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https://issues.apache.org/jira/browse/HIVE-26221?focusedWorklogId=830968&page=com.atlassian.jira.plugin.system.issuetabpanels:worklog-tabpanel#worklog-830968
]
ASF GitHub Bot logged work on HIVE-26221:
-----------------------------------------
Author: ASF GitHub Bot
Created on: 05/Dec/22 09:14
Start Date: 05/Dec/22 09:14
Worklog Time Spent: 10m
Work Description: asolimando commented on code in PR #3137:
URL: https://github.com/apache/hive/pull/3137#discussion_r1039333194
##########
standalone-metastore/metastore-server/src/main/java/org/apache/hadoop/hive/metastore/columnstats/aggr/BinaryColumnStatsAggregator.java:
##########
@@ -60,4 +60,8 @@ public ColumnStatisticsObj
aggregate(List<ColStatsObjWithSourceInfo> colStatsWit
statsObj.setStatsData(columnStatisticsData);
return statsObj;
}
+
+ @Override protected ColumnStatisticsData initColumnStatisticsData() {
+ throw new UnsupportedOperationException("initColumnStatisticsData not
supported for binary statistics");
Review Comment:
You are right, the method does not do much for `binary` and `boolean`, but
it still make sense, so I have:
- removed the exception, replaced with `return new ColumnStatisticsData();`
- used the method to actually initialize the emtpy `ColumnStatisticsData`
for those two data types
Issue Time Tracking
-------------------
Worklog Id: (was: 830968)
Time Spent: 3h (was: 2h 50m)
> Add histogram-based column statistics
> -------------------------------------
>
> Key: HIVE-26221
> URL: https://issues.apache.org/jira/browse/HIVE-26221
> Project: Hive
> Issue Type: Improvement
> Components: CBO, Metastore, Statistics
> Affects Versions: 4.0.0-alpha-2
> Reporter: Alessandro Solimando
> Assignee: Alessandro Solimando
> Priority: Major
> Labels: pull-request-available
> Time Spent: 3h
> Remaining Estimate: 0h
>
> 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/56c336268ea8c281d23c22d89271af37cb7e2572/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 the underlying data structure for our histogram statistics.
> The current proposal targets numeric data types (float, integer and numeric
> families) and temporal data types (date and timestamp).
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