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Apache Spark reassigned SPARK-10670:
Assignee: (was: Apache Spark)
> Link to each language's API in codetabs in ML docs:
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Apache Spark reassigned SPARK-10670:
Assignee: Apache Spark
> Link to each language's API in codetabs in ML docs: spark.ml
>
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Liang-Chi Hsieh commented on SPARK-8386:
[~phaumer] I can't reproduce this problem. Can you give
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Jonathan Kelly commented on SPARK-10790:
I did search through all dynamicAllocation-related JIRAs
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Sean Owen updated SPARK-10792:
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Priority: Minor (was: Major)
> Spark streaming + YARN – executor is not re-created on machine restart
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Adrian Tanase commented on SPARK-10792:
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https://issues.apache.org/jira/browse/SPARK-8297 seems to
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Sean Owen commented on SPARK-10792:
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I wonder if this is interacting with a blacklist mechanism? sort
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Adrian Tanase updated SPARK-10792:
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Description:
We’re using spark streaming (1.4.0), deployed on AWS through yarn. It’s a
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Adrian Tanase updated SPARK-10792:
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Priority: Major (was: Minor)
> Spark streaming + YARN – executor is not re-created on machine
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Adrian Tanase updated SPARK-10792:
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Priority: Minor (was: Major)
> Spark streaming + YARN – executor is not re-created on machine
Anilkumar Kalshetti created SPARK-10794:
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Summary: Spark-SQL- select query on table column with binary Data
Type displays error message- java.lang.ClassCastException: java.lang.String
cannot be cast to [B
Key: SPARK-10794
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simon.lou commented on SPARK-7483:
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kyro not support ListBuffer because ListBuffer don't have any "zero
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Anilkumar Kalshetti updated SPARK-10794:
Description:
Spark-SQL connected to Hive Metastore-- MapR5.0 has Hive 1.0.0
Use
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simon.lou commented on SPARK-7483:
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kyro not support ListBuffer because ListBuffer don't have any "zero
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Adrian Tanase commented on SPARK-10792:
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Correct - I forgot to attach a screenshot where this is
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Steve Loughran commented on SPARK-10793:
Leaving the sqp/hive parser integration alone, this is
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Apache Spark commented on SPARK-9346:
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User 'viirya' has created a pull request for this issue:
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Apache Spark reassigned SPARK-9346:
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Assignee: (was: Apache Spark)
> Conversion is applied three times on partitioned data
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Apache Spark reassigned SPARK-9346:
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Assignee: Apache Spark
> Conversion is applied three times on partitioned data sources that
Harshit created SPARK-10795:
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Summary: FileNotFoundException while deploying pyspark job on
cluster
Key: SPARK-10795
URL: https://issues.apache.org/jira/browse/SPARK-10795
Project: Spark
Issue
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Adrian Tanase updated SPARK-10792:
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Attachment: Screen Shot 2015-09-21 at 1.58.28 PM.png
> Spark streaming + YARN – executor is
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Adrian Tanase commented on SPARK-10792:
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Yarn side or Spark side? If it does, shouldn't that also
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Sean Owen commented on SPARK-10792:
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Both potentially, though I mean the Spark side. In 6 it is
Steve Loughran created SPARK-10793:
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Summary: Make sparks use/subclassing of hive more maintainable
Key: SPARK-10793
URL: https://issues.apache.org/jira/browse/SPARK-10793
Project: Spark
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simon.lou updated SPARK-7483:
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Comment: was deleted
(was: kyro not support ListBuffer because ListBuffer don't have any "zero
argument
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Anilkumar Kalshetti updated SPARK-10794:
Attachment: binaryDataType.png
testbinary.txt
> Spark-SQL- select
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Harshit updated SPARK-10795:
Description:
I am trying to run simple spark job using pyspark, it works as standalone , but
while I
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Jonathan Kelly updated SPARK-10789:
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Component/s: Spark Submit
> Cluster mode SparkSubmit classpath only includes Spark classpath
Adrian Tanase created SPARK-10792:
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Summary: Spark streaming + YARN – executor is not re-created on
machine restart
Key: SPARK-10792
URL: https://issues.apache.org/jira/browse/SPARK-10792
Project:
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Bo soon Park commented on SPARK-10773:
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I also so this error like this in mapr-spark-1.4.1
[Code]
Jonathan Kelly created SPARK-10790:
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Summary: Dynamic Allocation does not request any executors if
first stage needs less than or equal to spark.dynamicAllocation.initialExecutors
Key: SPARK-10790
URL:
Marko Asplund created SPARK-10791:
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Summary: Optimize MLlib LDA topic distribution query performance
Key: SPARK-10791
URL: https://issues.apache.org/jira/browse/SPARK-10791
Project: Spark
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Sean Owen commented on SPARK-10790:
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In your email I think you said you were using 1.4.1; just to be
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Jonathan Kelly updated SPARK-10789:
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Description:
When using cluster deploy mode, the classpath of the SparkSubmit process that
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Sean Owen commented on SPARK-10790:
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[~jonathak] A number of quite similar sounding things were fixed
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Sean Owen commented on SPARK-10644:
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How many cores per executor? I'm assuming you mean 1 and have
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Apache Spark commented on SPARK-10670:
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User 'hhbyyh' has created a pull request for this issue:
Jonathan Kelly created SPARK-10789:
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Summary: Cluster mode SparkSubmit classpath only includes Spark
classpath
Key: SPARK-10789
URL: https://issues.apache.org/jira/browse/SPARK-10789
Project: Spark
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Zsolt Tóth commented on SPARK-10487:
Increasing the perm size on the driver fixes the OOM:
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Apache Spark commented on SPARK-10778:
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User 'y-shimizu' has created a pull request for this issue:
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Apache Spark reassigned SPARK-10778:
Assignee: Apache Spark
> Implement toString for AssociationRules.Rule
>
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Apache Spark reassigned SPARK-10778:
Assignee: (was: Apache Spark)
> Implement toString for AssociationRules.Rule
>
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Apache Spark commented on SPARK-6028:
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User 'zsxwing' has created a pull request for this issue:
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Yi Zhou commented on SPARK-10474:
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Hi [~andrewor14] [~yhuai]. It's OK for me and get no errors. Thanks !
