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Apache Spark reassigned SPARK-12197:
Assignee: (was: Apache Spark)
> Kryo's Avro Serializer add support for dynamic
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Xusen Yin commented on SPARK-12199:
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I am working on it
> Follow-up: Refine example code in
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Yanbo Liang updated SPARK-12144:
Summary: Support more external data source API in SparkR (was: Implement
DataFrameReader and
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Yanbo Liang updated SPARK-12198:
Issue Type: Sub-task (was: Improvement)
Parent: SPARK-12144
> SparkR support read.parquet
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Apache Spark reassigned SPARK-12198:
Assignee: Apache Spark
> SparkR support read.parquet and deprecate parquetFile
>
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Apache Spark reassigned SPARK-12198:
Assignee: (was: Apache Spark)
> SparkR support read.parquet and deprecate parquetFile
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Xiangrui Meng updated SPARK-12160:
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Fix Version/s: 1.6.1
> spark.mllib should use SQLContext.getOrCreate
>
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Apache Spark reassigned SPARK-12197:
Assignee: Apache Spark
> Kryo's Avro Serializer add support for dynamic schemas using
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Apache Spark commented on SPARK-12197:
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User 'RotemShaul' has created a pull request for this issue:
Rotem Shaul created SPARK-12197:
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Summary: Kryo's Avro Serializer add support for dynamic schemas
using SchemaRepository
Key: SPARK-12197
URL: https://issues.apache.org/jira/browse/SPARK-12197
Project:
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Rotem Shaul updated SPARK-12197:
Description:
The original problem: Serializing GenericRecords in Spark Core results in a
very
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Xiangrui Meng resolved SPARK-11551.
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Resolution: Fixed
Fix Version/s: 1.6.1
Issue resolved by pull request 10002
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Yanbo Liang updated SPARK-12144:
Description:
Currently we support read.df, write.df, jsonFile, parquetFile in SQLContext, we
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Apache Spark reassigned SPARK-12196:
Assignee: Apache Spark
> Store blocks in storage devices with hierarchy way
>
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Apache Spark commented on SPARK-12196:
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User 'yucai' has created a pull request for this issue:
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Rotem Shaul commented on SPARK-12197:
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Implemented solution as described above.
Added new spark
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Xiangrui Meng resolved SPARK-10259.
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Resolution: Fixed
Fix Version/s: 1.6.1
Issue resolved by pull request 8534
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yucai updated SPARK-12196:
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Description:
Problem:
Nowadays, users have both SSDs and HDDs.
SSDs have great performance, but
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pin_zhang closed SPARK-10290.
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not a bug
> Spark can register temp table and hive table with the same table name
>
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Apache Spark reassigned SPARK-12170:
Assignee: Apache Spark
> Deprecate the JAVA-specific deserialized storage levels
>
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Apache Spark reassigned SPARK-12170:
Assignee: (was: Apache Spark)
> Deprecate the JAVA-specific deserialized storage
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Apache Spark commented on SPARK-12170:
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User 'yanboliang' has created a pull request for this issue:
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Xiangrui Meng updated SPARK-11964:
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Shepherd: Joseph K. Bradley
> Create user guide section explaining export/import
>
Yanbo Liang created SPARK-12198:
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Summary: SparkR support read.parquet and deprecate parquetFile
Key: SPARK-12198
URL: https://issues.apache.org/jira/browse/SPARK-12198
Project: Spark
Issue
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Xiangrui Meng resolved SPARK-11957.
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Resolution: Fixed
Fix Version/s: 1.6.1
Issue resolved by pull request 10006
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Xiangrui Meng resolved SPARK-11958.
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Resolution: Fixed
Fix Version/s: 1.6.1
Issue resolved by pull request 10006
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Xiangrui Meng updated SPARK-11551:
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Assignee: somil deshmukh
> Replace example code in ml-features.md using include_example
>
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Xiangrui Meng resolved SPARK-12160.
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Resolution: Fixed
Fix Version/s: (was: 1.6.1)
1.5.3
Issue
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Xiangrui Meng updated SPARK-12160:
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Target Version/s: 1.5.3, 1.6.1 (was: 1.4.2, 1.5.3, 1.6.1)
> spark.mllib should use
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Apache Spark reassigned SPARK-12196:
Assignee: (was: Apache Spark)
> Store blocks in storage devices with hierarchy way
>
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Yanbo Liang updated SPARK-12144:
Description:
Currently we support read.df, write.df, jsonFile, parquetFile in SQLContext, we
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https://issues.apache.org/jira/browse/SPARK-11487?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=15046438#comment-15046438
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Xu Chen commented on SPARK-11487:
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{code}
java.lang.OutOfMemoryError: Java heap space
{code}
Increment
yucai created SPARK-12196:
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Summary: Store blocks in storage devices with hierarchy way
Key: SPARK-12196
URL: https://issues.apache.org/jira/browse/SPARK-12196
Project: Spark
Issue Type: New Feature
Xusen Yin created SPARK-12199:
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Summary: Follow-up: Refine example code in ml-features.md
Key: SPARK-12199
URL: https://issues.apache.org/jira/browse/SPARK-12199
Project: Spark
Issue Type:
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Xusen Yin updated SPARK-12199:
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Fix Version/s: (was: 1.6.1)
> Follow-up: Refine example code in ml-features.md
>
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Sean Owen commented on SPARK-12179:
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Yes, that's the critical information. I think it's hard to parse
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Tao Li commented on SPARK-12179:
[~sowen] My sql and command line param is like this:
DATE=$1
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Tao Li commented on SPARK-12179:
The query is on a hive table and the hive data is not changing.
