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Tathagata Das resolved SPARK-22017.
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Resolution: Fixed
Fix Version/s: 3.0.0
Issue resolved by pull request 19239
AnChe Kuo created SPARK-22034:
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Summary: CrossValidator's training and testing set with different
set of labels, resulting in encoder transform error
Key: SPARK-22034
URL:
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https://issues.apache.org/jira/browse/SPARK-22033?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=16168650#comment-16168650
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Sean Owen commented on SPARK-22033:
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Hm, good point. There may be other similar issues throughout the
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Vadim Semenov commented on SPARK-22033:
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Leaving traces for others if they happen to hit the same
Vadim Semenov created SPARK-22033:
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Summary: BufferHolder size checks should account for the specific
VM array size limitations
Key: SPARK-22033
URL: https://issues.apache.org/jira/browse/SPARK-22033
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Apache Spark reassigned SPARK-12297:
Assignee: (was: Apache Spark)
> Add work-around for Parquet/Hive int96 timestamp bug.
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Apache Spark commented on SPARK-12297:
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User 'squito' has created a pull request for this issue:
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Apache Spark reassigned SPARK-12297:
Assignee: Apache Spark
> Add work-around for Parquet/Hive int96 timestamp bug.
>
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Arthur Rand commented on SPARK-21842:
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Hey [~kalvinnchau]
I'm currently of the mind that using the
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Apache Spark reassigned SPARK-22032:
Assignee: Apache Spark
> Speed up StructType.fromInternal
>
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Apache Spark reassigned SPARK-22032:
Assignee: (was: Apache Spark)
> Speed up StructType.fromInternal
>
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Apache Spark commented on SPARK-22032:
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User 'maver1ck' has created a pull request for this issue:
Maciej Bryński created SPARK-22032:
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Summary: Speed up StructType.fromInternal
Key: SPARK-22032
URL: https://issues.apache.org/jira/browse/SPARK-22032
Project: Spark
Issue Type: Sub-task
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Sean Owen updated SPARK-22031:
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Target Version/s: (was: 2.3.0)
Labels: (was: newbie)
Priority: Minor
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Nicholas Chammas commented on SPARK-17025:
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I take that back. I won't be able to test this for
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Apache Spark reassigned SPARK-22030:
Assignee: (was: Apache Spark)
> GraphiteSink fails to re-connect to Graphite
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Apache Spark commented on SPARK-22030:
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User 'alexmnyc' has created a pull request for this issue:
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Apache Spark reassigned SPARK-22030:
Assignee: Apache Spark
> GraphiteSink fails to re-connect to Graphite instances behind an
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Laurent Valdes updated SPARK-22031:
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Summary: KMeans - Compute cost for a single vector (was: Compute cost for
a single vector)
Laurent Valdes created SPARK-22031:
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Summary: Compute cost for a single vector
Key: SPARK-22031
URL: https://issues.apache.org/jira/browse/SPARK-22031
Project: Spark
Issue Type: Improvement
Alex Mikhailau created SPARK-22030:
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Summary: GraphiteSink fails to re-connect to Graphite instances
behind an ELB or any other auto-scaled LB
Key: SPARK-22030
URL:
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https://issues.apache.org/jira/browse/SPARK-22029?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=16168017#comment-16168017
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Maciej Bryński commented on SPARK-22029:
I did a proof of concept with functools.lru_cache.
But
Maciej Bryński created SPARK-22029:
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Summary: Cache of _parse_datatype_json_string function
Key: SPARK-22029
URL: https://issues.apache.org/jira/browse/SPARK-22029
Project: Spark
Issue
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Maciej Bryński updated SPARK-22024:
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Summary: [pySpark] Speeding up internal conversion for Spark SQL (was:
[pySpark] Speeding
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Sean Owen commented on SPARK-22028:
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But that's a Java error or limit, even. What would Spark do? You
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Franz Wimmer reopened SPARK-22028:
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Sorry - the Error regarding the Hadoop binaries is normal for this system - I'm
asking because of
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Franz Wimmer updated SPARK-22028:
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Comment: was deleted
(was: The Error with the Hadoop binaries is normal for this system - I'm
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Franz Wimmer updated SPARK-22028:
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Description:
I have a strange environment variable in my Windows operating system:
{code:none}
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Franz Wimmer commented on SPARK-22028:
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The Error with the Hadoop binaries is normal for this system
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Sean Owen resolved SPARK-22028.
