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https://issues.apache.org/jira/browse/SPARK-23722?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16405181#comment-16405181
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Sital Kedia commented on SPARK-23722:
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Actually this is a duplicate of SPARK-21281 an
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Sital Kedia resolved SPARK-23722.
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Resolution: Duplicate
> Add support for inserting empty map or array to table
> -
Sital Kedia created SPARK-23722:
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Summary: Add support for inserting empty map or array to table
Key: SPARK-23722
URL: https://issues.apache.org/jira/browse/SPARK-23722
Project: Spark
Issue Typ
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https://issues.apache.org/jira/browse/SPARK-18134?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16394571#comment-16394571
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Sital Kedia commented on SPARK-18134:
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[~hvanhovell]- What is the state of this JIRA?
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https://issues.apache.org/jira/browse/SPARK-23502?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16380942#comment-16380942
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Sital Kedia commented on SPARK-23502:
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>> what happens when you operate on {{sc}} bef
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Sital Kedia commented on SPARK-23502:
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I realized that we are printing the web url li
Sital Kedia created SPARK-23502:
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Summary: Support async init of spark context during spark-shell
startup
Key: SPARK-23502
URL: https://issues.apache.org/jira/browse/SPARK-23502
Project: Spark
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https://issues.apache.org/jira/browse/SPARK-23310?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16351097#comment-16351097
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Sital Kedia commented on SPARK-23310:
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https://github.com/apache/spark/pull/20492
>
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Sital Kedia commented on SPARK-23310:
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[~yhuai] - Sorry about introducing the regress
Sital Kedia created SPARK-22827:
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Summary: Avoid throwing OutOfMemoryError in case of exception in
spill
Key: SPARK-22827
URL: https://issues.apache.org/jira/browse/SPARK-22827
Project: Spark
Sital Kedia created SPARK-22312:
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Summary: Spark job stuck with no executor due to bug in Executor
Allocation Manager
Key: SPARK-22312
URL: https://issues.apache.org/jira/browse/SPARK-22312
Project: Spa
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https://issues.apache.org/jira/browse/SPARK-21867?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16163705#comment-16163705
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Sital Kedia commented on SPARK-21867:
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[~rxin] - You are right, it is very tricky to
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Sital Kedia commented on SPARK-21867:
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cc - [~rxin], [~joshrosen], [~sameer] - What d
Sital Kedia created SPARK-21867:
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Summary: Support async spilling in UnsafeShuffleWriter
Key: SPARK-21867
URL: https://issues.apache.org/jira/browse/SPARK-21867
Project: Spark
Issue Type: Impro
Sital Kedia created SPARK-21834:
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Summary: Incorrect executor request in case of dynamic allocation
Key: SPARK-21834
URL: https://issues.apache.org/jira/browse/SPARK-21834
Project: Spark
Issue
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https://issues.apache.org/jira/browse/SPARK-21833?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Sital Kedia closed SPARK-21833.
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Resolution: Duplicate
Duplicate of SPARK-20540
> CoarseGrainedSchedulerBackend leaks executors in ca
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Sital Kedia updated SPARK-21833:
Description:
We have seen this issue in coarse grained scheduler that in case of dynamic
executor
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Sital Kedia commented on SPARK-21833:
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Actually, SPARK-20540 already addressed this i
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Sital Kedia updated SPARK-21833:
Description:
We have seen this issue in coarse grained scheduler that in case of dynamic
executor
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https://issues.apache.org/jira/browse/SPARK-21833?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Sital Kedia updated SPARK-21833:
Description:
We have seen this issue in coarse grained scheduler that in case of dynamic
executor
Sital Kedia created SPARK-21833:
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Summary: CoarseGrainedSchedulerBackend leaks executors in case of
dynamic allocation
Key: SPARK-21833
URL: https://issues.apache.org/jira/browse/SPARK-21833
Project: Sp
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https://issues.apache.org/jira/browse/SPARK-19112?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16109784#comment-16109784
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Sital Kedia commented on SPARK-19112:
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[~sowen], [~tgraves] - Using zstd compression
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https://issues.apache.org/jira/browse/SPARK-21444?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16090800#comment-16090800
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Sital Kedia commented on SPARK-21444:
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Any idea how to fix this issue?