I think
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Tao Li commented on SPARK-12179:
In the same stage with the same shuffle read, I think it should get the
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Tao Li edited comment on SPARK-12179 at 12/7/15 3:21 PM:
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The query is on a hive
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Apache Spark commented on SPARK-7727:
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User 'stephankessler' has created a pull request for this
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Sean Owen commented on SPARK-12179:
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I don't see that you've shown results at all. What do you expect
Daniel Thomas created SPARK-12180:
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Summary: DataFrame.join() in PySpark gives misleading exception
when column name exists on both side
Key: SPARK-12180
URL: https://issues.apache.org/jira/browse/SPARK-12180
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Tao Li commented on SPARK-12179:
[~srowen] In this case, there is no task failures and I set
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himanshu singhal commented on SPARK-12124:
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I am using the hadoop mongo dependency for the
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Tao Li commented on SPARK-12179:
For example:
1. First Time Run, I got:
20151204maingoogle
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YONG FENG commented on SPARK-5095:
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My team is now working on [MESOS-938]. After that, we actually could
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Justin Bailey commented on SPARK-8118:
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Did some research and Parquet uses java.util.logging. You can
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Caique Rodrigues Marques edited comment on SPARK-8855 at 12/7/15 4:10 PM:
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kevin yu commented on SPARK-7101:
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I will work on this.
> Spark SQL should support java.sql.Time
>
Ted Yu created SPARK-12181:
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Summary: Check Cached unaligned-access capability before using
Unsafe
Key: SPARK-12181
URL: https://issues.apache.org/jira/browse/SPARK-12181
Project: Spark
Issue
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Ted Yu commented on SPARK-12181:
We can add method to Platform which performs check on the architecture.
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Sean Owen commented on SPARK-12124:
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[~himanshu.techsk...@gmail.com] are you using this 3rd party
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hujiayin edited comment on SPARK-4036 at 12/7/15 8:10 AM:
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Hi Sasaki,
I'm not
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Yuhang Chen updated SPARK-12176:
Flags: Important
> SparkLauncher's setConf() does not support configs containing spaces
>
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Sasi commented on SPARK-12175:
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Yes my driver runs on JBoss.
I search same issues, and the fix was to remove
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Kai Sasaki commented on SPARK-11938:
[~mengxr] [~yanboliang] Sorry for bothering you, but could you
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Tathagata Das resolved SPARK-12106.
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Resolution: Fixed
Assignee: Burak Yavuz
Fix Version/s: 1.6.0
> Flaky Test:
Sasi created SPARK-12175:
Summary: Add new flag to Spark that identify if the driver run on
application servers.
Key: SPARK-12175
URL: https://issues.apache.org/jira/browse/SPARK-12175
Project: Spark
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Sean Owen resolved SPARK-12175.
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Resolution: Duplicate
[~sasi2103] this is the same issue that you already opened. Please just keep
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Yuhang Chen updated SPARK-12176:
Description:
The spark-submit uses '--conf K=V' pattern for setting configs. According to
the
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R. H. updated SPARK-12048:
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Comment: was deleted
(was: Thanks for including that fix so fast. I have just tested to fix in the
master
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Sean Owen updated SPARK-12103:
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Fix Version/s: (was: 1.4.2)
> KafkaUtils createStream with multiple topics -- does not work as
Nikita Tarasenko created SPARK-12177:
Summary: Update KafkaDStreams to new Kafka 0.9 Consumer API
Key: SPARK-12177
URL: https://issues.apache.org/jira/browse/SPARK-12177
Project: Spark
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Sasi commented on SPARK-12162:
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Yes my driver runs on JBoss.
> Embedded Spark on JBoss server cause
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Sean Owen reopened SPARK-12177:
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This can stay open as an item targeted for 2.0.0. Your PR can stay closed for
now but can be revived
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Sean Owen updated SPARK-12177:
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Target Version/s: 2.0.0
> Update KafkaDStreams to new Kafka 0.9 Consumer API
>
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Rodrigo Boavida commented on SPARK-12178:
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For any new implementation of a custom stream.
For
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Apache Spark reassigned SPARK-12177:
Assignee: (was: Apache Spark)
> Update KafkaDStreams to new Kafka 0.9 Consumer API
>
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Apache Spark commented on SPARK-12177:
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User 'ntarasenko' has created a pull request for this issue:
Rodrigo Boavida created SPARK-12178:
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Summary: Expose reporting of StreamInputInfo for custom made
streams
Key: SPARK-12178
URL: https://issues.apache.org/jira/browse/SPARK-12178
Project: Spark
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Sean Owen commented on SPARK-12178:
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What is the use case for this?
