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Hiroshi Takahashi commented on SPARK-10263:
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I'll work on this issue.
> Add @Since annotation
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KaiXinXIaoLei edited comment on SPARK-9776 at 9/29/15 6:14 AM:
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In security
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Saisai Shao commented on SPARK-10858:
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[~tgraves], I assume you're using yarn-cluster mode to submit
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Apache Spark commented on SPARK-10851:
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User 'sun-rui' has created a pull request for this issue:
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Apache Spark reassigned SPARK-10851:
Assignee: Apache Spark
> Exception not failing R applications (in yarn cluster mode)
>
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Apache Spark reassigned SPARK-10851:
Assignee: (was: Apache Spark)
> Exception not failing R applications (in yarn cluster
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Sun Rui commented on SPARK-10851:
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[~ztoth] does this PR fix your problem?
> Exception not failing R
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Hiroshi Takahashi commented on SPARK-10268:
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I think there are no public classes or methods
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Dilip Biswal commented on SPARK-8654:
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I would like to work on this issue..
> Analysis exception
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Apache Spark reassigned SPARK-10263:
Assignee: (was: Apache Spark)
> Add @Since annotation to ml.param and ml.*
>
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Apache Spark commented on SPARK-10263:
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User 'taishi-oss' has created a pull request for this issue:
Bryan Rivera created SPARK-10867:
Summary: df.write.partitionBy With Two Columns Collapses first
Column
Key: SPARK-10867
URL: https://issues.apache.org/jira/browse/SPARK-10867
Project: Spark
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Thomas Graves commented on SPARK-10858:
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yes its a bad thing as users don't know when # works. It
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Thomas Graves edited comment on SPARK-10858 at 9/29/15 1:06 PM:
yes its a
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Thomas Graves commented on SPARK-10858:
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Note the # is the name that we give it on the yarn side
Julien Genini created SPARK-10869:
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Summary: Auto-normalization of semi-structured schema from a
dataframe
Key: SPARK-10869
URL: https://issues.apache.org/jira/browse/SPARK-10869
Project: Spark
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Julien Genini updated SPARK-10869:
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Description:
today, you can get a multi-depth schema from a semi-structured dataframe. (XML,
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Martin Senne edited comment on SPARK-7135 at 9/29/15 10:04 AM:
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@[~rxin]:
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Martin Senne updated SPARK-10868:
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Summary: monotonicallyIncreasingId() supports offset for indexing (was:
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Chris Heller commented on SPARK-8734:
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I agree on the goal. Without a total redesign of the Spark
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David Sabater commented on SPARK-3862:
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Thanks Reynold - I am really interested in this feature and
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Martin Senne updated SPARK-10868:
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Description:
With SPARK-7135 and https://github.com/apache/spark/pull/5709
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Martin Senne commented on SPARK-7135:
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@[~rxin]: First, great feature. Unfortunately, there seems to
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Martin Senne updated SPARK-10868:
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Description:
With SPARK-7135 and https://github.com/apache/spark/pull/5709
Martin Senne created SPARK-10868:
Summary: monotonicallyIncreasingId() supports offset to start
indexing at
Key: SPARK-10868
URL: https://issues.apache.org/jira/browse/SPARK-10868
Project: Spark
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Apache Spark commented on SPARK-10490:
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User 'yanboliang' has created a pull request for this issue:
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Apache Spark reassigned SPARK-10490:
Assignee: Apache Spark
> Consolidate the Cholesky solvers in WeightedLeastSquares and ALS
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Apache Spark reassigned SPARK-10490:
Assignee: (was: Apache Spark)
> Consolidate the Cholesky solvers in
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Hans van den Bogert commented on SPARK-10474:
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I should note that I can reproduce this easily
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Apache Spark commented on SPARK-10736:
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User 'yanboliang' has created a pull request for this issue:
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Apache Spark reassigned SPARK-10736:
Assignee: (was: Apache Spark)
> Use 1 for all ratings if $(ratingCol) = ""
>
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Apache Spark reassigned SPARK-10736:
Assignee: Apache Spark
> Use 1 for all ratings if $(ratingCol) = ""
>
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Apache Spark commented on SPARK-10871:
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User 'ryan-williams' has created a pull request for this
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Peter Rudenko updated SPARK-10870:
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Description:
Very useful dataset to test pipeline because of:
# "Big data" dataset - original
Peter Rudenko created SPARK-10870:
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Summary: Criteo Display Advertising Challenge dataset
