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Alexey Zotov edited comment on SPARK-16917 at 8/12/16 5:24 AM:
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[~sowen]
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Alexey Zotov commented on SPARK-16917:
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[~sowen]
[~c...@koeninger.org]
It really seems to be
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Dongjoon Hyun commented on SPARK-16975:
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Hi, [~rxin].
Could you review this PR?
> Spark-2.0.0
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Apache Spark reassigned SPARK-17019:
Assignee: Apache Spark
> Expose off-heap memory usage in various places
>
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Apache Spark reassigned SPARK-17019:
Assignee: (was: Apache Spark)
> Expose off-heap memory usage in various places
>
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Apache Spark commented on SPARK-17019:
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User 'jerryshao' has created a pull request for this issue:
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https://issues.apache.org/jira/browse/SPARK-16434?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Wenchen Fan updated SPARK-16434:
Assignee: Hyukjin Kwon
> Avoid record-per type dispatch in JSON when reading
>
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Wenchen Fan resolved SPARK-16434.
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Resolution: Fixed
Fix Version/s: 2.1.0
Issue resolved by pull request 14102
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Marcelo Vanzin resolved SPARK-13081.
Resolution: Fixed
Assignee: Jeff Zhang
Fix Version/s: 2.1.0
> Allow set
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Apache Spark commented on SPARK-16955:
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User 'clockfly' has created a pull request for this issue:
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https://issues.apache.org/jira/browse/SPARK-6235?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=15418225#comment-15418225
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Guoqiang Li commented on SPARK-6235:
I'm doing this work and I'll put the patch in this month.
>
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Andrew Ash commented on SPARK-17029:
Note RDD form usage from
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Apache Spark reassigned SPARK-17029:
Assignee: (was: Apache Spark)
> Dataset toJSON goes through RDD form instead of
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Miao Wang commented on SPARK-16578:
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OK. I will check with Junyang.
> Configurable hostname for
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Apache Spark commented on SPARK-17029:
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User 'robert3005' has created a pull request for this issue:
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Apache Spark reassigned SPARK-17029:
Assignee: Apache Spark
> Dataset toJSON goes through RDD form instead of transforming
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Shixiong Zhu closed SPARK-17028.
Resolution: Won't Fix
> Backport SI-9734 for Scala 2.10
> ---
>
>
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Apache Spark reassigned SPARK-17027:
Assignee: (was: Apache Spark)
> PolynomialExpansion.choose is prone to integer
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Apache Spark reassigned SPARK-17027:
Assignee: Apache Spark
> PolynomialExpansion.choose is prone to integer overflow
>
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Apache Spark commented on SPARK-16883:
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User 'wangmiao1981' has created a pull request for this
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Apache Spark reassigned SPARK-16883:
Assignee: (was: Apache Spark)
> SQL decimal type is not properly cast to number when
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Apache Spark reassigned SPARK-16883:
Assignee: Apache Spark
> SQL decimal type is not properly cast to number when collecting
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Apache Spark commented on SPARK-17027:
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User 'zero323' has created a pull request for this issue:
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Xin Ren resolved SPARK-17026.
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Resolution: Not A Problem
> warning msg in MulticlassMetricsSuite
>
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Apache Spark commented on SPARK-16803:
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User 'gatorsmile' has created a pull request for this issue:
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Maciej Szymkiewicz edited comment on SPARK-17027 at 8/11/16 10:38 PM:
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Apache Spark reassigned SPARK-17028:
Assignee: Apache Spark
> Backport SI-9734 for Scala 2.10
>
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Apache Spark commented on SPARK-17028:
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User 'zsxwing' has created a pull request for this issue:
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https://issues.apache.org/jira/browse/SPARK-17014?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Sean Owen resolved SPARK-17014.
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Resolution: Invalid
Believe this was opened in error as a duplicate
> arithmetic.sql
>
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Apache Spark reassigned SPARK-17028:
Assignee: (was: Apache Spark)
> Backport SI-9734 for Scala 2.10
>
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Sean Owen commented on SPARK-17027:
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Is the problem in the naive calculation of n choose k?
{code}
Shixiong Zhu created SPARK-17028:
Summary: Backport SI-9734 for Scala 2.10
Key: SPARK-17028
URL: https://issues.apache.org/jira/browse/SPARK-17028
Project: Spark
Issue Type: Bug
Maciej Szymkiewicz created SPARK-17027:
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Summary: PolynomialExpansion.choose is prone to integer overflow
Key: SPARK-17027
URL: https://issues.apache.org/jira/browse/SPARK-17027
Project: Spark
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Marcelo Vanzin resolved SPARK-17022.
