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Jiang Xingbo updated SPARK-17851:
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Description: Currently we have several tens of test sqls in catalyst will
fail at
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Guoqiang Li commented on SPARK-17930:
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If a stage contains a lot of tasks, eg one million tasks, the
Amit Baghel created SPARK-17952:
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Summary: Java SparkSession createDataFrame doesn't work with
nested Javabean
Key: SPARK-17952
URL: https://issues.apache.org/jira/browse/SPARK-17952
Project: Spark
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Amit Baghel updated SPARK-17952:
Description:
As per latest spark documentation at
Tae Jun Kim created SPARK-17953:
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Summary: Fix typo in SparkSession scaladoc
Key: SPARK-17953
URL: https://issues.apache.org/jira/browse/SPARK-17953
Project: Spark
Issue Type: Documentation
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Amit Baghel updated SPARK-17952:
Description:
As per latest spark documentation for Java at
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Amit Baghel updated SPARK-17952:
Description:
As per latest spark documentation at
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Amit Baghel updated SPARK-17952:
Description:
As per latest spark documentation at
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Amit Baghel updated SPARK-17952:
Description:
As per latest spark documentation at
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Amit Baghel updated SPARK-17952:
Summary: Java SparkSession createDataFrame method throws exception for
nested JavaBeans (was:
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Amit Baghel updated SPARK-17952:
Summary: Java SparkSession createDataFrame method throws exception with
nested Javabean (was:
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Apache Spark commented on SPARK-17953:
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User 'tae-jun' has created a pull request for this issue:
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Apache Spark reassigned SPARK-17953:
Assignee: (was: Apache Spark)
> Fix typo in SparkSession scaladoc
>
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Apache Spark reassigned SPARK-17953:
Assignee: Apache Spark
> Fix typo in SparkSession scaladoc
>
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Sean Owen commented on SPARK-17945:
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You can just set this with the S3 APIs directly? this borders or
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Reynold Xin resolved SPARK-17953.
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Resolution: Fixed
Assignee: Tae Jun Kim
Fix Version/s: 2.1.0
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Sean Owen commented on SPARK-17950:
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Doesn't that make a potentially huge array every time this is
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Sean Owen updated SPARK-17953:
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Priority: Trivial (was: Minor)
> Fix typo in SparkSession scaladoc
>
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Reynold Xin updated SPARK-16845:
Target Version/s: 2.1.0
>
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Sean Owen updated SPARK-17951:
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Description:
The following code demonstrates the issue:
{code}
def main(args: Array[String]): Unit =
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Sean Owen commented on SPARK-17951:
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I'm not sure this suggests a problem with Spark. It's a very small
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Sean Owen commented on SPARK-17944:
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Yes, for example `hostname` differs on OS X / Linux but the
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Sean Owen resolved SPARK-17936.
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Resolution: Fixed
Assignee: Takuya Ueshin
Fix Version/s: 2.1.0
OK, if you're pretty
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Sean Owen commented on SPARK-14887:
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Possibly resolved by
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Sean Owen commented on SPARK-17930:
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Maybe so; I think the question is whether this would cause it to
Vitaly Gerasimov created SPARK-17954:
Summary: FetchFailedException executor cannot connect to another
worker executor
Key: SPARK-17954
URL: https://issues.apache.org/jira/browse/SPARK-17954
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Vitaly Gerasimov updated SPARK-17954:
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Issue Type: Bug (was: Question)
> FetchFailedException executor cannot connect to
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Hyukjin Kwon commented on SPARK-14428:
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For 1. I guess this was fixed in
Hyukjin Kwon created SPARK-17955:
Summary: Use the same read path in DataFrameReader.jdbc and
DataFrameReader.format("jdbc")
Key: SPARK-17955
URL: https://issues.apache.org/jira/browse/SPARK-17955
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Apache Spark commented on SPARK-17955:
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User 'HyukjinKwon' has created a pull request for this
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Apache Spark reassigned SPARK-17955:
Assignee: Apache Spark
> Use the same read path in DataFrameReader.jdbc and
>
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Apache Spark reassigned SPARK-17955:
Assignee: (was: Apache Spark)
> Use the same read path in DataFrameReader.jdbc and
>
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Jeff Schobelock commented on SPARK-17945:
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That's true enough. The use case on my end is that we
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ding edited comment on SPARK-17951 at 10/16/16 12:22 AM:
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I tried to call
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Mridul Muralidharan updated SPARK-17637:
Affects Version/s: 2.1.0
> Packed scheduling for Spark tasks across executors
>
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Mridul Muralidharan resolved SPARK-17637.