> Fetch failu
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Sital Kedia commented on SPARK-21444:
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cc - [~joshrosen]
> Fetch failure due to node
Sital Kedia created SPARK-21444:
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Summary: Fetch failure due to node reboot causes job failure
Key: SPARK-21444
URL: https://issues.apache.org/jira/browse/SPARK-21444
Project: Spark
Issue Type:
Sital Kedia created SPARK-21113:
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Summary: Support for read ahead input stream to amortize disk IO
cost in the Spill reader
Key: SPARK-21113
URL: https://issues.apache.org/jira/browse/SPARK-21113
Projec
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https://issues.apache.org/jira/browse/SPARK-18838?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16046957#comment-16046957
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Sital Kedia commented on SPARK-18838:
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[~joshrosen] - The PR for my change to multi-t
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https://issues.apache.org/jira/browse/SPARK-20178?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16030284#comment-16030284
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Sital Kedia commented on SPARK-20178:
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https://github.com/apache/spark/pull/18150
>
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Sital Kedia commented on SPARK-20178:
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>> So to get the robustness for now I'm fine w
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Sital Kedia commented on SPARK-18838:
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[~joshrosen] - >> Alternatively, we could use
Sital Kedia created SPARK-20640:
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Summary: Make rpc timeout and retry for shuffle registration
configurable
Key: SPARK-20640
URL: https://issues.apache.org/jira/browse/SPARK-20640
Project: Spark
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Sital Kedia commented on SPARK-20178:
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[~tgraves] Thanks for creating the JIRA and dr
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Sital Kedia closed SPARK-20163.
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Resolution: Duplicate
> Kill all running tasks in a stage in case of fetch failure
>
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Sital Kedia commented on SPARK-20163:
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Thanks [~imranr], closing this as this is dupl
Sital Kedia created SPARK-20163:
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Summary: Kill all running tasks in a stage in case of fetch failure
Key: SPARK-20163
URL: https://issues.apache.org/jira/browse/SPARK-20163
Project: Spark
Issu
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https://issues.apache.org/jira/browse/SPARK-3577?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15947669#comment-15947669
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Sital Kedia commented on SPARK-3577:
I am making a change to report correct spill data
Sital Kedia created SPARK-20091:
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Summary: DagScheduler should allow running concurrent attempts of
a stage in case of multiple fetch failure
Key: SPARK-20091
URL: https://issues.apache.org/jira/browse/SPARK-20091
Sital Kedia created SPARK-20074:
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Summary: Make buffer size in unsafe external sorter configurable
Key: SPARK-20074
URL: https://issues.apache.org/jira/browse/SPARK-20074
Project: Spark
Issue T
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Sital Kedia updated SPARK-20014:
Description:
When the individual partition size in a spill is small,
mergeSpillsWithTransferTo met
Sital Kedia created SPARK-20014:
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Summary: Optimize mergeSpillsWithFileStream method
Key: SPARK-20014
URL: https://issues.apache.org/jira/browse/SPARK-20014
Project: Spark
Issue Type: Improveme
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https://issues.apache.org/jira/browse/SPARK-19837?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15897961#comment-15897961
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Sital Kedia commented on SPARK-19837:
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`SparkHiveDynamicPartitionWriterContainer` has
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Sital Kedia closed SPARK-19837.
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Resolution: Fixed
> Fetch failure throws a SparkException in SparkHiveWriter
> --
Sital Kedia created SPARK-19837:
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Summary: Fetch failure throws a SparkException in SparkHiveWriter
Key: SPARK-19837
URL: https://issues.apache.org/jira/browse/SPARK-19837
Project: Spark
Issue
Sital Kedia created SPARK-19803:
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Summary: Flaky BlockManagerProactiveReplicationSuite tests
Key: SPARK-19803
URL: https://issues.apache.org/jira/browse/SPARK-19803
Project: Spark
Issue Type: B
Sital Kedia created SPARK-19753:
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Summary: Remove all shuffle files on a host in case of slave lost
of fetch failure
Key: SPARK-19753
URL: https://issues.apache.org/jira/browse/SPARK-19753
Project: Spar
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Sital Kedia commented on SPARK-18838:
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cc - [~kayousterhout]
> High latency of event
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Sital Kedia updated SPARK-18838:
Description:
Currently we are observing the issue of very high event processing delay in
driver's
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Sital Kedia commented on SPARK-18838:
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[~zsxwing] - Its not only the ExecutorAllocati
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Sital Kedia updated SPARK-18838:
Description:
Currently we are observing the issue of very high event processing delay in
driver's
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https://issues.apache.org/jira/browse/SPARK-18838?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15744086#comment-15744086
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Sital Kedia commented on SPARK-18838:
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[~rxin], [~zsxwing] - Any thoughts on this?
