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Apache Spark reassigned SPARK-24397:
Assignee: Tathagata Das (was: Apache Spark)
> Add TaskContext.getLocalProperties in
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Apache Spark commented on SPARK-24397:
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User 'tdas' has created a pull request for this issue:
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Apache Spark reassigned SPARK-24397:
Assignee: Apache Spark (was: Tathagata Das)
> Add TaskContext.getLocalProperties in
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Apache Spark commented on SPARK-24250:
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User 'gatorsmile' has created a pull request for this issue:
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Tathagata Das commented on SPARK-24396:
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TaskContext.getLocalProperty in Python is needed for
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Tathagata Das edited comment on SPARK-24396 at 5/26/18 12:07 AM:
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Tathagata Das updated SPARK-24397:
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Issue Type: New Feature (was: Sub-task)
Parent: (was: SPARK-24396)
> Add
Tathagata Das created SPARK-24397:
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Summary: Add TaskContext.getLocalProperties in Python
Key: SPARK-24397
URL: https://issues.apache.org/jira/browse/SPARK-24397
Project: Spark
Issue Type:
Tathagata Das created SPARK-24396:
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Summary: Add Structured Streaming ForeachWriter for python
Key: SPARK-24396
URL: https://issues.apache.org/jira/browse/SPARK-24396
Project: Spark
Issue
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Joseph K. Bradley commented on SPARK-24359:
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Regarding separating repos: What's the conclusion?
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Joseph K. Bradley updated SPARK-24359:
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Description:
h1. Background and motivation
SparkR supports calling MLlib
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Lu Wang commented on SPARK-24300:
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I will fix this issue.
> generateLDAData in ml.cluster.LDASuite
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Xiao Li resolved SPARK-24366.
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Resolution: Fixed
Assignee: Maxim Gekk
Fix Version/s: 2.4.0
> Improve error message for
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Joseph K. Bradley commented on SPARK-23455:
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Yep, thanks [~viirya] for answering! It will
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Xiao Li commented on SPARK-24369:
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Thanks!
> A bug when having multiple distinct aggregations
>
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Yinan Li commented on SPARK-24122:
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The operator does cover automatic restart of an application with a
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Miles Yucht updated SPARK-24395:
Description:
Spark does not return the correct answer when evaluating NOT IN in some cases.
For
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Joseph K. Bradley updated SPARK-24300:
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Shepherd: Joseph K. Bradley
> generateLDAData in ml.cluster.LDASuite didn't set seed
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Marcelo Vanzin reassigned SPARK-6235:
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Assignee: Marcelo Vanzin
> Address various 2G limits
> -
>
>
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Marcelo Vanzin reassigned SPARK-6235:
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Assignee: (was: Marcelo Vanzin)
> Address various 2G limits
>
Miles Yucht created SPARK-24395:
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Summary: Fix Behavior of NOT IN with Literals Containing NULL
Key: SPARK-24395
URL: https://issues.apache.org/jira/browse/SPARK-24395
Project: Spark
Issue
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Marcelo Vanzin updated SPARK-24392:
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Target Version/s: 2.3.1
> Mark pandas_udf as Experimental
> ---
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Li Jin commented on SPARK-24373:
[~smilegator] do you mean that add AnalysisBarrier to
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Bryan Cutler edited comment on SPARK-24392 at 5/25/18 9:53 PM:
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Targeting
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Marcelo Vanzin commented on SPARK-24392:
(There's a target version field for that, btw. Updating
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Bryan Cutler commented on SPARK-24392:
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Targeting 2.3.1
> Mark pandas_udf as Experimental
>
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Bryan Cutler updated SPARK-24392:
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Fix Version/s: 2.3.1
> Mark pandas_udf as Experimental
> ---
>
>
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Xiao Li commented on SPARK-24373:
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In the above example, each time when we re-analyze the plan that is
Barry Becker created SPARK-24394:
Summary: Nodes in decision tree sometimes have negative impurity
values
Key: SPARK-24394
URL: https://issues.apache.org/jira/browse/SPARK-24394
Project: Spark
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Hafthor Stefansson edited comment on SPARK-23576 at 5/25/18 9:27 PM:
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Hafthor Stefansson edited comment on SPARK-23576 at 5/25/18 9:26 PM:
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Mingjie Tang commented on SPARK-24093:
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i can add a PR for this.
