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From "ASF GitHub Bot (Jira)" <j...@apache.org>
Subject [jira] [Work logged] (HIVE-22239) Scale data size using column value ranges
Date Tue, 08 Oct 2019 08:48:01 GMT

     [ https://issues.apache.org/jira/browse/HIVE-22239?focusedWorklogId=324944&page=com.atlassian.jira.plugin.system.issuetabpanels:worklog-tabpanel#worklog-324944
]

ASF GitHub Bot logged work on HIVE-22239:
-----------------------------------------

                Author: ASF GitHub Bot
            Created on: 08/Oct/19 08:47
            Start Date: 08/Oct/19 08:47
    Worklog Time Spent: 10m 
      Work Description: kgyrtkirk commented on pull request #787: HIVE-22239
URL: https://github.com/apache/hive/pull/787#discussion_r332382671
 
 

 ##########
 File path: ql/src/test/results/clientpositive/llap/bucket_map_join_tez2.q.out
 ##########
 @@ -759,50 +759,56 @@ STAGE PLANS:
                   Statistics: Num rows: 500 Data size: 2000 Basic stats: COMPLETE Column
stats: COMPLETE
                   Filter Operator
                     predicate: (key > 2) (type: boolean)
-                    Statistics: Num rows: 166 Data size: 664 Basic stats: COMPLETE Column
stats: COMPLETE
+                    Statistics: Num rows: 498 Data size: 1992 Basic stats: COMPLETE Column
stats: COMPLETE
                     Select Operator
                       expressions: key (type: int)
                       outputColumnNames: _col0
-                      Statistics: Num rows: 166 Data size: 664 Basic stats: COMPLETE Column
stats: COMPLETE
-                      Map Join Operator
-                        condition map:
-                             Inner Join 0 to 1
-                        keys:
-                          0 _col0 (type: int)
-                          1 _col0 (type: int)
-                        outputColumnNames: _col0, _col1
-                        input vertices:
-                          1 Map 2
-                        Statistics: Num rows: 272 Data size: 2176 Basic stats: COMPLETE Column
stats: COMPLETE
-                        File Output Operator
-                          compressed: false
-                          Statistics: Num rows: 272 Data size: 2176 Basic stats: COMPLETE
Column stats: COMPLETE
-                          table:
-                              input format: org.apache.hadoop.mapred.SequenceFileInputFormat
-                              output format: org.apache.hadoop.hive.ql.io.HiveSequenceFileOutputFormat
-                              serde: org.apache.hadoop.hive.serde2.lazy.LazySimpleSerDe
+                      Statistics: Num rows: 498 Data size: 1992 Basic stats: COMPLETE Column
stats: COMPLETE
+                      Reduce Output Operator
+                        key expressions: _col0 (type: int)
+                        sort order: +
+                        Map-reduce partition columns: _col0 (type: int)
+                        Statistics: Num rows: 498 Data size: 1992 Basic stats: COMPLETE Column
stats: COMPLETE
 
 Review comment:
   disable enhancement; seems to be interfering with the test
 
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Issue Time Tracking
-------------------

    Worklog Id:     (was: 324944)
    Time Spent: 1h  (was: 50m)

> Scale data size using column value ranges
> -----------------------------------------
>
>                 Key: HIVE-22239
>                 URL: https://issues.apache.org/jira/browse/HIVE-22239
>             Project: Hive
>          Issue Type: Improvement
>          Components: Physical Optimizer
>            Reporter: Jesus Camacho Rodriguez
>            Assignee: Jesus Camacho Rodriguez
>            Priority: Major
>              Labels: pull-request-available
>         Attachments: HIVE-22239.01.patch, HIVE-22239.02.patch, HIVE-22239.patch
>
>          Time Spent: 1h
>  Remaining Estimate: 0h
>
> Currently, min/max values for columns are only used to determine whether a certain range
filter falls out of range and thus filters all rows or none at all. If it does not, we just
use a heuristic that the condition will filter 1/3 of the input rows. Instead of using that
heuristic, we can use another one that assumes that data will be uniformly distributed across
that range, and calculate the selectivity for the condition accordingly.
> This patch also includes the propagation of min/max column values from statistics to
the optimizer for timestamp type.



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