SuYan created SPARK-10796:
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Summary: The Stage taskSets may are all removed while stage still
have pending partitions after having lost some executors
Key: SPARK-10796
URL:
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Kai Jiang commented on SPARK-10688:
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Working on it~
> Python API for AFTSurvivalRegression
>
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Zoltán Zvara commented on SPARK-10797:
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I have prepared a solution for this, because I had to
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Dev Lakhani updated SPARK-10798:
Description:
When trying to create an RDD of Rows using a Java Spark Context:
List rows= new
Zoltán Zvara created SPARK-10797:
Summary: RDD's coalesce should not write out the temporary key
Key: SPARK-10797
URL: https://issues.apache.org/jira/browse/SPARK-10797
Project: Spark
Issue
Dev Lakhani created SPARK-10798:
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Summary: JsonMappingException with Spark Context Parallelize
Key: SPARK-10798
URL: https://issues.apache.org/jira/browse/SPARK-10798
Project: Spark
Issue
Xiangrui Meng created SPARK-10799:
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Summary: Flaky test: org.apache.spark.rpc.netty.InboxSuite.post:
multiple threads
Key: SPARK-10799
URL: https://issues.apache.org/jira/browse/SPARK-10799
Project:
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Xiangrui Meng updated SPARK-10799:
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Labels: flaky-test (was: )
> Flaky test: org.apache.spark.rpc.netty.InboxSuite.post: multiple
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Xiangrui Meng reopened SPARK-10651:
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I think timeout doesn't work well. Saw more failures:
Xiangrui Meng created SPARK-10800:
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Summary: Flaky test:
org.apache.spark.deploy.StandaloneDynamicAllocationSuite
Key: SPARK-10800
URL: https://issues.apache.org/jira/browse/SPARK-10800
Project:
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Apache Spark reassigned SPARK-10799:
Assignee: Apache Spark (was: Shixiong Zhu)
> Flaky test:
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Apache Spark commented on SPARK-10799:
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User 'zsxwing' has created a pull request for this issue:
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Apache Spark reassigned SPARK-10799:
Assignee: Shixiong Zhu (was: Apache Spark)
> Flaky test:
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Gianmario Spacagna updated SPARK-10801:
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Summary: StatCounter uses mutability and is not thread-safe (was:
StatCounter uses
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Gianmario Spacagna updated SPARK-10801:
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Description:
The current implementation of org.apache.spark.util.StatCounter is
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Xiangrui Meng updated SPARK-10651:
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Fix Version/s: (was: 1.6.0)
> Flaky test: BroadcastSuite
> --
>
>
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Gianmario Spacagna updated SPARK-10801:
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Affects Version/s: 1.0.0
> StatCounter uses mutability and is not thread-safe
>
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Xiangrui Meng updated SPARK-10778:
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Assignee: shimizu yoshihiro
> Implement toString for AssociationRules.Rule
>
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Jonathan Kelly updated SPARK-10789:
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Summary: Cluster mode SparkSubmit classpath only includes Spark assembly
(was: Cluster mode
Gianmario Spacagna created SPARK-10801:
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Summary: StatCounter uses mutability, is not thread-safe and hard
to understand its implementation
Key: SPARK-10801
URL:
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Jonathan Kelly commented on SPARK-10790:
Yes, this is on Spark 1.5.0. That's why I chose 1.5.0
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Sean Owen commented on SPARK-10801:
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Are you suggesting it be immutable? I think that would be much
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Xiangrui Meng updated SPARK-10670:
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Assignee: yuhao yang
> Link to each language's API in codetabs in ML docs: spark.ml
>
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Sean Owen updated SPARK-10790:
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Priority: Major (was: Critical)
Yeah if so then ignore most of this since I thought you were on
Tomasz Bartczak created SPARK-10802:
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Summary: Let ALS recommend for subset of data
Key: SPARK-10802
URL: https://issues.apache.org/jira/browse/SPARK-10802
Project: Spark
Issue Type:
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Konstantinos Kougios commented on SPARK-5928:
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Is there a work around for this?
