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https://issues.apache.org/jira/browse/HIVE-22515?focusedWorklogId=377960&page=com.atlassian.jira.plugin.system.issuetabpanels:worklog-tabpanel#worklog-377960
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ASF GitHub Bot logged work on HIVE-22515:
-----------------------------------------
Author: ASF GitHub Bot
Created on: 28/Jan/20 01:12
Start Date: 28/Jan/20 01:12
Worklog Time Spent: 10m
Work Description: ramesh0201 commented on pull request #880: HIVE-22515
Support cast to decimal64 in Vectorization
URL: https://github.com/apache/hive/pull/880#discussion_r371567891
##########
File path:
ql/src/test/results/clientpositive/llap/vector_reuse_scratchcols.q.out
##########
@@ -369,7 +369,7 @@ STAGE PLANS:
includeColumns: [0, 1, 2, 3, 4, 5, 6, 7, 9, 10, 11]
dataColumns: ctinyint:tinyint, csmallint:smallint,
cint:int, cbigint:bigint, cfloat:float, cdouble:double, cstring1:string,
cstring2:string, ctimestamp1:timestamp, ctimestamp2:timestamp,
cboolean1:boolean, cboolean2:boolean
partitionColumnCount: 0
- scratchColumnTypeNames: [double, double, double,
decimal(22,3), decimal(13,3), double, double, double, double, double, double,
double, double]
+ scratchColumnTypeNames: [double, double, double,
decimal(22,3), decimal(13,3)/DECIMAL_64, double, double, double, double,
double, double, double, double]
Review comment:
Yes, because we can safely store a decimal with (13,3) by scaling them up
and storing in long vectors and tracking the scale. We do this until
precision+scale is <=18.
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Issue Time Tracking
-------------------
Worklog Id: (was: 377960)
Time Spent: 0.5h (was: 20m)
> Support cast to decimal64 in Vectorization
> ------------------------------------------
>
> Key: HIVE-22515
> URL: https://issues.apache.org/jira/browse/HIVE-22515
> Project: Hive
> Issue Type: Bug
> Reporter: Ramesh Kumar Thangarajan
> Assignee: Ramesh Kumar Thangarajan
> Priority: Major
> Labels: pull-request-available
> Attachments: HIVE-22515.5.patch, HIVE-22515.8.patch,
> HIVE-22515.9.patch
>
> Time Spent: 0.5h
> Remaining Estimate: 0h
>
> Support cast to decimal64 in Vectorization
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