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https://issues.apache.org/jira/browse/HIVE-9188?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14302507#comment-14302507
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Owen O'Malley commented on HIVE-9188:
-------------------------------------
Suggestions:
* Pick m to always be a multiple of 64 (since you are using longs are the
representation)
* change the representation of BloomFilter in orc_proto to record the number of
hash functions and not the size or fpp.
* use fixed64 for the bit field
* you'll also need to update the specification in the wiki with the change to
the format
(https://cwiki.apache.org/confluence/display/Hive/LanguageManual+ORC#LanguageManualORC-orc-specORCFormatSpecification)
* revert the spurious change to CliDriver.java
* revert the spurious change to .gitignore
* it seems suboptimal to convert long values to bytes before hashing
> BloomFilter in ORC row group index
> ----------------------------------
>
> Key: HIVE-9188
> URL: https://issues.apache.org/jira/browse/HIVE-9188
> Project: Hive
> Issue Type: New Feature
> Components: File Formats
> Affects Versions: 0.15.0
> Reporter: Prasanth Jayachandran
> Assignee: Prasanth Jayachandran
> Labels: orcfile
> Attachments: HIVE-9188.1.patch, HIVE-9188.2.patch, HIVE-9188.3.patch,
> HIVE-9188.4.patch, HIVE-9188.5.patch, HIVE-9188.6.patch
>
>
> BloomFilters are well known probabilistic data structure for set membership
> checking. We can use bloom filters in ORC index for better row group pruning.
> Currently, ORC row group index uses min/max statistics to eliminate row
> groups (stripes as well) that do not satisfy predicate condition specified in
> the query. But in some cases, the efficiency of min/max based elimination is
> not optimal (unsorted columns with wide range of entries). Bloom filters can
> be an effective and efficient alternative for row group/split elimination for
> point queries or queries with IN clause.
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