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Posted to dev@hive.apache.org by "Alessandro Solimando (Jira)" <ji...@apache.org> on 2022/05/11 09:22:00 UTC

[jira] [Created] (HIVE-26221) Add histogram-based column statistics

Alessandro Solimando created HIVE-26221:
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             Summary: Add histogram-based column statistics
                 Key: HIVE-26221
                 URL: https://issues.apache.org/jira/browse/HIVE-26221
             Project: Hive
          Issue Type: Improvement
          Components: Statistics
    Affects Versions: 4.0.0-alpha-2
            Reporter: Alessandro Solimando
            Assignee: Alessandro Solimando


Hive does not support histogram statistics, which are particularly useful for skewed data (which is very common in practice) and range predicates.

Hive's current selectivity estimation for range predicates is based on a hard-coded value of 1/3 (see [FilterSelectivityEstimator.java#L138-L144|[https://github.com/apache/hive/blob/4622860b8c7dbddaf4c556e65c5039c60da15e82/ql/src/java/org/apache/hadoop/hive/ql/optimizer/calcite/stats/FilterSelectivityEstimator.java#L138-L144]).]

The current proposal aims at integrating histogram as an additional column statistics, stored into the Hive metastore at the table (or partition) level.

The main requirements for histogram integration are the following:
 * efficiency: the approach must scale and support billions of rows
 * merge-ability: partition-level histograms have to be merged to form table-level histograms
 * explicit and configurable trade-off between memory footprint and accuracy

Hive already integrates [KLL data sketches|https://datasketches.apache.org/docs/KLL/KLLSketch.html] UDAF. Datasketches are small, stateful programs that process massive data-streams and can provide approximate answers, with mathematical guarantees, to computationally difficult queries orders-of-magnitude faster than traditional, exact methods.

We propose to use KLL, and more specifically the cumulative distribution function (CDF) as underlying data structure for our histogram statistics.

The current proposal only targets numeric data types (float, integer and numeric families), excluding string and temporal data types for the moment.



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