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Resolution: Not A Problem
No, it indicates you don't have the win Hadoop binaries available. See the
Franz Wimmer created SPARK-22028:
Summary: spark-submit trips over environment variables
Key: SPARK-22028
URL: https://issues.apache.org/jira/browse/SPARK-22028
Project: Spark
Issue Type:
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https://issues.apache.org/jira/browse/SPARK-22027?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Kazunori Sakamoto updated SPARK-22027:
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Labels: documentation (was: )
> Explanation of default value of GBTRegressor's
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Apache Spark reassigned SPARK-22027:
Assignee: (was: Apache Spark)
> Explanation of default value of GBTRegressor's
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Apache Spark reassigned SPARK-22027:
Assignee: Apache Spark
> Explanation of default value of GBTRegressor's maxIter is
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Apache Spark commented on SPARK-22027:
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User 'exKAZUu' has created a pull request for this issue:
Kazunori Sakamoto created SPARK-22027:
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Summary: Explanation of default value of GBTRegressor's maxIter is
missing in API doc
Key: SPARK-22027
URL: https://issues.apache.org/jira/browse/SPARK-22027
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Xiayun Sun edited comment on SPARK-21996 at 9/15/17 2:30 PM:
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I can reproduce
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Xiayun Sun commented on SPARK-21996:
I can reproduce this issue for master branch, and found out it
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Apache Spark commented on SPARK-21996:
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User 'xysun' has created a pull request for this issue:
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https://issues.apache.org/jira/browse/SPARK-21996?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Apache Spark reassigned SPARK-21996:
Assignee: Apache Spark
> Streaming ignores files with spaces in the file names
>
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Apache Spark reassigned SPARK-21996:
Assignee: (was: Apache Spark)
> Streaming ignores files with spaces in the file names
Wenchen Fan created SPARK-22026:
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Summary: data source v2 write path
Key: SPARK-22026
URL: https://issues.apache.org/jira/browse/SPARK-22026
Project: Spark
Issue Type: Sub-task
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Maciej Bryński updated SPARK-22024:
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Description:
fromInternal methods of pySpark datatypes are bottleneck when using pySpark.
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Nick Pentreath reassigned SPARK-21958:
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Assignee: Travis Hegner
> Attempting to save large Word2Vec model hangs driver in
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Nick Pentreath resolved SPARK-21958.
Resolution: Fixed
Fix Version/s: 2.3.0
Issue resolved by pull request 19191
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Apache Spark reassigned SPARK-22025:
Assignee: (was: Apache Spark)
> Speeding up fromInternal for StructField
>
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Apache Spark reassigned SPARK-22025:
Assignee: Apache Spark
> Speeding up fromInternal for StructField
>
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Apache Spark commented on SPARK-22025:
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User 'maver1ck' has created a pull request for this issue:
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https://issues.apache.org/jira/browse/SPARK-22012?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Karan Singh updated SPARK-22012:
Description:
My Spark Streaming duration is 5 seconds (5000) and kafka is all at its default
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Karan Singh edited comment on SPARK-19275 at 9/15/17 1:02 PM:
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Hi Team ,
My
Maciej Bryński created SPARK-22025:
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Summary: Speeding up fromInternal for StructField
Key: SPARK-22025
URL: https://issues.apache.org/jira/browse/SPARK-22025
Project: Spark
Issue Type:
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https://issues.apache.org/jira/browse/SPARK-22024?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Maciej Bryński updated SPARK-22024:
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Summary: [pySpark] Speeding up fromInternal methods (was: Speeding up
fromInternal methods)
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https://issues.apache.org/jira/browse/SPARK-22010?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Maciej Bryński updated SPARK-22010:
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Issue Type: Sub-task (was: Improvement)
Parent: SPARK-22024
> Slow fromInternal
Maciej Bryński created SPARK-22024:
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Summary: Speeding up fromInternal methods
Key: SPARK-22024
URL: https://issues.apache.org/jira/browse/SPARK-22024
Project: Spark
Issue Type: Improvement
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https://issues.apache.org/jira/browse/SPARK-7276?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=16167814#comment-16167814
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Barry Becker commented on SPARK-7276:
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Isn't there still a problem with withColumn performance in
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Nick Pentreath commented on SPARK-22021:
Why a JavaScript function? I think this is not a good
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Jurgis Pods edited comment on SPARK-21994 at 9/15/17 12:13 PM:
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I have
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Jurgis Pods commented on SPARK-21994:
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I have updated to CDH 5.12.1 and the problem persists. There
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Jurgis Pods updated SPARK-21994:
Description:
This seems to be a new bug introduced in Spark 2.2, since it did not occur
