Reynold Xin created SPARK-18856:
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Summary: Newly created catalog table assumed to have 0 rows and 0
bytes
Key: SPARK-18856
URL: https://issues.apache.org/jira/browse/SPARK-18856
Project: Spark
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Yuming Wang updated SPARK-18827:
Summary: Cann't read broadcast if broadcast blocks are stored on-disk,
(was: Cann't cache
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Yuming Wang updated SPARK-18827:
Summary: Cann't read broadcast if broadcast blocks are stored on-disk
(was: Cann't read broadcast
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Reynold Xin updated SPARK-18854:
Target Version/s: 2.0.3, 2.1.1, 2.2.0 (was: 2.1.1, 2.2.0)
> getNodeNumbered and
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Apache Spark reassigned SPARK-18854:
Assignee: (was: Apache Spark)
> getNodeNumbered and generateTreeString are not
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Apache Spark commented on SPARK-18854:
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User 'rxin' has created a pull request for this issue:
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Apache Spark reassigned SPARK-18854:
Assignee: Apache Spark
> getNodeNumbered and generateTreeString are not consistent
>
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Joseph K. Bradley updated SPARK-18356:
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Summary: KMeans should cache RDD before training (was: Issue + Resolution:
Kmeans
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Reynold Xin updated SPARK-18854:
Description:
This is a bug introduced by subquery handling. generateTreeString numbers trees
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Reynold Xin updated SPARK-18854:
Description:
This is a bug introduced by subquery handling. generateTreeString numbers trees
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Felix Cheung commented on SPARK-18823:
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We will address both of your suggestions.
As for x$y <-
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Felix Cheung commented on SPARK-18823:
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For #2, I do agree it could get messy, but I was thinking
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Apache Spark reassigned SPARK-18855:
Assignee: (was: Apache Spark)
> Add RDD flatten function
>
>
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Apache Spark reassigned SPARK-18855:
Assignee: Apache Spark
> Add RDD flatten function
>
>
>
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Apache Spark commented on SPARK-18855:
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User 'linbojin' has created a pull request for this issue:
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Felix Cheung commented on SPARK-18849:
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probably would be good to check for warning or error in
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Felix Cheung commented on SPARK-18825:
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I will see what I can do...
> Eliminate duplicate links in
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Jeff Zhang commented on SPARK-13587:
If it is pretty large cluster, then I would suggest to set up a
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Linbo updated SPARK-18855:
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Target Version/s: (was: 2.1.0)
> Add RDD flatten function
>
>
>
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Prasanna Santhanam commented on SPARK-13587:
[~zjffdu] In case of Anaconda Python the
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Prasanna Santhanam commented on SPARK-13587:
[~zjffdu] In case of Anaconda Python the
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Prasanna Santhanam updated SPARK-13587:
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Comment: was deleted
(was: [~zjffdu] In case of Anaconda Python the environment is
Linbo created SPARK-18855:
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Summary: Add RDD flatten function
Key: SPARK-18855
URL: https://issues.apache.org/jira/browse/SPARK-18855
Project: Spark
Issue Type: New Feature
Components:
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Jeff Zhang commented on SPARK-13587:
[~prasanna.santha...@icloud.com] I don't understand how this can
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Prasanna Santhanam commented on SPARK-13587:
[~nchammas] sorry, this got buried in several
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Shuai Lin commented on SPARK-18278:
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bq. If I had to choose between maintaining a fork versus cleaning
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Liang-Chi Hsieh edited comment on SPARK-18281 at 12/14/16 3:48 AM:
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Liang-Chi Hsieh commented on SPARK-18281:
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[~mwdus...@us.ibm.com] Thanks for reporting this
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Wenchen Fan resolved SPARK-18566.
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Resolution: Fixed
Fix Version/s: 2.2.0
> remove OverwriteOptions
>
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Reynold Xin commented on SPARK-18854:
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To test this, introduce a subquery and call
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Reynold Xin updated SPARK-18854:
Description:
This is a bug introduced by subquery handling. generateTreeString numbers trees
Reynold Xin created SPARK-18854:
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Summary: getNodeNumbered and generateTreeString are not consistent
Key: SPARK-18854
URL: https://issues.apache.org/jira/browse/SPARK-18854
Project: Spark
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Reynold Xin commented on SPARK-18854:
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cc [~smilegator]
> getNodeNumbered and generateTreeString are
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Apache Spark reassigned SPARK-18588:
Assignee: Shixiong Zhu (was: Apache Spark)
> KafkaSourceStressForDontFailOnDataLossSuite
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Apache Spark commented on SPARK-18588:
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User 'zsxwing' has created a pull request for this issue:
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Apache Spark reassigned SPARK-18588:
Assignee: Apache Spark (was: Shixiong Zhu)
> KafkaSourceStressForDontFailOnDataLossSuite
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Wenchen Fan resolved SPARK-18746.
