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[ML] Add support for search-time runtime fields to data frame analytics #65056
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Pinging @elastic/ml-core (:ml) |
I am working on this following approach 2: allowing the user to provide search-time runtime fields to the config which are then becoming mapped runtime fields in the destination index. |
dimitris-athanasiou
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Users can now specify runtime mappings as part of the source config of a data frame analytics job. Those runtime mappings become part of the mapping of the destination index. This ensures the fields are accessible in the destination index even if the relevant data frame analytics job gets deleted. Closes #65056
dimitris-athanasiou
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#69284) Users can now specify runtime mappings as part of the source config of a data frame analytics job. Those runtime mappings become part of the mapping of the destination index. This ensures the fields are accessible in the destination index even if the relevant data frame analytics job gets deleted. Closes #65056 Backport of #69183
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Since #64374 Elasticsearch has the option to have search-time runtime fields.
ML should allow these to be used in data frame analytics.
The most obvious way to do it seems to be to add an optional
runtime_mappings
section to the data frame analytics config with the same structure as theruntime_mappings
section of searches (as defined in #64374), then add this into the search the data frame analytics job does when reindexing source data to the destination index.However, after this initial step there is a choice of approaches. For the destination index we could:
Some analysis of the pros and cons is needed before deciding which option is best.
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