> Expose reporting of
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Apache Spark reassigned SPARK-12177:
Assignee: Apache Spark
> Update KafkaDStreams to new Kafka 0.9 Consumer API
>
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Nikita Tarasenko closed SPARK-12177.
Resolution: Later
This kind of change would have to wait for Spark 2.x.
> Update
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Rodrigo Boavida commented on SPARK-12178:
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This is probably the first step onto the effort of
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Brandon Bradley commented on SPARK-9184:
Hello! Can we have some discussion?
We can use something
Tao Li created SPARK-12179:
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Summary: Spark SQL get different result with the same code
Key: SPARK-12179
URL: https://issues.apache.org/jira/browse/SPARK-12179
Project: Spark
Issue Type: Bug
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Brandon Bradley updated SPARK-9184:
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Priority: Major (was: Minor)
> spark.task.cpus under Mesos should accept floating point
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Tao Li updated SPARK-12179:
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Description:
I run the sql in yarn-client mode, but get different result each time.
As you can see the
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Tao Li updated SPARK-12179:
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Description:
I run the sql in yarn-client mode, but get different result each time.
As you can see the
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Tao Li updated SPARK-12179:
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Comment: was deleted
(was: [~liancheng] [~sowen ][~andrewor14] [~rxin])
> Spark SQL get different result
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Sean Owen updated SPARK-12179:
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Priority: Minor (was: Major)
What's the problem here? you're not actually getting different *query*
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Yuhang Chen updated SPARK-12176:
Description:
The spark-submit uses '--conf K=V' pattern for setting configs. According to
the
Xiao Li created SPARK-12188:
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Summary: [SQL] Code refactoring and comment correction in Dataset
APIs
Key: SPARK-12188
URL: https://issues.apache.org/jira/browse/SPARK-12188
Project: Spark
Issue
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Apache Spark reassigned SPARK-12188:
Assignee: (was: Apache Spark)
> [SQL] Code refactoring and comment correction in
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Apache Spark commented on SPARK-12188:
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User 'gatorsmile' has created a pull request for this issue:
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Yuhang Chen updated SPARK-12176:
Description:
The spark-submit uses '--conf K=V' pattern for setting configs. According to
the
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https://issues.apache.org/jira/browse/SPARK-12188?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Apache Spark reassigned SPARK-12188:
Assignee: Apache Spark
> [SQL] Code refactoring and comment correction in Dataset APIs
>
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https://issues.apache.org/jira/browse/SPARK-12176?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Yuhang Chen updated SPARK-12176:
Description:
The spark-submit uses '--conf K=V' pattern for setting configs. According to
the
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https://issues.apache.org/jira/browse/SPARK-12176?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=15046205#comment-15046205
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Marcelo Vanzin commented on SPARK-12176:
As I tried to explain, you need to show (i) code and
Andrew Or created SPARK-12189:
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Summary: UnifiedMemoryManager double counts storage memory freed
Key: SPARK-12189
URL: https://issues.apache.org/jira/browse/SPARK-12189
Project: Spark
Issue
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https://issues.apache.org/jira/browse/SPARK-12189?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Apache Spark reassigned SPARK-12189:
Assignee: Apache Spark (was: Josh Rosen)
> UnifiedMemoryManager double counts storage
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https://issues.apache.org/jira/browse/SPARK-12189?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=15046236#comment-15046236
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Apache Spark commented on SPARK-12189:
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User 'JoshRosen' has created a pull request for this issue:
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https://issues.apache.org/jira/browse/SPARK-12189?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Apache Spark reassigned SPARK-12189:
Assignee: Josh Rosen (was: Apache Spark)
> UnifiedMemoryManager double counts storage
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https://issues.apache.org/jira/browse/SPARK-12179?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=15046240#comment-15046240
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Tao Li commented on SPARK-12179:
yes, my spark version is 1.5.3-SNAPSHOT,and the issue SPARK-11009 is
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https://issues.apache.org/jira/browse/SPARK-12179?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Tao Li updated SPARK-12179:
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Comment: was deleted
(was: yes, my spark version is 1.5.3-SNAPSHOT,and the issue SPARK-11009 is
already
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https://issues.apache.org/jira/browse/SPARK-12179?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Tao Li updated SPARK-12179:
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Comment: was deleted
(was: yes, my spark version is 1.5.3-SNAPSHOT,and the issue SPARK-11009 is
already
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https://issues.apache.org/jira/browse/SPARK-12179?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=15046238#comment-15046238
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Tao Li commented on SPARK-12179:
yes, my spark version is 1.5.3-SNAPSHOT,and the issue SPARK-11009 is
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https://issues.apache.org/jira/browse/SPARK-12179?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=15046239#comment-15046239
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Tao Li commented on SPARK-12179:
yes, my spark version is 1.5.3-SNAPSHOT,and the issue SPARK-11009 is
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https://issues.apache.org/jira/browse/SPARK-12179?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=15046243#comment-15046243
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Tao Li commented on SPARK-12179:
I see there was some exceptions in my executors stderr log:
```
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