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Resolution: Fixed
Assignee: Weiqing Yang
Fix Version/s: 2.2.0
> Add implicit
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Marcelo Vanzin resolved SPARK-18840.
Resolution: Fixed
> HDFSCredentialProvider throws exception in non-HDFS security
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Marcelo Vanzin commented on SPARK-18840:
Ok. Since it's not a regression, let's do it if it
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Apache Spark commented on SPARK-18853:
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User 'rxin' has created a pull request for this issue:
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Apache Spark reassigned SPARK-18853:
Assignee: (was: Apache Spark)
> Project (UnaryNode) is way too aggressive in
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Apache Spark reassigned SPARK-18853:
Assignee: Apache Spark
> Project (UnaryNode) is way too aggressive in estimating
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Saisai Shao commented on SPARK-18840:
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[~vanzin], is it necessary to fix it in old version (2.0/1.6),
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Nattavut Sutyanyong commented on SPARK-18814:
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As this JIRA will be brought to close shortly,
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Alexander Ulanov commented on SPARK-7253:
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Here is the implementation of belief propagation
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Xiangrui Meng resolved SPARK-18793.
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Resolution: Fixed
Fix Version/s: 2.2.0
2.1.1
Issue resolved by
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Xiangrui Meng resolved SPARK-18794.
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Resolution: Fixed
Fix Version/s: 2.2.0
2.1.1
Issue resolved by
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Joseph K. Bradley updated SPARK-17455:
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Target Version/s: 2.0.3, 2.1.1, 2.2.0
> IsotonicRegression takes non-polynomial time
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Reynold Xin updated SPARK-18853:
Summary: Project (UnaryNode) is way too aggressive in estimating statistics
(was: Project is way
Reynold Xin created SPARK-18853:
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Summary: Project is way too aggressive in estimating statistics
Key: SPARK-18853
URL: https://issues.apache.org/jira/browse/SPARK-18853
Project: Spark
Issue
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manuel garrido commented on SPARK-18783:
I agree, it's not a deal breaker. Good to have it
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Bryan Cutler commented on SPARK-18783:
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I believe this is the case for most ML
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Alex Bozarth commented on SPARK-18837:
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Did some digging and this *seems* to have been caused by
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Apache Spark commented on SPARK-18852:
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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-18852?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Apache Spark reassigned SPARK-18852:
Assignee: (was: Apache Spark)
> StreamingQuery.lastProgress should be null when
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Apache Spark reassigned SPARK-18852:
Assignee: Apache Spark
> StreamingQuery.lastProgress should be null when recentProgress
Shixiong Zhu created SPARK-18852:
Summary: StreamingQuery.lastProgress should be null when
recentProgress is empty
Key: SPARK-18852
URL: https://issues.apache.org/jira/browse/SPARK-18852
Project:
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Shixiong Zhu updated SPARK-18852:
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Affects Version/s: 2.1.0
> StreamingQuery.lastProgress should be null when recentProgress is
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Russell Spitzer resolved SPARK-18851.
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Resolution: Duplicate
> DataSet Limit into Aggregate Results in NPE in Codegen
>
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Joseph K. Bradley updated SPARK-4591:
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Target Version/s: (was: 2.2.0)
> Algorithm/model parity for spark.ml (Scala)
>
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Joseph K. Bradley commented on SPARK-4591:
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I also removed the target version since this includes
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Joseph K. Bradley updated SPARK-18813:
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Description:
*PROPOSAL: This includes a proposal for the 2.2 roadmap process for
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Joseph K. Bradley commented on SPARK-4591:
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I just updated this a bit. I did not finish linking
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Russell Spitzer updated SPARK-18851:
Labels: regresion (was: )
> DataSet Limit into Aggregate Results in NPE in Codegen
>
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Joseph K. Bradley updated SPARK-14709:
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Shepherd: Joseph K. Bradley
Target Version/s: 2.2.0
> spark.ml API for
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Joseph K. Bradley commented on SPARK-14709:
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Marking myself as shepherd per the 2.2 roadmap
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Joseph K. Bradley updated SPARK-4591:
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Description:
This is an umbrella JIRA for porting spark.mllib implementations to use the
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Tathagata Das resolved SPARK-18834.
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Resolution: Fixed
Fix Version/s: 2.1.0
Issue resolved by pull request 16258
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Apache Spark commented on SPARK-18850:
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User 'zsxwing' has created a pull request for this issue:
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Apache Spark reassigned SPARK-18850:
Assignee: Apache Spark (was: Shixiong Zhu)
> Make StreamExecution serializable
>
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Apache Spark reassigned SPARK-18850:
Assignee: Shixiong Zhu (was: Apache Spark)
> Make StreamExecution serializable
>
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Joseph K. Bradley updated SPARK-4591:
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Description:
This is an umbrella JIRA for porting spark.mllib implementations to use the
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Shixiong Zhu resolved SPARK-18843.
