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Thomas Graves updated SPARK-25250:
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Description:
We recently had a scenario where a race condition occurred when a task from
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Thomas Graves updated SPARK-25250:
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Priority: Major (was: Minor)
> Race condition with tasks running when new attempt for same
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Thomas Graves updated SPARK-24909:
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Description:
The DAGScheduler can hang if the executor was lost (due to fetch failure) and
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Thomas Graves updated SPARK-24909:
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Description:
The DAGScheduler can hang if the executor was lost (due to fetch failure) and
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Thomas Graves commented on SPARK-24924:
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I'd be ok with that but CSV has been that way already for
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Thomas Graves commented on SPARK-24924:
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[~cloud_fan] [~hyukjin.kwon] seems no one else has a
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Thomas Graves reassigned SPARK-25043:
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Assignee: Alessandro Bellina
> spark-sql should print the appId and master on startup
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Thomas Graves resolved SPARK-25043.
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Resolution: Fixed
Fix Version/s: 2.4.0
> spark-sql should print the appId and master
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Thomas Graves commented on SPARK-24787:
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Yes it was caused by hsync, hsync has to go to the
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Thomas Graves commented on SPARK-24918:
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Personally I like the explicit config on better
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Thomas Graves updated SPARK-25051:
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Priority: Blocker (was: Major)
> where clause on dataset gives AnalysisException
>
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Thomas Graves commented on SPARK-23298:
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[~mjukiewicz] have you tried spark with fix for
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Thomas Graves commented on SPARK-25081:
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thanks, wanted to clarify since the description only
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Thomas Graves commented on SPARK-25081:
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Does this ever result in the task reading the wrong data
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Thomas Graves commented on SPARK-25024:
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ok, I'm not familiar with mesos hardly at all so I
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Thomas Graves commented on SPARK-23207:
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ok, I guess I disagree with that. Any correctness bug is
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Thomas Graves commented on SPARK-23207:
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[~jiangxb1987] ^
> Shuffle+Repartition on an DataFrame
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Thomas Graves commented on SPARK-24924:
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| There was a discussion about why we shouldn't support
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Thomas Graves commented on SPARK-23207:
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does this affect spark 2.2 and < ? from the description
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Thomas Graves commented on SPARK-24598:
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In the very least we should file a separate Jira to track
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Thomas Graves commented on SPARK-24924:
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so originally when I started on this I didn't know about
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Thomas Graves commented on SPARK-24924:
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thanks, I missed it in the output for spark as I was just
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Thomas Graves commented on SPARK-24924:
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so officially the spark api compatibility is only at the
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Thomas Graves commented on SPARK-24924:
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so if the user includes the databricks jar and they
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Thomas Graves resolved SPARK-24992.
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Resolution: Fixed
Assignee: Hieu Tri Huynh
Fix Version/s: 2.4.0
> spark
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Thomas Graves commented on SPARK-24924:
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So something I just thought of that I want to clarify, is
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Thomas Graves commented on SPARK-24924:
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For compatibility we can't remove it unless major
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Thomas Graves resolved SPARK-24981.
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Resolution: Fixed
Assignee: Hieu Tri Huynh
Fix Version/s: 2.4.0
>
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Thomas Graves commented on SPARK-24924:
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{quote}I have followed the changes in Avro and I don't
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Thomas Graves commented on SPARK-25024:
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We need to make it clear what mesos supports for security
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Thomas Graves commented on SPARK-25023:
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note some of this was already updated with
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Thomas Graves updated SPARK-25024:
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Comment: was deleted
(was: I'm going to work on this.)
> Update mesos documentation to be
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Thomas Graves commented on SPARK-25023:
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I'm going to work on this
> Clarify Spark security
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Thomas Graves commented on SPARK-25024:
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I'm going to work on this.
