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Apache Spark reassigned SPARK-17534:
Assignee: Apache Spark
> Increase timeouts for DirectKafkaStreamSuite tests
>
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Apache Spark commented on SPARK-17534:
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User 'a-roberts' has created a pull request for this issue:
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Apache Spark commented on SPARK-17480:
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User 'HyukjinKwon' has created a pull request for this
Adam Roberts created SPARK-17534:
Summary: Increase timeouts for DirectKafkaStreamSuite tests
Key: SPARK-17534
URL: https://issues.apache.org/jira/browse/SPARK-17534
Project: Spark
Issue
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Apache Spark reassigned SPARK-17534:
Assignee: (was: Apache Spark)
> Increase timeouts for DirectKafkaStreamSuite tests
>
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Max Moroz commented on SPARK-17496:
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Agreed, I thought 1 means randomly permute the DataFrame like in
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Yang Wang updated SPARK-17537:
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Description: spark.read.parquet would issue a spark jobs to read parquet
schema. When
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Jeff Nadler commented on SPARK-17510:
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I consider this to be a separate issue from the backpressure
WangJianfei created SPARK-17535:
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Summary: Performance Improvement of Signleton pattern in
SparkContext
Key: SPARK-17535
URL: https://issues.apache.org/jira/browse/SPARK-17535
Project: Spark
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Sean Owen commented on SPARK-17535:
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This is called "double checked locking" and it doesn't actually
John Muller created SPARK-17536:
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Summary: Minor performance improvement to JDBC batch inserts
Key: SPARK-17536
URL: https://issues.apache.org/jira/browse/SPARK-17536
Project: Spark
Issue
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Andrew Or commented on SPARK-15917:
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By the way is there a pull request?
> Define the number of
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WangJianfei commented on SPARK-17535:
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Oh sorry, I should use volatile as a class field, like this
Weichen Xu created SPARK-17540:
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Summary: SparkR array serde cannot work correctly when array
length == 0
Key: SPARK-17540
URL: https://issues.apache.org/jira/browse/SPARK-17540
Project: Spark
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Apache Spark reassigned SPARK-17540:
Assignee: Apache Spark
> SparkR array serde cannot work correctly when array length == 0
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WangJianfei closed SPARK-17535.
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Resolution: Duplicate
> Performance Improvement of Signleton pattern in SparkContext
>
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Abel Rincón commented on SPARK-16742:
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We at Stratio are working on this issue,
Stratio design doc:
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Apache Spark reassigned SPARK-17537:
Assignee: (was: Apache Spark)
> Improve performance for reading parquet schema
>
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Apache Spark commented on SPARK-17537:
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User 'yangw1234' has created a pull request for this issue:
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Apache Spark reassigned SPARK-17537:
Assignee: Apache Spark
> Improve performance for reading parquet schema
>
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WangJianfei reopened SPARK-17535:
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> Performance Improvement of Signleton pattern in SparkContext
>
Srinivas Rishindra Pothireddi created SPARK-17538:
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Summary: sqlContext.registerDataFrameAsTable is not working
sometimes in spark 2.0
Key: SPARK-17538
URL:
Jeff Nadler created SPARK-17539:
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Summary: Streaming Backpressure Starves DirectStream When Used In
Combination With Receivers
Key: SPARK-17539
URL: https://issues.apache.org/jira/browse/SPARK-17539
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Apache Spark reassigned SPARK-17540:
Assignee: (was: Apache Spark)
> SparkR array serde cannot work correctly when array
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Apache Spark commented on SPARK-17540:
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User 'WeichenXu123' has created a pull request for this
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WangJianfei updated SPARK-17535:
Description:
I think the singleton pattern of SparkContext is inefficient if there are many
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WangJianfei updated SPARK-17535:
Description:
I think the singleton pattern of SparkContext is inefficient if there are many
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Wenchen Fan resolved SPARK-17409.
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Resolution: Fixed
Fix Version/s: 2.1.0
Issue resolved by pull request 15048
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Yang Wang updated SPARK-17537:
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Description: spark.read.parquet would issue a spark job to read parquet
schema. When
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Yang Wang updated SPARK-17537:
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Description: spark.read.parquet would issue a spark jobs to read parquet
schema. When
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Srinivas Rishindra Pothireddi updated SPARK-17538:
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Summary: sqlContext.registerDataFrameAsTable is not working
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Srinivas Rishindra Pothireddi updated SPARK-17538:
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Description:
I have a production job in spark 1.6.2 that
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Sean Owen commented on SPARK-17535:
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I think this happens to work out because the context is held in an
Yang Wang created SPARK-17537:
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Summary: Improve performance for reading parquet schema
Key: SPARK-17537
URL: https://issues.apache.org/jira/browse/SPARK-17537
Project: Spark
Issue Type:
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Jeff Nadler commented on SPARK-17510:
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I filed SPARK-17539 for the backpressure bug.
