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Juefei Yan commented on SPARK-47287:
I tried the code on 3.4 branch, cannot reproduce this problem
[ https://issues.apache.org/jira/browse/SPARK-43251 ]
Liang Yan deleted comment on SPARK-43251:
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was (Author: JIRAUSER299156):
I will work on this issue.
> Assign a name to the error class _LEGACY_ERROR_TEMP_2015
>
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Liang Yan commented on SPARK-43251:
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I will work on this issue.
> Assign a name to the error class
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https://issues.apache.org/jira/browse/SPARK-42844?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=17709235#comment-17709235
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Liang Yan commented on SPARK-42844:
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[~maxgekk], I have added PR.
> Assign a name to the error class
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Liang Yan resolved SPARK-42711.
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Resolution: Not A Problem
The original codes are just a copy of upstream. And the changes not fix
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Liang Yan closed SPARK-42711.
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> build/sbt usage error messages and shellcheck warn/error
>
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Liang Yan updated SPARK-42711:
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Description:
The build/sbt tool's usage information has some missing content:
{code:java}
(base)
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Liang Yan updated SPARK-42711:
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Summary: build/sbt usage error messages and shellcheck warn/error (was:
build/sbt usage error
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Liang Yan commented on SPARK-42711:
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I am preparing my PR for this issue. Please assign it to me.
>
Liang Yan created SPARK-42711:
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Summary: build/sbt usage error messages about java-home
Key: SPARK-42711
URL: https://issues.apache.org/jira/browse/SPARK-42711
Project: Spark
Issue Type: Bug
Wei Yan created SPARK-42395:
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Summary: The code logic of the configmap max size validation lacks
extra content
Key: SPARK-42395
URL: https://issues.apache.org/jira/browse/SPARK-42395
Project: Spark
Wei Yan created SPARK-42344:
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Summary: The default size of the CONFIG_MAP_MAXSIZE should not be
greater than 1048576
Key: SPARK-42344
URL: https://issues.apache.org/jira/browse/SPARK-42344
Project: Spark
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https://issues.apache.org/jira/browse/SPARK-24666?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=16957623#comment-16957623
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carlos yan commented on SPARK-24666:
I also get this question, and my spark version is 2.1.0. I used
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https://issues.apache.org/jira/browse/SPARK-27894?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Jeffrey(Xilang) Yan updated SPARK-27894:
Description:
In PySpark Steaming, if checkpoint enabled and there is a
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Jeffrey(Xilang) Yan updated SPARK-27894:
Description:
In PySpark Steaming, if checkpoint enabled and there is a
Jeffrey(Xilang) Yan created SPARK-27894:
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Summary: PySpark streaming transform RDD join not works when
checkpoint enabled
Key: SPARK-27894
URL: https://issues.apache.org/jira/browse/SPARK-27894
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https://issues.apache.org/jira/browse/SPARK-5594?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=16833632#comment-16833632
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Jeffrey(Xilang) Yan commented on SPARK-5594:
There is a bug before 2.2.3/2.3.0
If you met
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https://issues.apache.org/jira/browse/SPARK-24374?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=16490307#comment-16490307
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Wei Yan commented on SPARK-24374:
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Thanks [~mengxr] for the initiative and the doc. cc [~leftnoteasy]
Yan created SPARK-21576:
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Summary: Spark caching difference between 2.0.2 and 2.1.1
Key: SPARK-21576
URL: https://issues.apache.org/jira/browse/SPARK-21576
Project: Spark
Issue Type: Bug
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https://issues.apache.org/jira/browse/SPARK-3165?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=15935646#comment-15935646
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Facai Yan edited comment on SPARK-3165 at 3/22/17 1:57 AM:
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Do you mean that:
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Facai Yan commented on SPARK-3165:
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Do you mean that:
TreePoint.binnedFeatures is Array[int], which
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https://issues.apache.org/jira/browse/SPARK-19320?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=15904479#comment-15904479
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Ji Yan commented on SPARK-19320:
i'm proposing to add a configuration parameter to guarantee a hard limit
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Ji Yan commented on SPARK-19320:
[~tnachen] in this case, should we rename spark.mesos.gpus.max to
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https://issues.apache.org/jira/browse/SPARK-19740?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=15884487#comment-15884487
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Ji Yan commented on SPARK-19740:
the problem is that when running Spark on Mesos, there is no way to run
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https://issues.apache.org/jira/browse/SPARK-19740?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=15884426#comment-15884426
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Ji Yan commented on SPARK-19740:
proposed change:
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Ji Yan updated SPARK-19740:
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Description:
When running Spark on Mesos with docker containerizer, the spark executors are
always launched
Ji Yan created SPARK-19740:
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Summary: Spark executor always runs as root when running on mesos
Key: SPARK-19740
URL: https://issues.apache.org/jira/browse/SPARK-19740
Project: Spark
Issue Type: Bug
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https://issues.apache.org/jira/browse/SPARK-15777?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=15593229#comment-15593229
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Yan commented on SPARK-15777:
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One approach could be first tagging a subtree as specific to a data source,
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Yan commented on SPARK-15777:
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There is a paragraph in the design doc about the ordering of rule application
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Yan commented on SPARK-15777:
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1) Currently the rules are applied on a per-session basis. Right, ideally they
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Yan commented on SPARK-15777:
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A design document is just attached above. We realize that this task requires
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Yan updated SPARK-15777:
Attachment: SparkFederationDesign.pdf
> Catalog federation
> --
>
> Key:
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Yan commented on SPARK-17556:
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For 2), I think BitTorrent won't help in the case of all-to-all transfers,
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Yan commented on SPARK-17556:
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A few comments of mine are as follows:
1) The "one-executor collection"
Yan created SPARK-17375:
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Summary: Star Join Optimization
Key: SPARK-17375
URL: https://issues.apache.org/jira/browse/SPARK-17375
Project: Spark
Issue Type: Improvement
Components: SQL
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https://issues.apache.org/jira/browse/SPARK-14521?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=15267811#comment-15267811
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Yan commented on SPARK-14521:
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Yes, we are serializing the fields that should not be serialized. Please check
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https://issues.apache.org/jira/browse/SPARK-14507?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=15240616#comment-15240616
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Yan commented on SPARK-14507:
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In terms of Hive support vs Spark SQL support, the "external table" concept
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https://issues.apache.org/jira/browse/SPARK-11368?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=15233231#comment-15233231
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Yan commented on SPARK-11368:
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The issue seems to be gone with the latest master code (for 2.0):
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https://issues.apache.org/jira/browse/SPARK-14389?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=15231655#comment-15231655
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Yan commented on SPARK-14389:
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Actually the current Master branch does not have the issue; while 1.6.0 has.
