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https://issues.apache.org/jira/browse/LUCENE-4602?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=13554112#comment-13554112
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Michael McCandless commented on LUCENE-4602:
--------------------------------------------
I tested this with Wikipedia (avg ~25 ords per doc across 9 dimensions; 2.5M
unique ords):
{noformat}
Task QPS base StdDev QPS comp StdDev
Pct diff
PKLookup 188.75 (5.3%) 195.05 (2.1%) 3.3% ( -3% -
11%)
HighTerm 3.26 (0.8%) 3.80 (3.4%) 16.3% ( 12% -
20%)
MedTerm 6.85 (0.8%) 9.14 (3.1%) 33.4% ( 29% -
37%)
LowTerm 14.45 (1.5%) 24.41 (2.1%) 68.9% ( 64% -
73%)
{noformat}
Nice!
It's odd how the pctg gains are the same for High/Med/LowTerm ... not sure why.
> Use DocValues to store per-doc facet ord
> ----------------------------------------
>
> Key: LUCENE-4602
> URL: https://issues.apache.org/jira/browse/LUCENE-4602
> Project: Lucene - Core
> Issue Type: Improvement
> Components: modules/facet
> Reporter: Michael McCandless
> Attachments: FacetsPayloadMigrationReader.java, LUCENE-4602.patch,
> LUCENE-4602.patch, LUCENE-4602.patch, LUCENE-4602.patch,
> TestFacetsPayloadMigrationReader.java
>
>
> Spinoff from LUCENE-4600
> DocValues can be used to hold the byte[] encoding all facet ords for
> the document, instead of payloads. I made a hacked up approximation
> of in-RAM DV (see CachedCountingFacetsCollector in the patch) and the
> gains were somewhat surprisingly large:
> {noformat}
> Task QPS base StdDev QPS comp StdDev
> Pct diff
> HighTerm 0.53 (0.9%) 1.00 (2.5%)
> 87.3% ( 83% - 91%)
> LowTerm 7.59 (0.6%) 26.75 (12.9%)
> 252.6% ( 237% - 267%)
> MedTerm 3.35 (0.7%) 12.71 (9.0%)
> 279.8% ( 268% - 291%)
> {noformat}
> I didn't think payloads were THAT slow; I think it must be the advance
> implementation?
> We need to separately test on-disk DV to make sure it's at least
> on-par with payloads (but hopefully faster) and if so ... we should
> cutover facets to using DV.
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