> Set
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Chris Horn commented on SPARK-15835:
You can work around this issue by providing the schema
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Apache Spark commented on SPARK-17541:
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User 'cloud-fan' has created a pull request for this issue:
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Davies Liu resolved SPARK-17514.
Resolution: Fixed
Fix Version/s: 2.1.0
2.0.1
Issue resolved by pull
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Sean Owen updated SPARK-17542:
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Issue Type: Improvement (was: Bug)
There are unfortunately a number of warnings, and I don't think we
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Apache Spark commented on SPARK-17536:
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User 'blue666man' has created a pull request for this issue:
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Apache Spark reassigned SPARK-17536:
Assignee: (was: Apache Spark)
> Minor performance improvement to JDBC batch inserts
>
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Apache Spark reassigned SPARK-17541:
Assignee: Wenchen Fan (was: Apache Spark)
> fix some DDL bugs about table management
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Apache Spark reassigned SPARK-17541:
Assignee: Apache Spark (was: Wenchen Fan)
> fix some DDL bugs about table management
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Apache Spark commented on SPARK-17317:
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User 'junyangq' has created a pull request for this issue:
Frederick Reiss created SPARK-17542:
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Summary: Compiler warning in UnsafeInMemorySorter class
Key: SPARK-17542
URL: https://issues.apache.org/jira/browse/SPARK-17542
Project: Spark
Issue
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Cody Koeninger commented on SPARK-17510:
I use direct stream for multiple topic jobs where the
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Cody Koeninger edited comment on SPARK-17510 at 9/14/16 6:12 PM:
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I use
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Apache Spark reassigned SPARK-17536:
Assignee: Apache Spark
> Minor performance improvement to JDBC batch inserts
>
Frederick Reiss created SPARK-17543:
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Summary: Missing log4j config file for tests in
common/network-shuffle
Key: SPARK-17543
URL: https://issues.apache.org/jira/browse/SPARK-17543
Project: Spark
Wenchen Fan created SPARK-17541:
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Summary: fix some DDL bugs about table management when same-name
temp view exists
Key: SPARK-17541
URL: https://issues.apache.org/jira/browse/SPARK-17541
Project:
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Jeff Nadler commented on SPARK-17510:
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Yes you're right - it's partly about differing rates but the
Brady Auen created SPARK-17544:
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Summary: Timeout waiting for connection from pool, DataFrame
Reader's not closing S3 connections?
Key: SPARK-17544
URL: https://issues.apache.org/jira/browse/SPARK-17544
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Thomas Graves resolved SPARK-17511.
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Resolution: Fixed
Assignee: Kishor Patil
Fix Version/s: 2.1.0
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Maciej Bryński commented on SPARK-16534:
[~rxin]
Could you explain your decision ?
I think that
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Evan Zamir commented on SPARK-17508:
Honestly, if the documentation was just more explicit, users
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holdenk commented on SPARK-16424:
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Just an update - we have a really early proof of concept branch
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Bryan Cutler commented on SPARK-17508:
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I had a similar discussion in this PR
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Herman van Hovell resolved SPARK-10747.
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Resolution: Fixed
Assignee: Xin Wu
Fix Version/s: 2.1.0
> add
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Evan Zamir edited comment on SPARK-17508 at 9/14/16 6:52 PM:
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Honestly, if
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Evan Zamir edited comment on SPARK-17508 at 9/14/16 6:53 PM:
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Honestly, if
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Cody Koeninger commented on SPARK-17510:
Just for clarity's sake, compute time is far higher on
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Josh Rosen updated SPARK-17465:
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Assignee: Xing Shi
> Inappropriate memory management in `org.apache.spark.storage.MemoryStore` may
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Josh Rosen updated SPARK-17465:
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Fix Version/s: 2.1.0
2.0.1
> Inappropriate memory management in
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Jeff Nadler commented on SPARK-17510:
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That would be incredible, thank you very much for looking into
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Apache Spark commented on SPARK-17346:
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User 'zsxwing' has created a pull request for this issue:
Kevin Burton created SPARK-17546:
Summary: start-* scripts should use hostname --fqdn
Key: SPARK-17546
URL: https://issues.apache.org/jira/browse/SPARK-17546
Project: Spark
Issue Type: Bug
Josh Rosen created SPARK-17547:
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Summary: Temporary shuffle data files may be leaked following
exception in write
Key: SPARK-17547
URL: https://issues.apache.org/jira/browse/SPARK-17547
Project: Spark
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Cody Koeninger commented on SPARK-17510:
Ok, next time I get some free hacking time I can make a
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Apache Spark reassigned SPARK-17100:
Assignee: Davies Liu (was: Apache Spark)
> pyspark filter on a udf column after join
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Apache Spark reassigned SPARK-17100:
Assignee: Apache Spark (was: Davies Liu)
> pyspark filter on a udf column after join
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Apache Spark commented on SPARK-17100:
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User 'davies' has created a pull request for this issue:
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Apache Spark reassigned SPARK-17547:
Assignee: Josh Rosen (was: Apache Spark)
> Temporary shuffle data files may be leaked
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Davies Liu resolved SPARK-17472.