> Make some fields of
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Arun Mahadevan commented on SPARK-23887:
We could probably invoke
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Yinan Li commented on SPARK-24091:
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Thanks [~tmckay]! I think the first approach is a good way of
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Hafthor Stefansson edited comment on SPARK-23576 at 5/25/18 9:14 PM:
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Marco Gaido commented on SPARK-24373:
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[~smilegator] yes, you're right, the impact would be
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Hafthor Stefansson edited comment on SPARK-23576 at 5/25/18 9:06 PM:
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Hafthor Stefansson commented on SPARK-23576:
Here's an equivalent problem:
spark.sql("select
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Xiao Li updated SPARK-24373:
Summary: "df.cache() df.count()" no longer eagerly caches data when the
analyzed plans are different after
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Xiao Li commented on SPARK-23309:
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[~vanzin] https://issues.apache.org/jira/browse/SPARK-24373 is not
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Xiao Li updated SPARK-24373:
Summary: "df.cache() df.count()" no longer eagerly caches data when the
analyzed plans are different after
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Xiao Li edited comment on SPARK-24373 at 5/25/18 8:24 PM:
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{code}
def count():
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Xiao Li edited comment on SPARK-24373 at 5/25/18 8:23 PM:
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{code}
def count():
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Xiao Li updated SPARK-24373:
Target Version/s: 2.3.1
> "df.cache() df.count()" no longer eagerly caches data
>
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Xiao Li updated SPARK-24373:
Priority: Blocker (was: Major)
> "df.cache() df.count()" no longer eagerly caches data
>
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Maxim Gekk resolved SPARK-24004.
Resolution: Won't Fix
> Tests of from_json for MapType
> --
>
>
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Xiao Li commented on SPARK-24373:
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{code}
def count(): Long = withAction("count",
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Maxim Gekk resolved SPARK-15125.
Resolution: Fixed
Fix Version/s: 2.4.0
The issue has been fixed by
Henry Robinson created SPARK-24393:
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Summary: SQL builtin: isinf
Key: SPARK-24393
URL: https://issues.apache.org/jira/browse/SPARK-24393
Project: Spark
Issue Type: New Feature
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Tomasz Gawęda commented on SPARK-24373:
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[~LI,Xiao] That is a good idea :) Eager caching is
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Marco Gaido commented on SPARK-24373:
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[~smilegator] I think an eager API is not related to the
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Li Jin commented on SPARK-24324:
Moved under Spark-22216 for better ticket organization.
> Pandas
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Li Jin updated SPARK-24324:
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Issue Type: Sub-task (was: Bug)
Parent: SPARK-22216
> Pandas Grouped Map UserDefinedFunction mixes
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Marcelo Vanzin updated SPARK-22809:
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Target Version/s: 2.4.0 (was: 2.3.1, 2.4.0)
> pyspark is sensitive to imports with dots
>
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Yinan Li commented on SPARK-24383:
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OK, then garbage collection should kick in and delete the service
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Marcelo Vanzin commented on SPARK-22809:
I'm removing 2.3.1 since it doesn't seem there's any
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Marcelo Vanzin commented on SPARK-24392:
What release is this supposed to block?
> Mark
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Xiao Li commented on SPARK-24373:
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BTW, I plan to continue my work of
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Xiao Li edited comment on SPARK-24373 at 5/25/18 5:57 PM:
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[~icexelloss]
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Li Jin commented on SPARK-24373:
We use groupby() and pivot()
> "df.cache() df.count()" no longer
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Xiao Li commented on SPARK-24373:
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[~icexelloss] [~aweise] Are you also using the Dataset APIs groupBy(),
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Apache Spark reassigned SPARK-24392:
Assignee: Apache Spark
> Mark pandas_udf as Experimental
>
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Apache Spark commented on SPARK-24392:
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User 'BryanCutler' has created a pull request for this
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Apache Spark reassigned SPARK-24392:
Assignee: (was: Apache Spark)
> Mark pandas_udf as Experimental
>
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Apache Spark commented on SPARK-24331:
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User 'mn-mikke' has created a pull request for this issue:
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Apache Spark reassigned SPARK-24331:
Assignee: Apache Spark
> Add arrays_overlap / array_repeat / map_entries
>
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Apache Spark reassigned SPARK-24331:
Assignee: (was: Apache Spark)
> Add arrays_overlap / array_repeat / map_entries
>
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Bryan Cutler updated SPARK-24392:
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Priority: Blocker (was: Critical)
> Mark pandas_udf as Experimental
>
Bryan Cutler created SPARK-24392:
Summary: Mark pandas_udf as Experimental
Key: SPARK-24392
URL: https://issues.apache.org/jira/browse/SPARK-24392
Project: Spark
Issue Type: Task
Sam Kitajima-Kimbrel created SPARK-24391:
Summary: to_json/from_json should support arrays of primitives,
and more generally all JSON
Key: SPARK-24391
URL:
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Apache Spark reassigned SPARK-23820:
Assignee: Apache Spark
> Allow the long form of call sites to be recorded in the log
>
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Apache Spark reassigned SPARK-23820:
Assignee: (was: Apache Spark)
> Allow the long form of call sites to be recorded in
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Apache Spark commented on SPARK-23820:
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User 'michaelmior' has created a pull request for this
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Marek Novotny updated SPARK-24331:
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Description:
Add SparkR equivalent to:
* arrays_overlap - SPARK-23922
* array_repeat -
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paul mackles closed SPARK-24380.
