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https://issues.apache.org/jira/browse/SOLR-10528?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Kensho Hirasawa updated SOLR-10528:
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Attachment: SOLR-10528.patch
Attached the first patch. This patch is for branch_6x.
I have implemented just only counting and so the first patch is incomplete.
In our environment (800,000 docs on 4 nodes, 1.5GB heap per node), latency
decreases in all situations.
{code}
# buckets in the whole range = 3 —> original: 22.2ms, patched: 20.5ms
# buckets in the whole range = 1000 —> original: 687ms, patched: 22.6ms
# buckets in the whole range = 1million —> original: OutOfMemoryError,
patched:23.3ms
{code}
However, there are many limitations for now.
- doesn't handle multiValued field
- doesn't handle TrieDate field
- doesn't handle subfacets
- doesn't handle substats
- doesn't handle include/others parameters
- doesn't handle mincount == 0
I am going to remove the above limitations one by one.
> Use docvalue for range faceting in JSON facet API
> -------------------------------------------------
>
> Key: SOLR-10528
> URL: https://issues.apache.org/jira/browse/SOLR-10528
> Project: Solr
> Issue Type: Improvement
> Components: Facet Module
> Affects Versions: 6.5
> Reporter: Kensho Hirasawa
> Priority: Minor
> Attachments: SOLR-10528.patch
>
>
> Range faceting in JSON facet API has only one implementation. In the
> implementation, all buckets are allocated and then range queries are executed
> for all the buckets. Therefore, memory usage and computational cost of range
> facet can be very high if range is wide and gap is narrow.
> I think range faceting in JSON facet should have the implementation which
> uses DocValues instead of inverted indices. By scanning DocValues, we can
> execute range facets much more efficiently especially when the number of
> buckets is large.
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