Getting Data In

Does anyone have experience with how indexing latency affects accelerated data models and how to handle this?

romedome
Path Finder

Has anyone had any experience on how indexing lag affects accelerated data models and ways to mitigate the issue?

Thanks!

0 Karma
1 Solution

woodcock
Esteemed Legend

It is all handled automatically in a lossless way (unlike Summary Indices). So your only concern, is to not search for (rely on) data that has happened more recently than the max duration of your input + indexer pipeline latency.

View solution in original post

woodcock
Esteemed Legend

It is all handled automatically in a lossless way (unlike Summary Indices). So your only concern, is to not search for (rely on) data that has happened more recently than the max duration of your input + indexer pipeline latency.

romedome
Path Finder

That's reassuring. Is there any documentation that shows how this "losslessness" works?

Thanks!

0 Karma

woodcock
Esteemed Legend

It is because all of the magic happens WHENEVER the event is indexed as PART OF the indexing process. Therefore, it is impossible for the acceleration to be missed, even if event/pipeline latency is very large.

https://helgeklein.com/blog/2015/10/splunk-accelerated-data-models-part-1/
http://docs.splunk.com/Documentation/Splunk/6.4.1/Knowledge/Acceleratedatamodels

romedome
Path Finder

Cool blog post! Thanks!

0 Karma
Get Updates on the Splunk Community!

Introducing the 2024 SplunkTrust!

Hello, Splunk Community! We are beyond thrilled to announce our newest group of SplunkTrust members!  The ...

Introducing the 2024 Splunk MVPs!

We are excited to announce the 2024 cohort of the Splunk MVP program. Splunk MVPs are passionate members of ...

Splunk Custom Visualizations App End of Life

The Splunk Custom Visualizations apps End of Life for SimpleXML will reach end of support on Dec 21, 2024, ...