> argument quoting/escaping broken in mesos cluster scheduler
>
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paul mackles resolved SPARK-24380.
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Resolution: Duplicate
Dupe of SPARK-23941, just a different config
> argument
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Marek Novotny updated SPARK-24331:
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Summary: Add arrays_overlap / array_repeat / map_entries(was: Add
cardinality /
Ryan Foss created SPARK-24390:
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Summary: confusion of columns in projection after WITH ROLLUP
Key: SPARK-24390
URL: https://issues.apache.org/jira/browse/SPARK-24390
Project: Spark
Issue Type:
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Marco Gaido commented on SPARK-24389:
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I cannot reproduce on current master. Probably it has been
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Apache Spark reassigned SPARK-24373:
Assignee: Apache Spark
> "df.cache() df.count()" no longer eagerly caches data
>
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Apache Spark reassigned SPARK-24373:
Assignee: (was: Apache Spark)
> "df.cache() df.count()" no longer eagerly caches data
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Apache Spark commented on SPARK-24373:
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User 'mgaido91' has created a pull request for this issue:
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https://issues.apache.org/jira/browse/SPARK-19112?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=16490749#comment-16490749
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Apache Spark commented on SPARK-19112:
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User 'wangyum' has created a pull request for this issue:
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https://issues.apache.org/jira/browse/SPARK-23991?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=16490729#comment-16490729
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Apache Spark commented on SPARK-23991:
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User 'gaborgsomogyi' has created a pull request for this
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Apache Spark reassigned SPARK-23991:
Assignee: (was: Apache Spark)
> data loss when allocateBlocksToBatch
>
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Apache Spark reassigned SPARK-23991:
Assignee: Apache Spark
> data loss when allocateBlocksToBatch
>
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Marco Gaido commented on SPARK-24373:
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[~wbzhao] yes, I do agree with you. That is the problem.
>
zhanggengxin created SPARK-24389:
Summary: describe() can't work on column that name contain dots
Key: SPARK-24389
URL: https://issues.apache.org/jira/browse/SPARK-24389
Project: Spark
Issue
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https://issues.apache.org/jira/browse/SPARK-24271?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=16490499#comment-16490499
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Jami Malikzade commented on SPARK-24271:
[~ste...@apache.org] Thank you
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https://issues.apache.org/jira/browse/SPARK-24271?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=16490474#comment-16490474
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Steve Loughran commented on SPARK-24271:
Disabling the s3 cache can be pretty inefficient, as
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https://issues.apache.org/jira/browse/SPARK-17592?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Jorge Machado updated SPARK-17592:
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Comment: was deleted
(was: I'm hitting the same issue I'm afraid but in slightly another way.
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Xianjin YE commented on SPARK-24388:
I am working on this and will send a pr soon.
> EventLoop's run
Xianjin YE created SPARK-24388:
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Summary: EventLoop's run method don't handle fatal error, causes
driver hang forever
Key: SPARK-24388
URL: https://issues.apache.org/jira/browse/SPARK-24388
Project:
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https://issues.apache.org/jira/browse/SPARK-24387?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=16490309#comment-16490309
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Rui Li commented on SPARK-24387:
When HeartbeatReceiver finds the executor's heartbeat is timeout, it
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https://issues.apache.org/jira/browse/SPARK-24374?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=16490307#comment-16490307
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Wei Yan commented on SPARK-24374:
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Thanks [~mengxr] for the initiative and the doc. cc [~leftnoteasy]
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https://issues.apache.org/jira/browse/SPARK-24387?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=16490293#comment-16490293
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Rui Li commented on SPARK-24387:
A snippet of the log w/ some fields masked:
{noformat}
[Stage
Rui Li created SPARK-24387:
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Summary: Heartbeat-timeout executor is added back and used again
Key: SPARK-24387
URL: https://issues.apache.org/jira/browse/SPARK-24387
Project: Spark
Issue Type: Bug
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