> Update mesos documentation
Thomas Graves created SPARK-25024:
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Summary: Update mesos documentation to be clear about security
supported
Key: SPARK-25024
URL: https://issues.apache.org/jira/browse/SPARK-25024
Project: Spark
Thomas Graves created SPARK-25023:
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Summary: Clarify Spark security documentation
Key: SPARK-25023
URL: https://issues.apache.org/jira/browse/SPARK-25023
Project: Spark
Issue Type: Bug
Thomas Graves created SPARK-25016:
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Summary: remove Support for hadoop 2.6
Key: SPARK-25016
URL: https://issues.apache.org/jira/browse/SPARK-25016
Project: Spark
Issue Type: Improvement
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Thomas Graves updated SPARK-25016:
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Target Version/s: 3.0.0
> remove Support for hadoop 2.6
> -
>
>
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Thomas Graves commented on SPARK-24924:
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| It wouldn't be very different for 2.4.0. It could be
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Thomas Graves commented on SPARK-24924:
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[~felixcheung] did your discussion on the same thing with
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Thomas Graves commented on SPARK-24924:
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Hmm, so we are adding this for ease of upgrading I guess
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Thomas Graves updated SPARK-24909:
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Target Version/s: 2.4.0
> Spark scheduler can hang when fetch failures, executor lost, task
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Thomas Graves commented on SPARK-24924:
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why are we doing this? If a user ships the spark-avro
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Thomas Graves commented on SPARK-24909:
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looking more I think the fix may actually just be to
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Thomas Graves commented on SPARK-24909:
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this is unfortunately not a straight forward fix, the
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Thomas Graves commented on SPARK-24986:
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fyi [~irashid] I know you were looking at memory related
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Thomas Graves commented on SPARK-24615:
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so I guess my question is this the right approach at all.
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Thomas Graves commented on SPARK-24579:
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going from Spark feeds data into DL/AI frameworks for
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Thomas Graves commented on SPARK-24934:
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what is the real affected versions here? Since it went
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Thomas Graves updated SPARK-23243:
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Priority: Blocker (was: Major)
> Shuffle+Repartition on an RDD could lead to incorrect
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Thomas Graves resolved SPARK-13343.
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Resolution: Fixed
Assignee: Hieu Tri Huynh
Fix Version/s: 2.4.0
>
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Thomas Graves commented on SPARK-24918:
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I think this is a good idea. I thought I had seen a Jira
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Thomas Graves commented on SPARK-24909:
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I haven't come up with a fix yet but have been looking at
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Thomas Graves updated SPARK-24909:
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Description:
The DAGScheduler can hang if the executor was lost (due to fetch failure) and
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Thomas Graves updated SPARK-24909:
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Summary: Spark scheduler can hang when fetch failures, executor lost, task
running on lost
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Thomas Graves commented on SPARK-24909:
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Note this may have been introduced as part of SPARK-23433
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Thomas Graves updated SPARK-24909:
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Description:
The DAGScheduler can hang if the executor was lost (due to fetch failure) and
Thomas Graves created SPARK-24909:
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Summary: Spark scheduler can hang with fetch failures and executor
lost and multiple stage attempts
Key: SPARK-24909
URL: https://issues.apache.org/jira/browse/SPARK-24909
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Thomas Graves updated SPARK-24909:
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Priority: Critical (was: Major)
> Spark scheduler can hang with fetch failures and executor
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Thomas Graves commented on SPARK-24615:
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Right so I think part of this is trying to make it more
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Thomas Graves commented on SPARK-23128:
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we also did some initial evaluation with it as well and
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Thomas Graves commented on SPARK-23128:
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[~carsonwang] I'm curious if you are still running with
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Thomas Graves commented on SPARK-24615:
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the other thing which I think I mentioned above is could
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Thomas Graves commented on SPARK-24615:
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Ok so thinking about this a bit more I slightly misread
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Thomas Graves commented on SPARK-24615:
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yes if any requirement can't be satisfied it would use
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Thomas Graves reassigned SPARK-24755:
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Assignee: Hieu Tri Huynh
> Executor loss can cause task to not be resubmitted
>
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Thomas Graves resolved SPARK-24755.
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Resolution: Fixed
Fix Version/s: 2.3.3
2.4.0
> Executor loss can
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Thomas Graves commented on SPARK-22151:
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ok thanks, must have missed that.
> PYTHONPATH not
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Thomas Graves commented on SPARK-22151:
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[~srowen] why did you blank out fixed version and
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Thomas Graves resolved SPARK-22151.