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Resolution: Fixed
Fix Version/s: 2.1.1
2.0.3
> Fix timeout in
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Russell Spitzer updated SPARK-18851:
Summary: DataSet Limit into Aggregate Results in NPE in Codegen (was:
DataSet
Russell Spitzer created SPARK-18851:
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Summary: DataSet limit.distinct Results in NPE in Codegen
Key: SPARK-18851
URL: https://issues.apache.org/jira/browse/SPARK-18851
Project: Spark
Issue
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Reynold Xin commented on SPARK-18676:
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That's the other option I was considering. It'd be good to
Shixiong Zhu created SPARK-18850:
Summary: Make StreamExecution serializable
Key: SPARK-18850
URL: https://issues.apache.org/jira/browse/SPARK-18850
Project: Spark
Issue Type: Improvement
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Joseph K. Bradley updated SPARK-4591:
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Description:
This is an umbrella JIRA for porting spark.mllib implementations to use the
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Joseph K. Bradley updated SPARK-4591:
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Description:
This is an umbrella JIRA for porting spark.mllib implementations to use the
Xiangrui Meng created SPARK-18849:
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Summary: Vignettes final checks for Spark 2.1
Key: SPARK-18849
URL: https://issues.apache.org/jira/browse/SPARK-18849
Project: Spark
Issue Type:
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Andrew Ray commented on SPARK-18847:
I have and have not found any relevant. I'm currently working on
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Joseph K. Bradley updated SPARK-4591:
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Description:
This is an umbrella JIRA for porting spark.mllib implementations to use the
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https://issues.apache.org/jira/browse/SPARK-4591?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Joseph K. Bradley updated SPARK-4591:
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Description:
This is an umbrella JIRA for porting spark.mllib implementations to use the
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Joseph K. Bradley updated SPARK-4591:
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Description:
This is an umbrella JIRA for porting spark.mllib implementations to use the
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Andrew Ray commented on SPARK-18845:
[~srowen] No that's a different thing just whether the result
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Michael Allman commented on SPARK-18676:
Yeah, I was wondering how that would work with the
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Apache Spark commented on SPARK-18845:
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User 'aray' has created a pull request for this issue:
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https://issues.apache.org/jira/browse/SPARK-18845?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Apache Spark reassigned SPARK-18845:
Assignee: (was: Apache Spark)
> PageRank has incorrect initialization value that
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https://issues.apache.org/jira/browse/SPARK-18845?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Apache Spark reassigned SPARK-18845:
Assignee: Apache Spark
> PageRank has incorrect initialization value that leads to slow
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https://issues.apache.org/jira/browse/SPARK-18676?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=15746370#comment-15746370
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Davies Liu edited comment on SPARK-18676 at 12/13/16 9:47 PM:
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I had a
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https://issues.apache.org/jira/browse/SPARK-18676?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=15746370#comment-15746370
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Davies Liu commented on SPARK-18676:
I had a working prototype, but in introduce some weird behavior,
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https://issues.apache.org/jira/browse/SPARK-4591?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=15746350#comment-15746350
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Joseph K. Bradley edited comment on SPARK-4591 at 12/13/16 9:41 PM:
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https://issues.apache.org/jira/browse/SPARK-4591?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=15746350#comment-15746350
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Joseph K. Bradley commented on SPARK-4591:
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Good point. It should be. I'll add it.
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https://issues.apache.org/jira/browse/SPARK-18816?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Sean Owen resolved SPARK-18816.
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Resolution: Fixed
Fix Version/s: 2.2.0
2.1.1
Issue resolved by pull
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https://issues.apache.org/jira/browse/SPARK-18847?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=15746333#comment-15746333
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Sean Owen commented on SPARK-18847:
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Before you open more can you review old JIRAs about this?
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https://issues.apache.org/jira/browse/SPARK-18848?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Sean Owen resolved SPARK-18848.
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Resolution: Duplicate
> PageRank gives incorrect results for graphs with sinks
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Andrew Ray created SPARK-18848:
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Summary: PageRank gives incorrect results for graphs with sinks
Key: SPARK-18848
URL: https://issues.apache.org/jira/browse/SPARK-18848
Project: Spark
Issue
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https://issues.apache.org/jira/browse/SPARK-18846?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=15746326#comment-15746326
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Apache Spark commented on SPARK-18846:
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User 'squito' has created a pull request for this issue:
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https://issues.apache.org/jira/browse/SPARK-18846?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Apache Spark reassigned SPARK-18846:
Assignee: Imran Rashid (was: Apache Spark)
> Fix flakiness in SchedulerIntegrationSuite
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https://issues.apache.org/jira/browse/SPARK-18846?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Apache Spark reassigned SPARK-18846:
Assignee: Apache Spark (was: Imran Rashid)
> Fix flakiness in SchedulerIntegrationSuite
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