Resolution: Fixed
Fix Version/s: 2.1.0
Issue resolved by pull request 15026
Nathan Beyer created SPARK-17545:
Summary: Spark SQL Catalyst doesn't handle ISO 8601 date with
colon in offset
Key: SPARK-17545
URL: https://issues.apache.org/jira/browse/SPARK-17545
Project: Spark
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Jeff Nadler commented on SPARK-17510:
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Well... both streams use updateStateByKey. The session one
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Josh Rosen resolved SPARK-17465.
Resolution: Fixed
Fix Version/s: 1.6.3
Issue resolved by pull request 15022
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Apache Spark commented on SPARK-17114:
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User 'hvanhovell' has created a pull request for this issue:
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Brady Auen commented on SPARK-17544:
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Apache Spark reassigned SPARK-17346:
Assignee: (was: Apache Spark)
> Kafka 0.10 support in Structured Streaming
>
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Apache Spark reassigned SPARK-17547:
Assignee: Apache Spark (was: Josh Rosen)
> Temporary shuffle data files may be leaked
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Apache Spark commented on SPARK-17547:
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User 'JoshRosen' has created a pull request for this issue:
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WangJianfei closed SPARK-17533.
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Resolution: Won't Fix
> I think it's necessary to have an overrided method of union in sparkContext
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Bryan Cutler commented on SPARK-17508:
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To respond to [~srowen] question, I think it's reasonable to
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Josh Rosen commented on SPARK-17544:
I found a similar issue from the {{spark-avro}} repository:
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yuhao yang commented on SPARK-15573:
This sounds feasible. Two primary work items as I see:
1. Find a
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Shixiong Zhu commented on SPARK-16407:
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Right now we don't want to add such typed API to
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Davies Liu commented on SPARK-16439:
The separator was added on purpose, otherwise it's very
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Reynold Xin commented on SPARK-16407:
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This doesn't work in SQL, Python, etc.
I like the general
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Marcelo Vanzin updated SPARK-17549:
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Attachment: spark-1.6.patch
example_1.6_pre_patch.png
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Davies Liu reopened SPARK-16439:
We could bring the seperator back for better readability.
> Incorrect information in SQL Query
Marcelo Vanzin created SPARK-17549:
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Summary: InMemoryRelation doesn't scale to large tables
Key: SPARK-17549
URL: https://issues.apache.org/jira/browse/SPARK-17549
Project: Spark
Issue
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https://issues.apache.org/jira/browse/SPARK-16439?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Apache Spark reassigned SPARK-16439:
Assignee: Maciej Bryński (was: Apache Spark)
> Incorrect information in SQL Query
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https://issues.apache.org/jira/browse/SPARK-16439?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=15491766#comment-15491766
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Apache Spark commented on SPARK-16439:
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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-16439?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Apache Spark reassigned SPARK-16439:
Assignee: Apache Spark (was: Maciej Bryński)
> Incorrect information in SQL Query
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https://issues.apache.org/jira/browse/SPARK-16407?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=15491772#comment-15491772
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holdenk commented on SPARK-16407:
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Right the simplest example where you need to use the typed API is with
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https://issues.apache.org/jira/browse/SPARK-16407?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=15491784#comment-15491784
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holdenk commented on SPARK-16407:
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It's true it doesn't work in SQL - but I don't think the current
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https://issues.apache.org/jira/browse/SPARK-16407?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=15491779#comment-15491779
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Reynold Xin commented on SPARK-16407:
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Actually I spoke too soon. I only read the code change and
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https://issues.apache.org/jira/browse/SPARK-16407?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=15491787#comment-15491787
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holdenk commented on SPARK-16407:
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That's part of why I decided to just use the ForeachRDD sink as
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https://issues.apache.org/jira/browse/SPARK-17549?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Marcelo Vanzin updated SPARK-17549:
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Attachment: spark-1.6-2.patch
Just noticed there's already a more accurate count of the
Aniket Kulkarni created SPARK-17550:
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Summary: DataFrameWriter.partitionBy() should throw exception if
column is not present in Dataframe
Key: SPARK-17550
URL: https://issues.apache.org/jira/browse/SPARK-17550
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