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Resolution: Fixed
Assignee: Zhan Zhang
Target Version/s:
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Reynold Xin commented on SPARK-17865:
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Alright in this case I don't think we need R API for now.
>
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Amit Baghel updated SPARK-17952:
Description:
As per latest spark documentation for Java at
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Amit Baghel updated SPARK-17952:
Description:
As per latest spark documentation for Java at
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Amit Baghel updated SPARK-17952:
Description:
As per latest spark documentation for Java at
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Ofir Manor commented on SPARK-17812:
I think Michael suggest that if you use {{startingOffsets}}
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ding commented on SPARK-17951:
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I tried to call rdd.collect which internally called bm.getRemoteBytes in
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Mridul Muralidharan updated SPARK-17637:
Fix Version/s: 2.1.0
> Packed scheduling for Spark tasks across executors
>
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Reynold Xin closed SPARK-17865.
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Resolution: Not A Problem
> R API for global temp view
> --
>
>
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Lars Francke commented on SPARK-650:
I also have to disagree with this being a duplicate or obsolete.
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Cody Koeninger commented on SPARK-17812:
As you just said yourself, assign doesn't mean you
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Lars Francke commented on SPARK-650:
I can only come up with three reasons at the moment. I hope they
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Linbo commented on SPARK-17957:
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cc [~smilegator]
> Calling outer join and na.fill(0) and then inner join
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Apache Spark commented on SPARK-17812:
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User 'koeninger' has created a pull request for this issue:
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Apache Spark reassigned SPARK-17812:
Assignee: Cody Koeninger (was: Apache Spark)
> More granular control of starting offsets
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Apache Spark reassigned SPARK-17812:
Assignee: Apache Spark (was: Cody Koeninger)
> More granular control of starting offsets
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Sean Owen reopened SPARK-650:
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As you wish, but, I disagree with this type of reasoning about JIRAs. I dont
think anyone has addressed why a
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Linbo edited comment on SPARK-17957 at 10/16/16 2:26 AM:
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cc [~smilegator] and
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Linbo updated SPARK-17957:
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Description:
I reported a similar bug two months ago and it's fixed in Spark 2.0.1:
Linbo created SPARK-17957:
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Summary: Calling outer join and na.fill(0) and then inner join
will miss rows
Key: SPARK-17957
URL: https://issues.apache.org/jira/browse/SPARK-17957
Project: Spark
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Saikat Kanjilal commented on SPARK-9487:
Synched the code, am familiarizing myself first with how
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Lars Francke edited comment on SPARK-650 at 10/15/16 11:22 PM:
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I can only
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Reynold Xin reopened SPARK-17637:
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> Packed scheduling for Spark tasks across executors
>
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Reynold Xin commented on SPARK-17637:
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Note: I reverted the commit due to quality issues. We can
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Linbo commented on SPARK-17957:
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Thank you!
> Calling outer join and na.fill(0) and then inner join will
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Tejas Patil commented on SPARK-17954:
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I agree with [~srowen]'s comment about this being more of a
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Xiao Li commented on SPARK-17957:
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You can see the plan. The optimized plan is still full outer join. : )
dianwei Han created SPARK-17958:
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Summary: Why I ran into issue " accumulator, copyandreset must be
zero error"
Key: SPARK-17958
URL: https://issues.apache.org/jira/browse/SPARK-17958
Project: Spark
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Apache Spark reassigned SPARK-17637:
Assignee: Zhan Zhang (was: Apache Spark)
> Packed scheduling for Spark tasks across
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Apache Spark reassigned SPARK-17637:
Assignee: Apache Spark (was: Zhan Zhang)
> Packed scheduling for Spark tasks across
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Xiao Li commented on SPARK-17957:
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Thank you for reporting it. Let me do a quick check.
