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[DOCS] Clarify impact of delayed data in anomaly detection (#66816) (#67041) 

Co-authored-by: Benjamin Trent <ben.w.trent@gmail.com>
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Lisa Cawley 2021-01-05 13:15:19 -08:00 committed by GitHub
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docs/reference/ml/anomaly-detection/ml-delayed-data-detection.asciidoc
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@ -2,8 +2,9 @@
[[ml-delayed-data-detection]]
= Handling delayed data
Delayed data are documents that are indexed late. That is to say, it is data
related to a time that the {dfeed} has already processed.
Delayed data are documents that are indexed late. That is to say, it is data
related to a time that your {dfeed} has already processed and it is therefore
never analyzed by your {anomaly-job}.
When you create a {dfeed}, you can specify a
{ref}/ml-put-datafeed.html#ml-put-datafeed-request-body[`query_delay`] setting.
@ -50,4 +51,3 @@ action to consider is to increase the `query_delay` of the datafeed. This
increased delay allows more time for data to be indexed. If you have real-time
constraints, however, an increased delay might not be desirable. In which case,
you would have to {ref}/tune-for-indexing-speed.html[tune for better indexing speed].