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Xin Wu updated SPARK-14361:
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Description:
The current Spark SQL does not support the *exclude* clause in Window function
framing clause,
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Xin Wu commented on SPARK-14361:
[~smilegator][~dkbiswal]
> Support EXCLUDE clause in Window function
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Herman van Hovell commented on SPARK-7179:
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I think this one has been fixed in
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Reynold Xin resolved SPARK-7179.
Resolution: Fixed
Assignee: Herman van Hovell
Fix Version/s: 2.0.0
> Add pattern
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Xin Wu edited comment on SPARK-14361 at 4/4/16 6:06 AM:
[~hvanhovell] Since you
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Apache Spark reassigned SPARK-14361:
Assignee: Apache Spark
> Support EXCLUDE clause in Window function framing
>
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Apache Spark reassigned SPARK-14361:
Assignee: (was: Apache Spark)
> Support EXCLUDE clause in Window function framing
>
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Apache Spark commented on SPARK-14361:
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User 'xwu0226' has created a pull request for this issue:
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Xin Wu updated SPARK-14361:
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Description:
The current Spark SQL does not support the exclusion clause in Window function
framing, which
Reynold Xin created SPARK-14364:
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Summary: HeartbeatReceiver object should be private[spark]
Key: SPARK-14364
URL: https://issues.apache.org/jira/browse/SPARK-14364
Project: Spark
Issue Type:
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Apache Spark reassigned SPARK-14364:
Assignee: Reynold Xin (was: Apache Spark)
> HeartbeatReceiver object should be
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Apache Spark commented on SPARK-14364:
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User 'rxin' has created a pull request for this issue:
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Apache Spark reassigned SPARK-14364:
Assignee: Apache Spark (was: Reynold Xin)
> HeartbeatReceiver object should be
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Jurriaan Pruis updated SPARK-14343:
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Description:
When reading a dataset using {{sqlContext.read.text()}} queries on the
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Joseph K. Bradley closed SPARK-11611.
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Resolution: Fixed
Fix Version/s: 2.0.0
Target Version/s: (was: )
>
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Wenchen Fan updated SPARK-13456:
Comment: was deleted
(was: This may be related to
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Wenchen Fan commented on SPARK-13456:
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I found a minimal case to reproduce this issue:
{code}
scala>
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Reynold Xin commented on SPARK-14359:
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cc [~ekhliang] can you give this a shot?
> Improve user
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Reynold Xin updated SPARK-14359:
Description:
See the Scala version in SPARK-14285. The main problem we'd need to work around
is
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Herman van Hovell resolved SPARK-14360.
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Resolution: Resolved
> Allow using df.queryExecution.debug.codegen() to dump codegen
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Apache Spark reassigned SPARK-13929:
Assignee: Apache Spark
> Use Scala reflection for UDFs
> -
>
Dmitriy Selivanov created SPARK-14365:
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Summary: Repartition by column
Key: SPARK-14365
URL: https://issues.apache.org/jira/browse/SPARK-14365
Project: Spark
Issue Type: Improvement
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Wenchen Fan edited comment on SPARK-13456 at 4/4/16 9:52 AM:
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I found a
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Apache Spark reassigned SPARK-13929:
Assignee: (was: Apache Spark)
> Use Scala reflection for UDFs
>
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Apache Spark commented on SPARK-13929:
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User 'joan38' has created a pull request for this issue:
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https://issues.apache.org/jira/browse/SPARK-14243?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=15224283#comment-15224283
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Apache Spark commented on SPARK-14243:
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User 'jeanlyn' has created a pull request for this issue:
Masahiro TANAKA created SPARK-14368:
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Summary: Support python.spark.worker.memory with upper-case unit
Key: SPARK-14368
URL: https://issues.apache.org/jira/browse/SPARK-14368
Project: Spark
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Joan Goyeau updated SPARK-14366:
Description:
We should remove this deprecated sbt-idea plugin as this is generating outdated
Idea
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Joan Goyeau updated SPARK-14366:
Description:
We should remove this deprecated sbt-idea plugin as this is generating outdated
Idea
Joan Goyeau created SPARK-14366:
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Summary: Remove SBT-Idea plugin
Key: SPARK-14366
URL: https://issues.apache.org/jira/browse/SPARK-14366
Project: Spark
Issue Type: Task
Components:
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Joan Goyeau updated SPARK-14366:
Description:
We should remove this deprecated sbt-idea plugin as this is generating outdated
Idea
Tom Hubregtsen created SPARK-14367:
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Summary: spark.memory.useLegacyMode=true in 1.6 does not yield the
same memory behavior as in 1.3
Key: SPARK-14367
URL: https://issues.apache.org/jira/browse/SPARK-14367
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Jason Piper updated SPARK-14393:
Description:
When utilising monotonicallyIncreasingId with a coalesce, it appears that every
Sameer Agarwal created SPARK-14394:
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Summary: Generate AggregateHashMap class during TungstenAggregate
codegen
Key: SPARK-14394
URL: https://issues.apache.org/jira/browse/SPARK-14394
Project: Spark
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Joseph K. Bradley commented on SPARK-13048:
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[~jvstein] Would you be able to test whether the
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Apache Spark reassigned SPARK-13048:
Assignee: Apache Spark (was: Joseph K. Bradley)
> EMLDAOptimizer deletes dependent
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Apache Spark commented on SPARK-13211:
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User 'srowen' has created a pull request for this issue:
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Joseph K. Bradley updated SPARK-14298:
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Shepherd: Joseph K. Bradley
Assignee: Yanbo Liang
Affects
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Joseph K. Bradley updated SPARK-14298:
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Issue Type: Bug (was: Improvement)
> LDA should support disable checkpoint
>
Jason Piper created SPARK-14393:
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Summary: monotonicallyIncreasingId not monotonically increasing
with downstream coalesce
Key: SPARK-14393
URL: https://issues.apache.org/jira/browse/SPARK-14393
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Jason Piper updated SPARK-14393:
Description:
When utilising monotonicallyIncreasingId with a coalesce, it appears that every
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Jason Piper updated SPARK-14393:
Description:
When utilising monotonicallyIncreasingId with a coalesce, it appears that every
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Yong Tang commented on SPARK-14368:
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That is like an easy fix. Will create a pull request shortly.
