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Radu Gheorghe commented on SOLR-15008: -------------------------------------- Thanks for pointing to the optimization, it's nice to know! But I don't think this was the problem. We initially added a query that did match a lot of docs. But it didn't seem to warm up anything. I'm sure there was a (syntax?) error somewhere, but we didn't see anything in the logs or something like that. Plus, copy-pasting the query parameters worked as expected. We eventually added legacy facets and we stopped there, but I thought I should forward this info, just in case this is a different (known?) issue. I could look into it separately. > Avoid building OrdinalMap for each facet > ---------------------------------------- > > Key: SOLR-15008 > URL: https://issues.apache.org/jira/browse/SOLR-15008 > Project: Solr > Issue Type: Improvement > Security Level: Public(Default Security Level. Issues are Public) > Components: Facet Module > Affects Versions: 8.7 > Reporter: Radu Gheorghe > Priority: Major > Labels: performance > Attachments: Screenshot 2020-11-19 at 12.01.55.png, writes_commits.png > > > I'm running against the following scenario: > * [JSON] faceting on a high cardinality field > * few matching documents => few unique values > Yet the query almost always takes a long time. Here's an example taking > almost 4s for ~300 documents and unique values (edited a bit): > > {code:java} > "QTime":3869, > "params":{ > "json":"{\"query\": \"*:*\", > \"filter\": [\"type:test_type\", \"date:[1603670360 TO 1604361599]\", > \"unique_id:49866\"] > \"facet\": > {\"keywords\":{\"type\":\"terms\",\"field\":\"keywords\",\"limit\":20,\"mincount\":20}}}", > "rows":"0"}}, > > "response":{"numFound":333,"start":0,"maxScore":1.0,"numFoundExact":true,"docs":[] > }, > "facets":{ > "count":333, > "keywords":{ > "buckets":[{ > "val":"value1", > "count":124}, > ... > {code} > I did some [profiling with our Sematext > Monitoring|https://sematext.com/docs/monitoring/on-demand-profiling/] and it > points me to OrdinalMap building (see attached screenshot). If I read the > code right, an OrdinalMap is built with every facet. And it's expensive since > there are many unique values in the shard (previously, there we more smaller > shards, making latency better, but this approach doesn't scale for this > particular use-case). > If I'm right up to this point, I see a couple of potential improvements, > [inspired from > Elasticsearch|#search-aggregations-bucket-terms-aggregation-execution-hint]: > # *Keep the OrdinalMap cached until the next softCommit*, so that only the > first query takes the penalty > # *Allow faceting on actual values (a Map) rather than ordinals*, for > situations like the one above where we have few matching documents. We could > potentially auto-detect this scenario (e.g. by configuring a threshold) and > use a Map when there are few documents > I'm curious about what you're thinking: > * would a PR/patch be welcome for any of the two ideas above? > * do you see better options? am I missing something? > -- This message was sent by Atlassian Jira (v8.3.4#803005) --------------------------------------------------------------------- To unsubscribe, e-mail: issues-unsubscr...@lucene.apache.org For additional commands, e-mail: issues-h...@lucene.apache.org