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https://issues.apache.org/jira/browse/SPARK-18252?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15676899#comment-15676899
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Aleksey Ponkin commented on SPARK-18252:
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I did benchmarks(you can find it
[here|https://github.com/ponkin/bloo-filter-perf]) - tests were executed with 1
million random strings dataset.
1. bloom filter with roaringbitmap 20-25% slower than good old BitArray
implementation in put and migthContain operations.
new put - Elapsed time: 2308348596ns
old put - Elapsed time: 1700994048ns
new mightContain - Elapsed time: 2191514527ns
old mightContain - Elapsed time: 1637640048ns
2.full bloom filter with roaringbitmap(all expected elements are inserted) has
the same or bigger size than bitarray version(as I said earlier roaringbitmap
poorly compress half filled random strings)
Conclusion: Benefits from using RoaringBitmap in BloomFilters are not clear.
I think we can close the ticket. Thanks to everyone, sorry for waisting your
time)
> Improve serialized BloomFilter size
> -----------------------------------
>
> Key: SPARK-18252
> URL: https://issues.apache.org/jira/browse/SPARK-18252
> Project: Spark
> Issue Type: Improvement
> Components: Spark Core
> Affects Versions: 2.0.1
> Reporter: Aleksey Ponkin
> Priority: Minor
>
> Since version 2.0 Spark has BloomFilter implementation -
> org.apache.spark.util.sketch.BloomFilterImpl. I have noticed that current
> implementation is using custom class org.apache.spark.util.sketch.BitArray
> for bit vector, which is allocating memory for the whole filter no matter how
> many elements are set. Since BloomFilter can be serialized and sent over
> network in distribution stage may be we need to use some kind of compressed
> bloom filters? For example
> [https://github.com/RoaringBitmap/RoaringBitmap][RoaringBitmap] or
> [javaewah][https://github.com/lemire/javaewah].
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