>
Wenchen Fan created SPARK-14395:
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Summary: remove some unused code in REPL module
Key: SPARK-14395
URL: https://issues.apache.org/jira/browse/SPARK-14395
Project: Spark
Issue Type: Improvement
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Yanbo Liang commented on SPARK-13783:
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[~josephkb] I will work on this.
> Model export/import for
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Yin Huai commented on SPARK-13456:
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The original jira for this should be
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Yin Huai commented on SPARK-13456:
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[~rxin] This is the repl issue.
> Cannot create encoders for case
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Apache Spark reassigned SPARK-14368:
Assignee: Apache Spark
> Support python.spark.worker.memory with upper-case unit
>
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Apache Spark commented on SPARK-14368:
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User 'yongtang' has created a pull request for this issue:
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Apache Spark reassigned SPARK-14368:
Assignee: (was: Apache Spark)
> Support python.spark.worker.memory with upper-case
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Sean Owen updated SPARK-12425:
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Assignee: Guillaume Poulin
> DStream union optimisation
> --
>
>
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Sean Owen resolved SPARK-12425.
---
Resolution: Fixed
Fix Version/s: 2.0.0
Issue resolved by pull request 10382
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Sean Owen resolved SPARK-14240.
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Resolution: Not A Problem
Yeah all of this indicates you are not giving your job enough memory. It's
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Joseph K. Bradley resolved SPARK-14386.
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Resolution: Fixed
Fix Version/s: 2.0.0
Issue resolved by pull request 12158
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Joseph K. Bradley updated SPARK-13048:
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Target Version/s: 2.0.0
I'll send a PR for this. I'd prefer to fix this in 2.0 only
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Joseph K. Bradley updated SPARK-14087:
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Target Version/s: (was: 2.0.0)
> PySpark ML JavaModel does not properly own params
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Apache Spark commented on SPARK-14394:
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User 'sameeragarwal' has created a pull request for this
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Apache Spark reassigned SPARK-14394:
Assignee: Apache Spark
> Generate AggregateHashMap class during TungstenAggregate codegen
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Apache Spark reassigned SPARK-14394:
Assignee: (was: Apache Spark)
> Generate AggregateHashMap class during
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Apache Spark commented on SPARK-13048:
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User 'jkbradley' has created a pull request for this issue:
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Apache Spark reassigned SPARK-13048:
Assignee: Joseph K. Bradley (was: Apache Spark)
> EMLDAOptimizer deletes dependent
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Apache Spark reassigned SPARK-14395:
Assignee: Wenchen Fan (was: Apache Spark)
> remove some unused code in REPL module
>
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Apache Spark reassigned SPARK-14395:
Assignee: Apache Spark (was: Wenchen Fan)
> remove some unused code in REPL module
>
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Kousuke Saruta updated SPARK-14368:
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Fix Version/s: 2.0.0
1.6.2
> Support python.spark.worker.memory with
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Kousuke Saruta resolved SPARK-14368.
Resolution: Fixed
> Support python.spark.worker.memory with upper-case unit
>
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Kousuke Saruta updated SPARK-14368:
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Assignee: Yong Tang
> Support python.spark.worker.memory with upper-case unit
>
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Apache Spark commented on SPARK-14359:
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User 'ericl' has created a pull request for this issue:
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Apache Spark reassigned SPARK-14359:
Assignee: (was: Apache Spark)
> Improve user experience for typed aggregate functions
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Xiao Li commented on SPARK-14125:
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Now, working on TOK_ALTERVIEW_ADDPARTS/TOK_ALTERVIEW_DROPPARTS. will
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Hyukjin Kwon edited comment on SPARK-14103 at 4/5/16 12:45 AM:
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Oh, sorry I
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Yuanzhen Geng updated SPARK-14289:
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Summary: Add support to multiple eviction strategies for cached RDD
partitions (was: Add
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Michael Armbrust resolved SPARK-14287.
