Developing for Splunk Enterprise

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

bcyates
Communicator

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

1 Solution

skoelpin
SplunkTrust
SplunkTrust

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

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skoelpin
SplunkTrust
SplunkTrust

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

View solution in original post

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somesoni2
Revered Legend

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_a...

Steps

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