Key: SPARK-10870
URL: https://issues.apache.org/jira/browse/SPARK-10870
Project: Spark
Issue Type:
Ryan Williams created SPARK-10871:
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Summary: Specify number of failed executors in ApplicationMaster
error message
Key: SPARK-10871
URL: https://issues.apache.org/jira/browse/SPARK-10871
Project:
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Peter Rudenko updated SPARK-10870:
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Summary: Criteo Display Advertising Challenge (was: Criteo Display
Advertising Challenge
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Apache Spark reassigned SPARK-10871:
Assignee: Apache Spark
> Specify number of failed executors in ApplicationMaster error
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Apache Spark reassigned SPARK-10871:
Assignee: (was: Apache Spark)
> Specify number of failed executors in
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Julien Genini updated SPARK-10869:
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Description:
today, you can get a multi-depth schema from a semi-structured dataframe. (XML,
Thomas Graves created SPARK-10874:
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Summary: add Search box to History Page
Key: SPARK-10874
URL: https://issues.apache.org/jira/browse/SPARK-10874
Project: Spark
Issue Type: Improvement
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Thomas Graves commented on SPARK-10873:
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Note if there isn't a jira filed to fix the issue we
Thomas Graves created SPARK-10873:
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Summary: can't sort columns on history page
Key: SPARK-10873
URL: https://issues.apache.org/jira/browse/SPARK-10873
Project: Spark
Issue Type: Bug
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Thomas Graves commented on SPARK-10172:
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Was there another jira filed to really fix this problem
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Sandhya Sundaresan commented on SPARK-1493:
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Erik's proposal would certainly help us in the
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Julien Genini updated SPARK-10869:
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Description:
today, you can get a multi-depth schema from a semi-structured dataframe. (XML,
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Thomas Graves closed SPARK-6508.
Resolution: Duplicate
> error handling issue running python in yarn cluster mode
>
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Thomas Graves commented on SPARK-10873:
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evidentally this was explicitly disabled by SPARK-10172.
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Thomas Graves commented on SPARK-6951:
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I'm still seeing history server startup really slow in
Dmytro Bielievtsov created SPARK-10872:
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Summary: Derby error (XSDB6) when creating new HiveContext after
restarting SparkContext
Key: SPARK-10872
URL: https://issues.apache.org/jira/browse/SPARK-10872
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Julien Genini updated SPARK-10869:
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Description:
today, you can get a multi-depth schema from a semi-structured dataframe. (XML,
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https://issues.apache.org/jira/browse/SPARK-8734?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=14935352#comment-14935352
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Alan Braithwaite commented on SPARK-8734:
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I like this method and it's consistent with most other
Matt Cheah created SPARK-10877:
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Summary: Assertions fail straightforward DataFrame job
Key: SPARK-10877
URL: https://issues.apache.org/jira/browse/SPARK-10877
Project: Spark
Issue Type: Bug
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Matt Cheah updated SPARK-10877:
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Summary: Assertions fail straightforward DataFrame job due to word
alignment (was: Assertions fail
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Matt Cheah updated SPARK-10877:
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Attachment: SparkFilterByKeyTest.scala
I've attached the Scala script that manifests the problem on
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Davies Liu resolved SPARK-6919.
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Resolution: Fixed
Fix Version/s: 1.6.0
Issue resolved by pull request 5516
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Apache Spark reassigned SPARK-10875:
Assignee: (was: Apache Spark)
> RowMatrix.computeCovariance() result is not exactly
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Narine Kokhlikyan commented on SPARK-7245:
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Thanks for your comment ~Xiangrui Meng
Let me know if
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Apache Spark commented on SPARK-9835:
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User 'davies' has created a pull request for this issue:
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Apache Spark reassigned SPARK-9835:
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Assignee: Xiangrui Meng (was: Apache Spark)
> Iteratively reweighted least squares solver
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Apache Spark reassigned SPARK-9835:
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Assignee: Apache Spark (was: Xiangrui Meng)
> Iteratively reweighted least squares solver
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Apache Spark commented on SPARK-10671:
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User 'cloud-fan' has created a pull request for this issue:
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Xiangrui Meng updated SPARK-10058:
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Assignee: Shixiong Zhu (was: Andrew Or)
> Flaky test: HeartbeatReceiverSuite: normal
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Sean Owen updated SPARK-10782:
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Assignee: Asoka Diggs
> Duplicate examples for drop_duplicates and DropDuplicates
>
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Apache Spark reassigned SPARK-10875:
Assignee: Apache Spark
> RowMatrix.computeCovariance() result is not exactly symmetric
>
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Sean Owen resolved SPARK-10782.