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Sital Kedia updated SPARK-18838:
Description:
Currently we are observing the issue of very high event processing delay in
driver's
Sital Kedia created SPARK-18838:
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Summary: High latency of event processing for large jobs
Key: SPARK-18838
URL: https://issues.apache.org/jira/browse/SPARK-18838
Project: Spark
Issue Type: Imp
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https://issues.apache.org/jira/browse/SPARK-13510?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15671415#comment-15671415
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Sital Kedia commented on SPARK-13510:
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[~shenhong] - We are seeing the same issue on
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Sital Kedia updated SPARK-16827:
Summary: Stop reporting spill metrics as shuffle metrics (was: Query with
Join produces excessive
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https://issues.apache.org/jira/browse/SPARK-17839?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Sital Kedia updated SPARK-17839:
Summary: Use Nio's directbuffer instead of BufferedInputStream in order to
avoid additional copy fr
Sital Kedia created SPARK-17839:
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Summary: UnsafeSorterSpillReader should use Nio's directbuffer to
read the spill files in order to avoid additional copy
Key: SPARK-17839
URL: https://issues.apache.org/jira/browse/
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https://issues.apache.org/jira/browse/SPARK-17509?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Sital Kedia updated SPARK-17509:
Affects Version/s: 2.0.0
Description: Profiling a job, we saw that patten matching in wrap
Sital Kedia created SPARK-17509:
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Summary: When wrapping catalyst datatype to Hive data type avoid
pattern matching
Key: SPARK-17509
URL: https://issues.apache.org/jira/browse/SPARK-17509
Project: Spark
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https://issues.apache.org/jira/browse/SPARK-16922?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15469092#comment-15469092
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Sital Kedia commented on SPARK-16922:
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There is no noticable performance gain I obser
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Sital Kedia commented on SPARK-16922:
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[~davies] - Thanks for looking into this. I t
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Sital Kedia commented on SPARK-16922:
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Thanks for the fix [~davies]. I will test this
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Sital Kedia closed SPARK-17164.
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Resolution: Won't Fix
> Query with colon in the table name fails to parse in 2.0
> --
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Sital Kedia commented on SPARK-17164:
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Thanks [~rxin], [~hvanhovell], that makes sens
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Sital Kedia commented on SPARK-17164:
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cc - [~hvanhovell], [~rxin]
> Query with colo
Sital Kedia created SPARK-17164:
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Summary: Query with colon in the table name fails to parse in 2.0
Key: SPARK-17164
URL: https://issues.apache.org/jira/browse/SPARK-17164
Project: Spark
Issue
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https://issues.apache.org/jira/browse/SPARK-16922?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15427429#comment-15427429
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Sital Kedia commented on SPARK-16922:
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Kryo
> Query with Broadcast Hash join fails
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Sital Kedia commented on SPARK-16922:
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>> Could you also try to disable the dense mod
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Sital Kedia commented on SPARK-16922:
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The failure is deterministic, we are reproduci
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https://issues.apache.org/jira/browse/SPARK-17113?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Sital Kedia updated SPARK-17113:
Summary: Job failure due to Executor OOM in offheap mode (was: Job failure
due to Executor OOM)
>
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https://issues.apache.org/jira/browse/SPARK-17113?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15425216#comment-15425216
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Sital Kedia commented on SPARK-17113:
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cc - [~davies]
> Job failure due to Executor
Sital Kedia created SPARK-17113:
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Summary: Job failure due to Executor OOM
Key: SPARK-17113
URL: https://issues.apache.org/jira/browse/SPARK-17113
Project: Spark
Issue Type: Bug
Affects Ver
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Sital Kedia commented on SPARK-16922:
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Yes, I have the above mentioned PR as well.
