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From "Owen O'Malley (JIRA)" <>
Subject [jira] [Commented] (HIVE-9188) BloomFilter in ORC row group index
Date Tue, 13 Jan 2015 21:46:34 GMT


Owen O'Malley commented on HIVE-9188:

[~prasanth_j] Please remove the upper two levels of bloom filters. They are utterly useless.
Their false positive rate will be far above 99%.

They absolutely should not be stored in the column statistics. That will hurt the common ppd
case and not help.

> BloomFilter in ORC row group index
> ----------------------------------
>                 Key: HIVE-9188
>                 URL:
>             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
> 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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