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Resolution: Fixed
Fix Version/s: 1.6.0
Issue resolved by pull request 8930
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Apache Spark commented on SPARK-10875:
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User 'pnpritchard' has created a pull request for this
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Saisai Shao edited comment on SPARK-10858 at 9/30/15 5:49 AM:
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So basically
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Seth Hendrickson commented on SPARK-10788:
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[~josephkb] I'm interested in working on this issue,
Ryan Williams created SPARK-10878:
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Summary: Race condition when resolving Maven coordinates via Ivy
Key: SPARK-10878
URL: https://issues.apache.org/jira/browse/SPARK-10878
Project: Spark
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Xiangrui Meng resolved SPARK-10800.
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Resolution: Duplicate
> Flaky test: org.apache.spark.deploy.StandaloneDynamicAllocationSuite
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KaiXinXIaoLei commented on SPARK-10515:
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If the heartbeat receiver kills executors (and new ones
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Russell Alexander Spitzer commented on SPARK-9472:
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Any thoughts on back-porting this to
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Saisai Shao commented on SPARK-10858:
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So basically I think the problem is do we need to treat this
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Hyukjin Kwon updated SPARK-10030:
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Comment: was deleted
(was: Such use case issue (maybe rather question) should go to user mailing
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Saisai Shao commented on SPARK-10858:
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Hi [~tgraves], I tested again with Mac and Linux (centos),
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Sen Fang commented on SPARK-:
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Another idea is do something similar to F# TypeProvider approach:
Yun Zhao created SPARK-10879:
Summary: spark on yarn support priority option
Key: SPARK-10879
URL: https://issues.apache.org/jira/browse/SPARK-10879
Project: Spark
Issue Type: Improvement
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KaiXinXIaoLei updated SPARK-10515:
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Target Version/s: 1.6.0
Fix Version/s: 1.6.0
> When killing executor, the pending
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Saisai Shao updated SPARK-10858:
Comment: was deleted
(was: The error I got in the failed case is the same as you mentioned above,
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Apache Spark reassigned SPARK-10473:
Assignee: Apache Spark
> EventLog will loss message in the long-running security
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Apache Spark reassigned SPARK-10473:
Assignee: (was: Apache Spark)
> EventLog will loss message in the long-running
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Apache Spark commented on SPARK-10473:
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User 'SaintBacchus' has created a pull request for this
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Yun Zhao updated SPARK-10879:
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Component/s: YARN
Spark Submit
> spark on yarn support priority option
>
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Saisai Shao edited comment on SPARK-10858 at 9/30/15 3:50 AM:
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Hi
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Saisai Shao commented on SPARK-10858:
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The error I got in the failed case is the same as you
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Saisai Shao updated SPARK-10858:
Comment: was deleted
(was: The error I got in the failed case is the same as you mentioned above,
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Saisai Shao commented on SPARK-10858:
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The error I got in the failed case is the same as you
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Saisai Shao commented on SPARK-10858:
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The error I got in the failed case is the same as you
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https://issues.apache.org/jira/browse/SPARK-10879?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=14936290#comment-14936290
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Apache Spark commented on SPARK-10879:
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User 'xiaowen147' has created a pull request for this issue:
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https://issues.apache.org/jira/browse/SPARK-10473?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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SaintBacchus updated SPARK-10473:
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Affects Version/s: 1.6.0
> EventLog will loss message in the long-running security application
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https://issues.apache.org/jira/browse/SPARK-10877?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=14936259#comment-14936259
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Matt Cheah commented on SPARK-10877:
Also the error doesn't occur if I turn code-generation off
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Apache Spark reassigned SPARK-10879:
Assignee: (was: Apache Spark)
> spark on yarn support priority option
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Apache Spark reassigned SPARK-10879:
Assignee: Apache Spark
> spark on yarn support priority option
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https://issues.apache.org/jira/browse/SPARK-10857?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=14935518#comment-14935518
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Josh Rosen commented on SPARK-10857:
Spark 1.5.0+ requires Java 7+, so it should be fine to use Java
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https://issues.apache.org/jira/browse/SPARK-10875?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=14935548#comment-14935548
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Sean Owen commented on SPARK-10875:
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Makes sense to me, do you want to try a PR?
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Nick Pritchard created SPARK-10875:
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Summary: RowMatrix.computeCovariance() result is not exactly
symmetric
Key: SPARK-10875
URL: https://issues.apache.org/jira/browse/SPARK-10875
Project: Spark
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https://issues.apache.org/jira/browse/SPARK-10779?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=14935572#comment-14935572
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Evan Chen commented on SPARK-10779:
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I can work on this Jira
> Set initialModel for KMeans model in
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Marcelo Vanzin commented on SPARK-10873:
To fix this properly we'd have to change the library
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Sean Owen updated SPARK-10875:
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Priority: Minor (was: Major)
> RowMatrix.computeCovariance() result is not exactly symmetric
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