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ASF GitHub Bot logged work on HIVE-26221: ----------------------------------------- Author: ASF GitHub Bot Created on: 06/Dec/22 07:10 Start Date: 06/Dec/22 07:10 Worklog Time Spent: 10m Work Description: asolimando commented on code in PR #3137: URL: https://github.com/apache/hive/pull/3137#discussion_r1040578295 ########## standalone-metastore/metastore-server/src/test/java/org/apache/hadoop/hive/metastore/columnstats/ColStatsBuilder.java: ########## @@ -103,6 +105,12 @@ public ColStatsBuilder<T> hll(String... values) { return this; } + public ColStatsBuilder<T> hll(double... values) { + HyperLogLog hll = StatisticsTestUtils.createHll(values); + this.bitVector = hll.serialize(); Review Comment: No, HLL is different from KLL, it's used for counting distinct values, the method naming is different because HLL has a in-house implementation in Hive while KLL comes from Apache datasketches library Issue Time Tracking ------------------- Worklog Id: (was: 831280) Time Spent: 4h 20m (was: 4h 10m) > 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: 4h 20m > 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). -- This message was sent by Atlassian Jira (v8.20.10#820010)