> Calling outer
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Xiao Li updated SPARK-17957:
Priority: Critical (was: Major)
> Calling outer join and na.fill(0) and then inner join will miss rows
>
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Xiao Li updated SPARK-17957:
Target Version/s: 2.0.2, 2.1.0 (was: 2.0.2)
> Calling outer join and na.fill(0) and then inner join will
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Xiao Li updated SPARK-17957:
Labels: correctness (was: joins na.fill)
> Calling outer join and na.fill(0) and then inner join will
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Shixiong Zhu commented on SPARK-13747:
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[~chinwei] could you post the stack trace here?
>
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Xiao Li commented on SPARK-17957:
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Found the bug.
{noformat}
Project [a#29, b#30, c#31, d#48]
+- Join
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Sean Owen commented on SPARK-17954:
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Lots of things changed. I think you need to first confirm
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Cody Koeninger commented on SPARK-17938:
There was pretty extensive discussion of this on list,
Liang-Chi Hsieh created SPARK-17956:
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Summary: ProjectExec has incorrect outputOrdering property
Key: SPARK-17956
URL: https://issues.apache.org/jira/browse/SPARK-17956
Project: Spark
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Sean Owen commented on SPARK-17954:
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Is this not just a networking or IP/hostname problem? it says it
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zhangxinyu commented on SPARK-17935:
I will try it on 0.10 in the future. But as I know most of users
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Olivier Armand commented on SPARK-650:
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Sean, a singleton is not the best option in our case. The
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Felix Cheung commented on SPARK-17865:
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I see. So then we could either omit the support for global
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Hyukjin Kwon commented on SPARK-17838:
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I am trying to work on this but I don't mind if anyone takes
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Michael Schmeißer commented on SPARK-636:
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I agree, that's why I also feel that these issues are no
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Sean Owen commented on SPARK-650:
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If you need init to happen ASAP when the driver starts, isn't any
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Hyukjin Kwon commented on SPARK-17878:
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Yes, this might not be a reason to block this feature.
It
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Apache Spark reassigned SPARK-17956:
Assignee: (was: Apache Spark)
> ProjectExec has incorrect outputOrdering property
>
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Apache Spark commented on SPARK-17956:
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User 'viirya' has created a pull request for this issue:
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Apache Spark reassigned SPARK-17956:
Assignee: Apache Spark
> ProjectExec has incorrect outputOrdering property
>
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Susan X. Huynh commented on SPARK-11524:
I would like to work on this. What are the missing
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Cody Koeninger commented on SPARK-17935:
Why is this in kafka-0-8, when we haven't resolved (for
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Apache Spark reassigned SPARK-17892:
Assignee: Xiao Li (was: Apache Spark)
> Query in CTAS is Optimized Twice (branch-2.0)
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https://issues.apache.org/jira/browse/SPARK-17892?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=15578300#comment-15578300
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Apache Spark commented on SPARK-17892:
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User 'gatorsmile' has created a pull request for this issue:
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https://issues.apache.org/jira/browse/SPARK-17892?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Apache Spark reassigned SPARK-17892:
Assignee: Apache Spark (was: Xiao Li)
> Query in CTAS is Optimized Twice (branch-2.0)
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https://issues.apache.org/jira/browse/SPARK-650?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=15578338#comment-15578338
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Sean Owen commented on SPARK-650:
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In practice, these should probably all be WontFix as it hasn't mattered
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https://issues.apache.org/jira/browse/SPARK-650?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=15578361#comment-15578361
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Michael Schmeißer commented on SPARK-650:
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Then somebody should please explain to me, how this
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https://issues.apache.org/jira/browse/SPARK-650?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=15578378#comment-15578378
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Sean Owen commented on SPARK-650:
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Sorry, I mean the _status_ doesn't matter. Most issues this old are
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https://issues.apache.org/jira/browse/SPARK-650?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=15578289#comment-15578289
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Michael Schmeißer commented on SPARK-650:
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I disagree that those issues are duplicates. Spark-636
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https://issues.apache.org/jira/browse/SPARK-17878?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=15578607#comment-15578607
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Hossein Falaki commented on SPARK-17878:
I think moving it to another ticket is a good idea. One
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https://issues.apache.org/jira/browse/SPARK-17709?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=15578200#comment-15578200
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Ashish Shrowty commented on SPARK-17709:
Oh .. sorry .. I misread. Will try with 2.0.1 later
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https://issues.apache.org/jira/browse/SPARK-17954?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=15578539#comment-15578539
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Vitaly Gerasimov commented on SPARK-17954:
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I don't think so. Spark 1.6 works fine in this case.
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