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https://issues.apache.org/jira/browse/SPARK-14389?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=15231013#comment-15231013
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Yan commented on SPARK-14389:
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[~Steve Johnston]
I guess the memory eater is probably not from the broadcast
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https://issues.apache.org/jira/browse/SPARK-12988?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=15128829#comment-15128829
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Yan commented on SPARK-12988:
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My thinking is that projections should parse the column names; while the
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https://issues.apache.org/jira/browse/SPARK-12988?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=15127883#comment-15127883
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Yan commented on SPARK-12988:
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[~marmbrus] For the same reason of "`a.c` is an invalid column name. toDF(...)
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https://issues.apache.org/jira/browse/SPARK-12686?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=15088343#comment-15088343
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Yan commented on SPARK-12686:
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Spark-12449 seems to be a super set of this Jira.
> Support group-by push
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https://issues.apache.org/jira/browse/SPARK-12449?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=15088334#comment-15088334
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Yan commented on SPARK-12449:
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Stephan, thanks for your explanations and questions. My answers are as
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https://issues.apache.org/jira/browse/SPARK-12449?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=15087983#comment-15087983
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Yan commented on SPARK-12449:
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Stephan,
By "partial op" I mean, for instance, partial map-side aggregation.
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Yan commented on SPARK-12449:
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To push down map-side (partial) ops, Physical Plan would need to be checked I
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Yan commented on SPARK-12449:
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Conceivably, if only logical plan is used, the Spark SQL execution would
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https://issues.apache.org/jira/browse/SPARK-12449?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=15068447#comment-15068447
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Yan commented on SPARK-12449:
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A few thoughts on the capabilities of this "CatalystSource Interface":
1)
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https://issues.apache.org/jira/browse/SPARK-7825?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Tang Yan updated SPARK-7825:
Affects Version/s: (was: 1.3.1)
(was: 1.2.2)
(was:
Tang Yan created SPARK-7825:
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Summary: Poor performance in Cross Product due to no combine
operations for small files.
Key: SPARK-7825
URL: https://issues.apache.org/jira/browse/SPARK-7825
Project: Spark
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https://issues.apache.org/jira/browse/SPARK-7270?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Feixiang Yan updated SPARK-7270:
Description:
Create a hive table with two partitons,the first type is bigint and the second
type
Feixiang Yan created SPARK-7270:
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Summary: StringType dynamic partition cast to DecimalType in Spark
Sql Hive
Key: SPARK-7270
URL: https://issues.apache.org/jira/browse/SPARK-7270
Project: Spark
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Yan commented on SPARK-3306:
If by global singleton object, you meant it to be in the Executor
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Yan commented on SPARK-3306:
The external resource primarily will serve the purpose of reuse
Lu Yan created SPARK-5614:
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Summary: Predicate pushdown through Generate
Key: SPARK-5614
URL: https://issues.apache.org/jira/browse/SPARK-5614
Project: Spark
Issue Type: Improvement
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https://issues.apache.org/jira/browse/SPARK-3880?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Yan updated SPARK-3880:
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Attachment: SparkSQLOnHBase_v2.0.docx
HBase as data source to SparkSQL
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Yan updated SPARK-3880:
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Attachment: (was: SparkSQLOnHBase_v2.docx)
HBase as data source to SparkSQL
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Yan updated SPARK-3880:
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Attachment: SparkSQLOnHBase_v2.docx
Version 2
HBase as data source to SparkSQL
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Yan commented on SPARK-3306:
Yes, close/cleanup will be supported, plus a show/list
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https://issues.apache.org/jira/browse/SPARK-3880?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanelfocusedCommentId=14167006#comment-14167006
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Yan commented on SPARK-3880:
The new context is intended to be very light-weighted. We noticed
Yan created SPARK-3880:
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Summary: HBase as data source to SparkSQL
Key: SPARK-3880
URL: https://issues.apache.org/jira/browse/SPARK-3880
Project: Spark
Issue Type: New Feature
Reporter: Yan
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Yan updated SPARK-3880:
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Component/s: SQL
Fix Version/s: (was: 1.3.0)
HBase as data source to SparkSQL
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Yan updated SPARK-3880:
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Attachment: HBaseOnSpark.docx
Design Document
HBase as data source to SparkSQL
Yan created SPARK-3306:
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Summary: Addition of external resource dependency in executors
Key: SPARK-3306
URL: https://issues.apache.org/jira/browse/SPARK-3306
Project: Spark
Issue Type: New Feature
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