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https://issues.apache.org/jira/browse/LUCENE-9378?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17140163#comment-17140163
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Alex Klibisz commented on LUCENE-9378:
--------------------------------------
[~jpountz] It's about 2x slower.
I re-ran a benchmark to be sure. Here is the setup:
* Storing a corpus of 18K binary vectors in a single shard.
* Each vector contains ~500 ints denoting the positive indices. So each one is
storing a bytearray of 500 * 4 = 2000 bytes in the binary doc values.
* Running 2000 serial searches against these vectors. Each search reads,
deserializes, and computes the Jaccard similarity against every vector in the
corpus. So a total of 18K * 2K reads from the shard.
* The read order is defined by Elasticsearch. Internally I'm using a
FunctionScoreQuery, code here:
[https://github.com/alexklibisz/elastiknn/blob/5246a26f76791362482a98066e31071cb03e0a74/plugin/src/main/scala/com/klibisz/elastiknn/query/ExactQuery.scala#L22-L29]
* Ubuntu 20 on an Intel i7-8750H 2.20GHz x 12cores
* Running Oracle Jdk 14 :
```
$ java -version
java version "14" 2020-03-17
Java(TM) SE Runtime Environment (build 14+36-1461)
Java HotSpot(TM) 64-Bit Server VM (build 14+36-1461, mixed mode, sharing)
```
* Running all 2000 searches once, then again, and reporting the time from
second run (JVM warmup, etc.).
Results:
* Using Elasticsearch 7.6.2 w/ Lucene 8.4.0:
** 212 seconds for 2000 searches
** Search threads spend 95.5% of time computing similarities, 0.2% in the
LZ4.decompress() method.
* Using Elasticsearch 7.7.1 w/ Lucene 8.5.1:
** 445 seconds for 2000 searches
** Search threads spend 56% of total time computing similarities, 42% in the
decompress method.
VisualVM screenshot for 7.6.x:
!hotspots-v76x.png!
VisualVM screenshot for 7.7.x:
!hotspots-v77x.png!
Attaching snapshots from VisualVM:
[^snapshots-v76x.nps]
[^snapshot-v77x.nps]
Thank you all for your help! :)
> Configurable compression for BinaryDocValues
> --------------------------------------------
>
> Key: LUCENE-9378
> URL: https://issues.apache.org/jira/browse/LUCENE-9378
> Project: Lucene - Core
> Issue Type: Improvement
> Reporter: Viral Gandhi
> Priority: Minor
> Attachments: hotspots-v76x.png, hotspots-v76x.png, hotspots-v76x.png,
> hotspots-v76x.png, hotspots-v76x.png, hotspots-v77x.png, hotspots-v77x.png,
> hotspots-v77x.png, hotspots-v77x.png, image-2020-06-12-22-17-30-339.png,
> image-2020-06-12-22-17-53-961.png, image-2020-06-12-22-18-24-527.png,
> image-2020-06-12-22-18-48-919.png, snapshot-v77x.nps, snapshot-v77x.nps,
> snapshot-v77x.nps, snapshots-v76x.nps, snapshots-v76x.nps, snapshots-v76x.nps
>
> Time Spent: 3h 40m
> Remaining Estimate: 0h
>
> Lucene 8.5.1 includes a change to always [compress
> BinaryDocValues|https://issues.apache.org/jira/browse/LUCENE-9211]. This
> caused (~30%) reduction in our red-line QPS (throughput).
> We think users should be given some way to opt-in for this compression
> feature instead of always being enabled which can have a substantial query
> time cost as we saw during our upgrade. [~mikemccand] suggested one possible
> approach by introducing a *mode* in Lucene80DocValuesFormat (COMPRESSED and
> UNCOMPRESSED) and allowing users to create a custom Codec subclassing the
> default Codec and pick the format they want.
> Idea is similar to Lucene50StoredFieldsFormat which has two modes,
> Mode.BEST_SPEED and Mode.BEST_COMPRESSION.
> Here's related issues for adding benchmark covering BINARY doc values
> query-time performance - [https://github.com/mikemccand/luceneutil/issues/61]
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