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Resolution: Fixed
Fix Version/s: 2.0.0
Issue resolved by pull request 12080
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Apache Spark reassigned SPARK-14359:
Assignee: Apache Spark
> Improve user experience for typed aggregate functions in Java
>
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Wenchen Fan edited comment on SPARK-13456 at 4/5/16 12:20 AM:
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I found a
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Apache Spark reassigned SPARK-14289:
Assignee: (was: Apache Spark)
> Add support to multiple eviction strategies for
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Apache Spark commented on SPARK-14289:
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User 'Earne' has created a pull request for this issue:
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Wenchen Fan resolved SPARK-13456.
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Resolution: Fixed
> Cannot create encoders for case classes defined in Spark shell after
>
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Apache Spark reassigned SPARK-14289:
Assignee: Apache Spark
> Add support to multiple eviction strategies for cached RDD
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Sayak Ghosh commented on SPARK-14240:
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The issue has been resolved. Its a GC issue as you mentioned
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Joseph K. Bradley reassigned SPARK-13048:
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Assignee: Joseph K. Bradley
> EMLDAOptimizer deletes dependent checkpoint of
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Wenchen Fan commented on SPARK-13456:
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This is a scala bug:
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Yuanzhen Geng updated SPARK-14289:
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Summary: Support multiple eviction strategies for cached RDD partitions
(was: Add support to
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Apache Spark commented on SPARK-14347:
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User 'srowen' has created a pull request for this issue:
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Apache Spark reassigned SPARK-14347:
Assignee: (was: Apache Spark)
> Require Java 8 for Spark 2.x
>
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Apache Spark reassigned SPARK-14347:
Assignee: Apache Spark
> Require Java 8 for Spark 2.x
>
>
>
Xiao Li created SPARK-14396:
---
Summary: Throw Exceptions for DDLs of Partitioned Views (CREATE
VIEW and ALTER VIEW)
Key: SPARK-14396
URL: https://issues.apache.org/jira/browse/SPARK-14396
Project: Spark
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Xiao Li updated SPARK-14396:
Description:
Because the concept of partitioning is associated with physical tables, we
disable all the
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Xiao Li updated SPARK-14362:
Description:
Native parsing and native analysis of DDL command: Drop View.
Based on the HIVE DDL document
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https://issues.apache.org/jira/browse/SPARK-14396?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Xiao Li updated SPARK-14396:
Description:
Because the concept of partitioning is associated with physical tables, we
disable all the
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https://issues.apache.org/jira/browse/SPARK-14396?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Xiao Li updated SPARK-14396:
Description:
Because the concept of partitioning is associated with physical tables, we
disable all the
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https://issues.apache.org/jira/browse/SPARK-14396?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Apache Spark reassigned SPARK-14396:
Assignee: (was: Apache Spark)
> Throw Exceptions for DDLs of Partitioned Views
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https://issues.apache.org/jira/browse/SPARK-14396?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=15225722#comment-15225722
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Apache Spark commented on SPARK-14396:
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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-14396?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Apache Spark reassigned SPARK-14396:
Assignee: Apache Spark
> Throw Exceptions for DDLs of Partitioned Views (CREATE VIEW and
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https://issues.apache.org/jira/browse/SPARK-13784?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Joseph K. Bradley updated SPARK-13784:
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Assignee: Gayathri Murali
> Model export/import for spark.ml: RandomForests
>
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https://issues.apache.org/jira/browse/SPARK-14245?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=15224589#comment-15224589
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Thomas Graves commented on SPARK-14245:
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ok, personally I would prefer people to assign jira to
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https://issues.apache.org/jira/browse/SPARK-14176?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Michael Armbrust resolved SPARK-14176.
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Resolution: Fixed
Fix Version/s: 2.0.0
Issue resolved by pull request 11976
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https://issues.apache.org/jira/browse/SPARK-12981?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Davies Liu resolved SPARK-12981.
Resolution: Fixed
Fix Version/s: 2.0.0
Issue resolved by pull request 12127
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https://issues.apache.org/jira/browse/SPARK-4105?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=15224503#comment-15224503
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Bo Liu commented on SPARK-4105:
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This happened in Spark Streaming 1.3.1 by using direct kafka api
{code}
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https://issues.apache.org/jira/browse/SPARK-14087?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Joseph K. Bradley updated SPARK-14087:
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Shepherd: Joseph K. Bradley
Assignee: Bryan Cutler
> PySpark ML JavaModel does not
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https://issues.apache.org/jira/browse/SPARK-14245?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=15224288#comment-15224288
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Thomas Graves commented on SPARK-14245:
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[~ajbozarth] Please go ahead and assign yourself the jira
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