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Sital Kedia commented on SPARK-16922:
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I am using the fix in https://github.com/apach
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Sital Kedia updated SPARK-16922:
Summary: Query with Broadcast Hash join fails due to executor OOM in Spark
2.0 (was: Query failure
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Sital Kedia edited comment on SPARK-16922 at 8/12/16 8:06 PM:
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Sital Kedia commented on SPARK-16922:
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I found that the regression was introduced in
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Sital Kedia commented on SPARK-16922:
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Update - The query works fine when Broadcast h
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Sital Kedia commented on SPARK-16922:
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PS - Rerunning the query with spark.sql.codege
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Sital Kedia commented on SPARK-16922:
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cc - [~rxin]
> Query failure due to executor
Sital Kedia created SPARK-16922:
---
Summary: Query failure due to executor OOM in Spark 2.0
Key: SPARK-16922
URL: https://issues.apache.org/jira/browse/SPARK-16922
Project: Spark
Issue Type: Bug
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https://issues.apache.org/jira/browse/SPARK-16827?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15402461#comment-15402461
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Sital Kedia commented on SPARK-16827:
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Performance is worse for this job. But I suspe
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Sital Kedia commented on SPARK-16827:
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Actually it seems like this is a bug in shuffl
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Sital Kedia edited comment on SPARK-16827 at 8/1/16 12:52 AM:
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Sital Kedia commented on SPARK-16827:
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That is not the case. There is no broadcast jo
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Sital Kedia updated SPARK-16827:
Description:
One of our hive job which looks like this -
{code}
SELECT userid
FROM table1
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Sital Kedia commented on SPARK-16827:
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[~rxin] - Any idea how to debug this issue?
>
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Sital Kedia updated SPARK-16827:
Description:
One of our hive job which looks like this -
{code}
SELECT userid
FROM table1
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Sital Kedia updated SPARK-16827:
Summary: Query with Join produces excessive amount of shuffle data (was:
Query with Join produces
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Sital Kedia updated SPARK-16827:
Description:
One of our hive job which looks like this -
{code]
SELECT userid
FROM table1
Sital Kedia created SPARK-16827:
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Summary: Query with Join produces excessive shuffle data
Key: SPARK-16827
URL: https://issues.apache.org/jira/browse/SPARK-16827
Project: Spark
Issue Type: Bug
Sital Kedia created SPARK-15958:
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Summary: Make initial buffer size for the Sorter configurable
Key: SPARK-15958
URL: https://issues.apache.org/jira/browse/SPARK-15958
Project: Spark
Issue Type
Sital Kedia created SPARK-15569:
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Summary: Executors spending significant time in
DiskObjectWriter.updateBytesWritten function
Key: SPARK-15569
URL: https://issues.apache.org/jira/browse/SPARK-15569
Pro
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https://issues.apache.org/jira/browse/SPARK-15391?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15289791#comment-15289791
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Sital Kedia commented on SPARK-15391:
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cc- [~davies] - Any idea how to fix this issu
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https://issues.apache.org/jira/browse/SPARK-15391?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Sital Kedia updated SPARK-15391:
Description:
While running a query, we are seeing a lot of executor OOM while doing TimSort.
Stack
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https://issues.apache.org/jira/browse/SPARK-15391?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Sital Kedia updated SPARK-15391:
Description:
While running a query, we are seeing a lot of executor OOM while doing TimSort.
Stack
Sital Kedia created SPARK-15391:
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Summary: Spark executor OOM during TimSort
Key: SPARK-15391
URL: https://issues.apache.org/jira/browse/SPARK-15391
Project: Spark
Issue Type: Bug
R
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https://issues.apache.org/jira/browse/SPARK-13850?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15286906#comment-15286906
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Sital Kedia commented on SPARK-13850:
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I am not 100% sure of the root cause, but I su
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https://issues.apache.org/jira/browse/SPARK-13850?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15283110#comment-15283110
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Sital Kedia commented on SPARK-13850:
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I have found a workaround for this issue. Plea
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https://issues.apache.org/jira/browse/SPARK-15233?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Sital Kedia updated SPARK-15233:
Affects Version/s: 1.6.1
Priority: Minor (was: Major)
Description: Currently
Sital Kedia created SPARK-15233:
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Summary: Spark UI should show metrics for hdfs read write latency
Key: SPARK-15233
URL: https://issues.apache.org/jira/browse/SPARK-15233
Project: Spark
Issue
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