under
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Oli Hall updated SPARK-22023:
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Description:
I've been testing some existing PySpark code after migrating to Python3, and
there seems
Oli Hall created SPARK-22023:
Summary: Multi-column Spark SQL UDFs broken in Python 3
Key: SPARK-22023
URL: https://issues.apache.org/jira/browse/SPARK-22023
Project: Spark
Issue Type: Bug
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Apache Spark reassigned SPARK-22021:
Assignee: (was: Apache Spark)
> Add a feature transformation to accept a function and
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Apache Spark commented on SPARK-22021:
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User 'narahari92' has created a pull request for this issue:
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https://issues.apache.org/jira/browse/SPARK-22021?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Apache Spark reassigned SPARK-22021:
Assignee: Apache Spark
> Add a feature transformation to accept a function and apply it
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https://issues.apache.org/jira/browse/SPARK-22019?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=16167734#comment-16167734
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Jen-Ming Chung edited comment on SPARK-22019 at 9/15/17 11:29 AM:
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The
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Hosur Narahari commented on SPARK-22021:
If I just apply this function, I can't use it in spark's
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Jen-Ming Chung edited comment on SPARK-22019 at 9/15/17 11:28 AM:
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The
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Jen-Ming Chung commented on SPARK-22019:
The alternative is giving the explicit schema instead
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Jen-Ming Chung edited comment on SPARK-22019 at 9/15/17 11:18 AM:
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Hi
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Jen-Ming Chung commented on SPARK-22019:
Hi [~client.test],
The schema inferred after
Maciej Bryński created SPARK-22022:
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Summary: Unable to use Python Profiler with SparkSession
Key: SPARK-22022
URL: https://issues.apache.org/jira/browse/SPARK-22022
Project: Spark
Issue
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https://issues.apache.org/jira/browse/SPARK-22021?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=16167722#comment-16167722
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Sean Owen commented on SPARK-22021:
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Why can't you just apply this function? Or implement Transformer.
Hosur Narahari created SPARK-22021:
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Summary: Add a feature transformation to accept a function and
apply it on all rows of dataframe
Key: SPARK-22021
URL: https://issues.apache.org/jira/browse/SPARK-22021
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Apache Spark reassigned SPARK-21780:
Assignee: Apache Spark
> Simpler Dataset.sample API in R
>
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Apache Spark commented on SPARK-21780:
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User 'HyukjinKwon' has created a pull request for this
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Apache Spark reassigned SPARK-21780:
Assignee: (was: Apache Spark)
> Simpler Dataset.sample API in R
>
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https://issues.apache.org/jira/browse/SPARK-22020?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Sean Owen resolved SPARK-22020.
---
Resolution: Duplicate
> Support session local timezone
> --
>
>
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Sean Owen resolved SPARK-20921.
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Resolution: Duplicate
> While reading from oracle database, it converts to wrong type.
>
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Apache Spark commented on SPARK-21713:
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User 'joseph-torres' has created a pull request for this
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https://issues.apache.org/jira/browse/SPARK-21987?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Xiao Li resolved SPARK-21987.
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Resolution: Fixed
Assignee: Wenchen Fan
Fix Version/s: 2.3.0
> Spark 2.3 cannot read 2.2
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https://issues.apache.org/jira/browse/SPARK-22002?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Xiao Li resolved SPARK-22002.
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Resolution: Fixed
Assignee: Yuming Wang
Fix Version/s: 2.3.0
> Read JDBC table use
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Jurgis Pods commented on SPARK-21994:
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Thank you for testing. Which version of Hive are you using? It
Navya Krishnappa created SPARK-22020:
Summary: Support session local timezone
Key: SPARK-22020
URL: https://issues.apache.org/jira/browse/SPARK-22020
Project: Spark
Issue Type: Bug
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https://issues.apache.org/jira/browse/SPARK-21902?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Saisai Shao updated SPARK-21902:
Priority: Trivial (was: Major)
> BlockManager.doPut will hide actually exception when exception
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Saisai Shao updated SPARK-21902:
Issue Type: Improvement (was: Wish)
> BlockManager.doPut will hide actually exception when
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Saisai Shao reassigned SPARK-21902:
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Assignee: zhoukang
> BlockManager.doPut will hide actually exception when exception thrown
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Saisai Shao resolved SPARK-21902.
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Resolution: Fixed
Fix Version/s: 2.3.0
Issue resolved by pull request 19171
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Yuming Wang commented on SPARK-20921:
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Fixed by https://github.com/apache/spark/pull/18266.
> While
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