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https://issues.apache.org/jira/browse/HIVE-11297?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16036830#comment-16036830
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Hive QA commented on HIVE-11297:
--------------------------------
Here are the results of testing the latest attachment:
https://issues.apache.org/jira/secure/attachment/12871201/HIVE-11297.2.patch
{color:green}SUCCESS:{color} +1 due to 1 test(s) being added or modified.
{color:red}ERROR:{color} -1 due to 5 failed/errored test(s), 10820 tests
executed
*Failed tests:*
{noformat}
org.apache.hadoop.hive.cli.TestMiniLlapCliDriver.testCliDriver[orc_ppd_basic]
(batchId=140)
org.apache.hadoop.hive.cli.TestMiniLlapLocalCliDriver.testCliDriver[vector_if_expr]
(batchId=145)
org.apache.hadoop.hive.cli.TestMiniTezCliDriver.testCliDriver[explainanalyze_2]
(batchId=99)
org.apache.hadoop.hive.cli.TestPerfCliDriver.testCliDriver[query14]
(batchId=232)
org.apache.hadoop.hive.cli.TestPerfCliDriver.testCliDriver[query78]
(batchId=232)
{noformat}
Test results: https://builds.apache.org/job/PreCommit-HIVE-Build/5531/testReport
Console output: https://builds.apache.org/job/PreCommit-HIVE-Build/5531/console
Test logs: http://104.198.109.242/logs/PreCommit-HIVE-Build-5531/
Messages:
{noformat}
Executing org.apache.hive.ptest.execution.TestCheckPhase
Executing org.apache.hive.ptest.execution.PrepPhase
Executing org.apache.hive.ptest.execution.ExecutionPhase
Executing org.apache.hive.ptest.execution.ReportingPhase
Tests exited with: TestsFailedException: 5 tests failed
{noformat}
This message is automatically generated.
ATTACHMENT ID: 12871201 - PreCommit-HIVE-Build
> Combine op trees for partition info generating tasks [Spark branch]
> -------------------------------------------------------------------
>
> Key: HIVE-11297
> URL: https://issues.apache.org/jira/browse/HIVE-11297
> Project: Hive
> Issue Type: Bug
> Affects Versions: spark-branch
> Reporter: Chao Sun
> Assignee: liyunzhang_intel
> Attachments: HIVE-11297.1.patch, HIVE-11297.2.patch
>
>
> Currently, for dynamic partition pruning in Spark, if a small table generates
> partition info for more than one partition columns, multiple operator trees
> are created, which all start from the same table scan op, but have different
> spark partition pruning sinks.
> As an optimization, we can combine these op trees and so don't have to do
> table scan multiple times.
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