[7.3][ML] Outlier detection should only fetch docs that have the analyzed … #44960
Conversation
This file contains hidden or bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
elastic#44944) As data frame rows with missing values for analyzed fields are skipped, we can be more efficient by including a query that only picks documents that have values for all analyzed fields. Besides improving the number of documents we go through, we also provide a more accurate measurement of how many rows we need which reduces the memory requirements. This also adds an integration test that runs outlier detection on data with missing fields.
Collaborator
|
Pinging @elastic/ml-core |
Contributor
Author
|
@elasticmachine update branch |
…-all-analyzed-fields-7_3
dimitris-athanasiou
deleted the
outlier-detection-should-query-docs-that-have-all-analyzed-fields-7_3
branch
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment
2 participants
Add this suggestion to a batch that can be applied as a single commit.
This suggestion is invalid because no changes were made to the code.
Suggestions cannot be applied while the pull request is closed.
Suggestions cannot be applied while viewing a subset of changes.
Only one suggestion per line can be applied in a batch.
Add this suggestion to a batch that can be applied as a single commit.
Applying suggestions on deleted lines is not supported.
You must change the existing code in this line in order to create a valid suggestion.
Outdated suggestions cannot be applied.
This suggestion has been applied or marked resolved.
Suggestions cannot be applied from pending reviews.
Suggestions cannot be applied on multi-line comments.
Suggestions cannot be applied while the pull request is queued to merge.
Suggestion cannot be applied right now. Please check back later.
…… (#44944)
As data frame rows with missing values for analyzed fields are skipped,
we can be more efficient by including a query that only picks documents
that have values for all analyzed fields. Besides improving the number
of documents we go through, we also provide a more accurate measurement
of how many rows we need which reduces the memory requirements.
This also adds an integration test that runs outlier detection on data
with missing fields.