[
https://issues.apache.org/jira/browse/HBASE-29889?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
JinHyuk Kim updated HBASE-29889:
--------------------------------
Description:
h2. Summary
Added *XXH3* as a new hashing option for the HBase Bloom Filter.
h2. Background
Existing hash functions used in HBase Bloom Filters(Jenkins, Murmur and
Murmur3) were designed years ago and do not fully leverage modern CPU
architectures.
[*XXH3*|https://github.com/Cyan4973/xxHash], on the other hand, is optimized
for today’s CPUs with wide execution units and fast unaligned memory access,
resulting in significantly faster hashing performance.
h2. What Was Done
* Implemented XXH3 Hashing and integrated it as an available hash type for
Bloom Filters.
* Conducted benchmark tests comparing XXH3 with existing hash algorithms.
** Benchmark test code is available in
[jinhyukify/xxh3-benchmark.|https://github.com/jinhyukify/xxh3-benchmark]
* *Benchmark Results:*
**
https://docs.google.com/document/d/1KcCLz3nnkDNgUUMpTIWOwvrY8kgpOJFKZHboRNt2mx0/edit?usp=sharing
h2. Expected Impact
* *Faster Bloom filter lookups* across all Bloom types during client-side read
paths.
* *Slight improvement in Bloom filter write performance* during HFile creation
and compaction, thanks to the lower hashing overhead of XXH3.
was:
h2. Summary
Added *XXH3* as a new hashing option for the HBase Bloom Filter.
h2. Background
Existing hash functions used in HBase Bloom Filters(Jenkins, Murmur and
Murmur3) were designed years ago and do not fully leverage modern CPU
architectures.
[*XXH3*|https://github.com/Cyan4973/xxHash], on the other hand, is optimized
for today’s CPUs with wide execution units and fast unaligned memory access,
resulting in significantly faster hashing performance.
h2. What Was Done
* Implemented XXH3 Hashing and integrated it as an available hash type for
Bloom Filters.
* Conducted benchmark tests comparing XXH3 with existing hash algorithms.
** Benchmark test code is available in
[jinhyukify/xxh3-benchmark.|https://github.com/jinhyukify/xxh3-benchmark]
* *Benchmark Results:*
**
[https://docs.google.com/document/d/1KcCLz3nnkDNgUUMpTIWOwvrY8kgpOJFKZHboRNt2mx0/edit?usp=sharing|https://docs.google.com/document/d/1LycZZMKFrrxYytEnzVj-EjQB4PbmmTgprhMOpDRPqYM/edit?usp=sharing]
h2. Expected Impact
* *Faster Bloom filter lookups* across all Bloom types during client-side read
paths.
* *Slight improvement in Bloom filter write performance* during HFile creation
and compaction, thanks to the lower hashing overhead of XXH3.
> Add XXH3 Hash Support to Bloom Filter
> -------------------------------------
>
> Key: HBASE-29889
> URL: https://issues.apache.org/jira/browse/HBASE-29889
> Project: HBase
> Issue Type: New Feature
> Components: regionserver
> Reporter: JinHyuk Kim
> Assignee: JinHyuk Kim
> Priority: Major
> Labels: pull-request-available
>
> h2. Summary
> Added *XXH3* as a new hashing option for the HBase Bloom Filter.
> h2. Background
> Existing hash functions used in HBase Bloom Filters(Jenkins, Murmur and
> Murmur3) were designed years ago and do not fully leverage modern CPU
> architectures.
> [*XXH3*|https://github.com/Cyan4973/xxHash], on the other hand, is optimized
> for today’s CPUs with wide execution units and fast unaligned memory access,
> resulting in significantly faster hashing performance.
> h2. What Was Done
> * Implemented XXH3 Hashing and integrated it as an available hash type for
> Bloom Filters.
> * Conducted benchmark tests comparing XXH3 with existing hash algorithms.
> ** Benchmark test code is available in
> [jinhyukify/xxh3-benchmark.|https://github.com/jinhyukify/xxh3-benchmark]
> * *Benchmark Results:*
> **
> https://docs.google.com/document/d/1KcCLz3nnkDNgUUMpTIWOwvrY8kgpOJFKZHboRNt2mx0/edit?usp=sharing
> h2. Expected Impact
> * *Faster Bloom filter lookups* across all Bloom types during client-side
> read paths.
> * *Slight improvement in Bloom filter write performance* during HFile
> creation and compaction, thanks to the lower hashing overhead of XXH3.
--
This message was sent by Atlassian Jira
(v8.20.10#820010)