Resolution: Fixed
Assignee: Tao Wang
Fix Version/s: 2.1.0
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Marcelo Vanzin resolved SPARK-16868.
Resolution: Fixed
Assignee: carlmartin
Fix Version/s: 2.1.0
> Executor
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Marcelo Vanzin resolved SPARK-13602.
Resolution: Fixed
Assignee: Bryan Cutler
Fix Version/s: 2.1.0
>
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Apache Spark reassigned SPARK-17026:
Assignee: Apache Spark
> warning msg in MulticlassMetricsSuite
>
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Apache Spark commented on SPARK-17026:
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User 'keypointt' has created a pull request for this issue:
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Apache Spark reassigned SPARK-17026:
Assignee: (was: Apache Spark)
> warning msg in MulticlassMetricsSuite
>
Xin Ren created SPARK-17026:
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Summary: warning msg in MulticlassMetricsSuite
Key: SPARK-17026
URL: https://issues.apache.org/jira/browse/SPARK-17026
Project: Spark
Issue Type: Improvement
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Apache Spark commented on SPARK-17013:
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User 'petermaxlee' has created a pull request for this
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https://issues.apache.org/jira/browse/SPARK-3577?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=15417929#comment-15417929
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Kay Ousterhout commented on SPARK-3577:
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I believe spill time will currently be displayed as part of
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Apache Spark commented on SPARK-16905:
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User 'davies' has created a pull request for this issue:
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https://issues.apache.org/jira/browse/SPARK-17018?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Reynold Xin resolved SPARK-17018.
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Resolution: Fixed
Assignee: Peter Lee
Fix Version/s: 2.1.0
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Tzach Zohar commented on SPARK-3577:
Does this mean that currently, spill time will be displayed as
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Sean Owen commented on SPARK-16784:
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Oh, I really meant {{log4j.configuration}} to specify your own
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Sean Owen commented on SPARK-16993:
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You would need to show some code or more about the error.
>
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Michael Gummelt edited comment on SPARK-16784 at 8/11/16 8:11 PM:
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Michael Gummelt commented on SPARK-16784:
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`log4j.debug=true` only results in log4j printing its
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Michael Gummelt reopened SPARK-16784:
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`log4j.debug=true` only results in log4j printing its debugging messages. It
doesn't turn
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Michael Gummelt edited comment on SPARK-16784 at 8/11/16 8:10 PM:
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Michael Gummelt updated SPARK-16784:
Comment: was deleted
(was: `log4j.debug=true` only results in log4j printing its debugging
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Dulaj Rajitha commented on SPARK-16993:
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But the thing is if add dummy column as as the label
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Iaroslav Zeigerman resolved SPARK-17024.
Resolution: Duplicate
> Weird behaviour of the DataFrame when a column name
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Sean Owen commented on SPARK-17024:
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There are many issues that sound like this, like
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Nicholas Chammas edited comment on SPARK-17025 at 8/11/16 7:33 PM:
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cc
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Iaroslav Zeigerman commented on SPARK-17024:
If I query this way (with backquotes for
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Nicholas Chammas edited comment on SPARK-17025 at 8/11/16 7:27 PM:
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cc
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Nicholas Chammas commented on SPARK-17025:
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cc [~josephkb] [~mengxr]
> Cannot persist PySpark
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Iaroslav Zeigerman commented on SPARK-17024:
If this behaviour is expected, is there a way to
Nicholas Chammas created SPARK-17025:
Summary: Cannot persist PySpark ML Pipeline model that includes
custom Transformer
Key: SPARK-17025
URL: https://issues.apache.org/jira/browse/SPARK-17025
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Iaroslav Zeigerman updated SPARK-17024:
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Summary: Weird behaviour of the DataFrame when a column name contains dots.
(was:
Iaroslav Zeigerman created SPARK-17024:
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Summary: Weird behaviour of the DataFrame when the column name
contains dots.
Key: SPARK-17024
URL: https://issues.apache.org/jira/browse/SPARK-17024
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Iaroslav Zeigerman updated SPARK-17024:
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Description:
When a column name contains dots and one of the segment in a name is
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Yin Huai resolved SPARK-17021.