> Remote
Cheng Lian created SPARK-10803:
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Summary: Allow users to write and query Parquet user-defined
key-value metadata directly
Key: SPARK-10803
URL: https://issues.apache.org/jira/browse/SPARK-10803
Project:
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Yin Huai commented on SPARK-10741:
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[~ianlcsd] Can you try the following queries to see if you can
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Gayathri Murali commented on SPARK-10688:
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I started working on it as well. Since there isnt a
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Sean Owen commented on SPARK-10802:
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You can already pass an RDD of user,item pairs. I think that's
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Yin Huai commented on SPARK-10741:
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Any error?
> Hive Query Having/OrderBy against Parquet table is not
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Ian edited comment on SPARK-10741 at 9/24/15 6:46 PM:
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Two of my tests failed. The
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Neal Yin commented on SPARK-6028:
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[~rxin] I am wondering why spark wants to remove AKKA dependence? Is
Davies Liu created SPARK-10810:
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Summary: Improve session management for SQL
Key: SPARK-10810
URL: https://issues.apache.org/jira/browse/SPARK-10810
Project: Spark
Issue Type: Bug
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Thomas Graves commented on SPARK-10735:
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The issue here appears to be that in spark 1.4.1 it would
Antonio Piccolboni created SPARK-10804:
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Summary: "LOCAL" in LOAD DATA LOCAL INPATH means "remote"
Key: SPARK-10804
URL: https://issues.apache.org/jira/browse/SPARK-10804
Project: Spark
Oscar D. Lara Yejas created SPARK-10807:
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Summary: Add as.data.frame() as a synonym for collect()
Key: SPARK-10807
URL: https://issues.apache.org/jira/browse/SPARK-10807
Project: Spark
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Glenn Strycker commented on SPARK-10735:
This appears very similar to a problem I had earlier
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Josh Rosen commented on SPARK-10735:
[~tgraves], Spark 1.5.0 is stricter in its enforcement of types
Joseph K. Bradley created SPARK-10808:
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Summary: LDA user guide: discuss running time of LDA
Key: SPARK-10808
URL: https://issues.apache.org/jira/browse/SPARK-10808
Project: Spark
Issue
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Ian commented on SPARK-10741:
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Two of my tests failed.
The query returns nothing.
{code}
test("test
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Joseph K. Bradley commented on SPARK-10487:
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As far as I can tell, there isn't a huge change
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Joseph K. Bradley closed SPARK-10487.
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Resolution: Not A Problem
> MLlib model fitting causes DataFrame write to break with
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Yin Huai resolved SPARK-10705.
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Resolution: Fixed
Fix Version/s: 1.6.0
This issue has been resolved by
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Zoltán Zvara updated SPARK-10797:
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Description:
It seems that {{RDD.coalesce}} will unnecessarily write out (to shuffle files)
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Joseph K. Bradley commented on SPARK-10791:
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This sounds like a question for the user list, not
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Josh Rosen updated SPARK-10735:
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Description:
In spark 1.5.0 we are now seeing an exception when converting an RDD with
custom
Boris Alexeev created SPARK-10806:
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Summary: Following val redefinition, sometimes the old value is
still visible
Key: SPARK-10806
URL: https://issues.apache.org/jira/browse/SPARK-10806
Project:
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Oscar D. Lara Yejas commented on SPARK-10807:
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I'm working on this one.
Thanks,
Oscar
> Add
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Ian commented on SPARK-10741:
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yup, it works.
The following insert select statement works for non parquet
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Marcelo Vanzin commented on SPARK-10804:
This is really a Hive issue, which Spark just inherits
Joseph K. Bradley created SPARK-10809:
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Summary: Single-document topicDistributions method for
LocalLDAModel
Key: SPARK-10809
URL: https://issues.apache.org/jira/browse/SPARK-10809
Project: Spark
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Andrew Or commented on SPARK-10773:
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I believe this is fixed in 1.5.0:
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Yin Huai commented on SPARK-10741:
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[~ianlcsd] Does {{select "test1" as c1, (count(*)+1) *10 as c2 from
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Thomas Graves commented on SPARK-10735:
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[~joshrosen] it appears you did some of the refactoring
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Jonathan Kelly commented on SPARK-10790:
I can reproduce it with minExecutors=N and
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