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Resolution: Fixed
Fix Version/s: 2.4.0
> PYTHONPATH not picked up from the
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Thomas Graves edited comment on SPARK-24615 at 7/19/18 2:28 PM:
but my
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Thomas Graves commented on SPARK-24615:
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but my point is exactly that, it shouldn't be yet another
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Thomas Graves commented on SPARK-24615:
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I think the usage for cpu/memory is the same. You know
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Thomas Graves reassigned SPARK-22151:
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Assignee: Parth Gandhi
> PYTHONPATH not picked up from the spark.yarn.appMasterEnv
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Thomas Graves updated SPARK-22151:
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Fix Version/s: 2.4.0
> PYTHONPATH not picked up from the spark.yarn.appMasterEnv properly
>
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Thomas Graves updated SPARK-24677:
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Fix Version/s: 2.2.3
> TaskSetManager not updating successfulTaskDurations for old stage
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Thomas Graves resolved SPARK-24677.
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Resolution: Fixed
Fix Version/s: 2.4.0
2.3.3
> TaskSetManager not
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Thomas Graves reassigned SPARK-24677:
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Assignee: dzcxzl
> TaskSetManager not updating successfulTaskDurations for old stage
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Thomas Graves updated SPARK-24677:
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Summary: TaskSetManager not updating successfulTaskDurations for old stage
attempts (was:
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Thomas Graves edited comment on SPARK-24677 at 7/18/18 6:22 PM:
This is
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Thomas Graves commented on SPARK-24677:
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In this case one of the older stage attempts (that is a
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Thomas Graves commented on SPARK-24615:
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did the design doc permissions change? I can't seem to
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Thomas Graves commented on SPARK-24615:
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ok, I agree, I think this SPIP should at least cover how
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Thomas Graves commented on SPARK-24615:
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The user is responsible for asking yarn for the right
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Thomas Graves commented on SPARK-24615:
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[~jerryshao] ^
> Accelerator aware task scheduling for
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Thomas Graves resolved SPARK-24610.
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Resolution: Fixed
Fix Version/s: 2.4.0
> wholeTextFiles broken for small files
>
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Thomas Graves reassigned SPARK-24610:
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Assignee: Dhruve Ashar
> wholeTextFiles broken for small files
>
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Thomas Graves commented on SPARK-16534:
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I agree it seems a bit of a bad user story to drop
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https://issues.apache.org/jira/browse/SPARK-16534?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=16537034#comment-16537034
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Thomas Graves commented on SPARK-16534:
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If we aren't going to do this we should close this as
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https://issues.apache.org/jira/browse/SPARK-13343?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Thomas Graves updated SPARK-13343:
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Description:
Currently Speculative tasks that didn't commit can show up as success
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https://issues.apache.org/jira/browse/SPARK-17181?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=16529869#comment-16529869
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Thomas Graves commented on SPARK-17181:
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that would be a question for [~marymwu]
> [Spark2.0 web
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https://issues.apache.org/jira/browse/SPARK-24615?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=16528293#comment-16528293
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Thomas Graves commented on SPARK-24615:
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maybe I"m missing it but how is this working with the
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https://issues.apache.org/jira/browse/SPARK-23309?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=16527865#comment-16527865
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Thomas Graves commented on SPARK-23309:
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We tried this on a newest 2.3.1 and haven't been able to
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https://issues.apache.org/jira/browse/SPARK-23309?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Thomas Graves resolved SPARK-23309.
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Resolution: Works for Me
> Spark 2.3 cached query performance 20-30% worse then spark 2.2
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https://issues.apache.org/jira/browse/SPARK-24372?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Thomas Graves resolved SPARK-24372.
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Resolution: Fixed
Assignee: Marcelo Vanzin
Fix Version/s: 2.4.0
> Create
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https://issues.apache.org/jira/browse/SPARK-24519?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Thomas Graves resolved SPARK-24519.
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Resolution: Fixed
Assignee: Hieu Tri Huynh
Fix Version/s: 2.4.0
> MapStatus
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https://issues.apache.org/jira/browse/SPARK-22897?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Thomas Graves updated SPARK-22897:
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Fix Version/s: 2.2.2
> Expose stageAttemptId in TaskContext
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https://issues.apache.org/jira/browse/SPARK-24589?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Thomas Graves resolved SPARK-24589.
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Resolution: Fixed
Assignee: Marcelo Vanzin
Fix Version/s: 2.4.0
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https://issues.apache.org/jira/browse/SPARK-24552?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=16519445#comment-16519445
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Thomas Graves edited comment on SPARK-24552 at 6/21/18 3:02 PM:
more
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https://issues.apache.org/jira/browse/SPARK-24552?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=16519445#comment-16519445
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Thomas Graves edited comment on SPARK-24552 at 6/21/18 3:01 PM:
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