be used to backfill an accelerated data model

skoelpin — Wed, 08 Aug 2018 18:40:57 GMT

Accelerated data models work off data in the summary range. The summary range is defined when you accelerate the data model and rebuilds every 5 minutes.. You cannot backfill a data model, you have to rebuild it. if you were using a summary index then yes, you could backfill it