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https://issues.apache.org/jira/browse/IMPALA-6070?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16483439#comment-16483439
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ASF subversion and git services commented on IMPALA-6070:
---------------------------------------------------------

Commit 9116423a76ca1a11fdd440d20f6fd14700bf9df9 in impala's branch 
refs/heads/2.x from [~philip]
[ https://git-wip-us.apache.org/repos/asf?p=impala.git;h=9116423 ]

IMPALA-6070: Adding ASAN, --tail to test-with-docker.

* Adds -ASAN suites to test-with-docker.
* Adds --tail flag, which starts a tail subprocess. This
  isn't pretty (there's potential for overlap), but it's a dead simple
  way to keep an eye on what's going on.
* Fixes a bug wherein I could call "docker rm <container>" twice
  simultaneously, which would make Docker fail the second call,
  and then fail the related "docker rmi". It's better to serialize,
  and I did that with a simple lock.

Change-Id: I51451cdf1352fc0f9516d729b9a77700488d993f
Reviewed-on: http://gerrit.cloudera.org:8080/10319
Reviewed-by: Joe McDonnell <joemcdonn...@cloudera.com>
Tested-by: Impala Public Jenkins <impala-public-jenk...@cloudera.com>


> Speed up test execution
> -----------------------
>
>                 Key: IMPALA-6070
>                 URL: https://issues.apache.org/jira/browse/IMPALA-6070
>             Project: IMPALA
>          Issue Type: Bug
>            Reporter: Philip Zeyliger
>            Assignee: Philip Zeyliger
>            Priority: Major
>         Attachments: screenshot-1.png
>
>
> Our tests (e.g., 
> https://jenkins.impala.io/job/ubuntu-16.04-from-scratch/buildTimeTrend) tend 
> to take about 4 hours. This can be improved.
> I'm opening this JIRA track those changes. I'm currently looking at:
> * Parallelizing multiple data-load steps: TPC-DS, TPC-H, and Functional take 
> ~65 minutes when serialized. They take 35 minutes if running in parallel.
> * Parallelizing compute stats: this takes ~10 minutes; probably can be faster.
> The trickier thing is parallelizing fe tests, ee tests, and custom cluster 
> tests. The approach I'm taking is to create a docker container with 
> everything in it (including data load), and then running tests in parallel. 
> This is a bit messier, but I think it has some legs when it comes to using 
> machines with many cores.



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