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[Percolator] Remove caching and support "now" in range queries #23859

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pickypg opened this issue Mar 31, 2017 · 1 comment
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[Percolator] Remove caching and support "now" in range queries #23859

pickypg opened this issue Mar 31, 2017 · 1 comment
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>enhancement :Search Relevance/Percolator Reverse search: find queries that match a document Team:Search Relevance Meta label for the Search Relevance team in Elasticsearch

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pickypg commented Mar 31, 2017

With the changes to Percolator, we began caching the results of Percolated requests, but this prevents the use of now in range queries / filters.

It was decided to disable caching (for many reasons), which will then allow now to be used by the Percolator.

@pickypg pickypg added :Search Relevance/Percolator Reverse search: find queries that match a document >enhancement labels Mar 31, 2017
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pickypg commented Mar 31, 2017

/cc @clintongormley @martijnvg

If this is a dupe, sorry. I couldn't find anything related. Feel free to fix my description of the issue too.

martijnvg added a commit that referenced this issue Apr 7, 2017
… queries.

Before now ranges where forbidden, because the percolator query itself could get cached and then the percolator queries with now ranges that should no longer match, incorrectly will continue to match.
By disabling caching when the `percolator` is being used, the percolator can now correctly support range queries with now based ranges.

 I think this is the right tradeoff. The percolator query is likely to not be the same between search requests and disabling range queries with now ranges really disabled people using the percolator for their use cases.

 Also fixed an issue that existed in the percolator fieldmapper, it was unable to find forbidden queries inside `dismax` queries.

 Closes #23859
@javanna javanna added the Team:Search Relevance Meta label for the Search Relevance team in Elasticsearch label Jul 12, 2024
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>enhancement :Search Relevance/Percolator Reverse search: find queries that match a document Team:Search Relevance Meta label for the Search Relevance team in Elasticsearch
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