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Resolution: Fixed
Fix Version/s: 2.1.0
Issue resolved by pull request 14603
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Reynold Xin updated SPARK-17015:
Fix Version/s: 2.0.1
> group-by-ordinal and order-by-ordinal test cases
>
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Reynold Xin updated SPARK-17016:
Fix Version/s: 2.0.1
> group-by/order-by ordinal should throw AnalysisException instead of
>
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Apache Spark reassigned SPARK-17023:
Assignee: (was: Apache Spark)
> Update Kafka connetor to use Kafka 0.10.0.1
>
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Apache Spark reassigned SPARK-17023:
Assignee: Apache Spark
> Update Kafka connetor to use Kafka 0.10.0.1
>
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Apache Spark commented on SPARK-17023:
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User 'lresende' has created a pull request for this issue:
Luciano Resende created SPARK-17023:
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Summary: Update Kafka connetor to use Kafka 0.10.0.1
Key: SPARK-17023
URL: https://issues.apache.org/jira/browse/SPARK-17023
Project: Spark
Issue
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Shivaram Venkataraman commented on SPARK-16577:
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Good point - Let me check this with
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Shivaram Venkataraman commented on SPARK-16519:
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Yeah I think the simplest thing to do is
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Apache Spark reassigned SPARK-17022:
Assignee: Apache Spark
> Potential deadlock in driver handling message
>
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Apache Spark commented on SPARK-17022:
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User 'WangTaoTheTonic' has created a pull request for this
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Apache Spark reassigned SPARK-17022:
Assignee: (was: Apache Spark)
> Potential deadlock in driver handling message
>
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https://issues.apache.org/jira/browse/SPARK-16958?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Davies Liu resolved SPARK-16958.
Resolution: Fixed
Fix Version/s: 2.1.0
Issue resolved by pull request 14548
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Felix Cheung edited comment on SPARK-16519 at 8/11/16 4:40 PM:
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since we
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Felix Cheung commented on SPARK-16519:
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since we are undecided on what to export for RDD, should we
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Felix Cheung edited comment on SPARK-16577 at 8/11/16 4:36 PM:
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I found
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Felix Cheung commented on SPARK-16577:
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I found that to run the cran check on PDF it requires these
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Sean Owen updated SPARK-16831:
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Fix Version/s: (was: 1.6.3)
> CrossValidator reports incorrect avgMetrics
>
Tao Wang created SPARK-17022:
Summary: Potential deadlock in driver handling message
Key: SPARK-17022
URL: https://issues.apache.org/jira/browse/SPARK-17022
Project: Spark
Issue Type: Bug
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Roi Reshef edited comment on SPARK-17020 at 8/11/16 2:09 PM:
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Nevertheless,
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Roi Reshef edited comment on SPARK-17020 at 8/11/16 2:09 PM:
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Nevertheless,
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Roi Reshef commented on SPARK-17020:
Nevertheless, any attempt to repartition the resulting RDD also
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Sean Owen commented on SPARK-17020:
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I see, I was asking because you show the results of caching a
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Roi Reshef commented on SPARK-17020:
The problem occurs only when calling **.rdd** on an
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Sean Owen commented on SPARK-17020:
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Yeah, after it's cached and the partitions are established, I'd
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Roi Reshef commented on SPARK-17020:
Also note that I have just called:
*data.cache().count()*
val
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Roi Reshef commented on SPARK-17020:
val ab = SomeReader.read(...) //some reader function that uses
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Sean Owen commented on SPARK-17020:
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I think that's probably material, yes, as is the operations that
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https://issues.apache.org/jira/browse/SPARK-16975?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=15417240#comment-15417240
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Dongjoon Hyun commented on SPARK-16975:
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Great! Thank you for confirming.
> Spark-2.0.0 unable to
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Sean Owen updated SPARK-17020:
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Priority: Major (was: Critical)
> Materialization of RDD via DataFrame.rdd forces a poor
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https://issues.apache.org/jira/browse/SPARK-17021?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=15417230#comment-15417230
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Apache Spark commented on SPARK-17021:
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User 'cloud-fan' has created a pull request for this issue:
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Apache Spark reassigned SPARK-17021:
Assignee: Wenchen Fan (was: Apache Spark)
> simplify the constructor parameters of
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Apache Spark reassigned SPARK-17021:
Assignee: Apache Spark (was: Wenchen Fan)
> simplify the constructor parameters of
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Roi Reshef commented on SPARK-17020:
[~srowen] Should there be any effect on this if I cached and
Wenchen Fan created SPARK-17021:
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Summary: simplify the constructor parameters of QuantileSummaries
Key: SPARK-17021
URL: https://issues.apache.org/jira/browse/SPARK-17021
Project: Spark
Issue
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Roi Reshef edited comment on SPARK-17020 at 8/11/16 1:13 PM:
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[~srowen] I
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