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Ke Jia updated SPARK-47773:
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Description:
SPIP doc:
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Ke Jia edited comment on SPARK-47773 at 4/22/24 6:22 AM:
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We have refined the
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Ke Jia edited comment on SPARK-47773 at 4/22/24 6:22 AM:
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We have refined the
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Ke Jia commented on SPARK-47773:
We have refined the above
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Ke Jia commented on SPARK-47773:
[~viirya] Great, I have added comment permissions in the SPIP Doc. I'm
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Ke Jia updated SPARK-47773:
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Description:
SPIP doc:
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Ke Jia updated SPARK-47773:
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Description:
This
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Ke Jia updated SPARK-47773:
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Description:
This
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Ke Jia updated SPARK-47773:
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Description:
This
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Ke Jia updated SPARK-47773:
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Description: This
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Ke Jia updated SPARK-47773:
---
Description: This SPIP outlines the integration of Gluten's physical plan
conversion, validation, and
Ke Jia created SPARK-47773:
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Summary: Enhancing the Flexibility of Spark's Physical Plan to
Enable Execution on Various Native Engines
Key: SPARK-47773
URL: https://issues.apache.org/jira/browse/SPARK-47773
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https://issues.apache.org/jira/browse/SPARK-43814?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Ke Jia updated SPARK-43814:
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Description:
When constructing the DecimalType in
CatalystTypeConverters.convertToCatalyst(), spark
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Ke Jia updated SPARK-43814:
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Summary: Spark cannot construct the DecimalType in
CatalystTypeConverters.convertToCatalyst() API (was:
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Ke Jia updated SPARK-43814:
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Description:
When using the df.collect() result to construct the DecimalType in
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Ke Jia updated SPARK-43814:
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Description:
When using the df.collect() result to construct the DecimalType in
Decimal scale (18) cannot
Ke Jia created SPARK-43814:
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Summary: Spark cannot use the df.collect() result to construct the
DecimalType in CatalystTypeConverters.convertToCatalyst() API
Key: SPARK-43814
URL:
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Ke Jia updated SPARK-43240:
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Affects Version/s: 3.3.2
(was: 3.2.2)
> df.describe() method may- return wrong
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Ke Jia updated SPARK-43240:
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Description: When calling the df.describe() method, the result maybe wrong
when the last RDD is
Ke Jia created SPARK-43240:
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Summary: df.describe() method may- return wrong result if the last
RDD is RDD[UnsafeRow]
Key: SPARK-43240
URL: https://issues.apache.org/jira/browse/SPARK-43240
Project: Spark
Ke Jia created SPARK-36898:
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Summary: Make the shuffle hash join factor configurable
Key: SPARK-36898
URL: https://issues.apache.org/jira/browse/SPARK-36898
Project: Spark
Issue Type: Improvement
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Ke Jia updated SPARK-35710:
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Description: Support DPP + AQE when no reused broadcast exchange.
> Support DPP + AQE when no reused
Ke Jia created SPARK-35710:
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Summary: Support DPP + AQE when no reused broadcast exchange
Key: SPARK-35710
URL: https://issues.apache.org/jira/browse/SPARK-35710
Project: Spark
Issue Type:
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Ke Jia updated SPARK-34637:
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Description: We have supported DPP in AQE when the join is Broadcast hash
join before applying the AQE
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Ke Jia updated SPARK-34637:
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Summary: Support DPP in AQE when the boradcast exchange can be reused
(was: Support DPP in AQE when the
Ke Jia created SPARK-34637:
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Summary: Support DPP in AQE when the boradcast exchange can reused
Key: SPARK-34637
URL: https://issues.apache.org/jira/browse/SPARK-34637
Project: Spark
Issue Type:
Ke Jia created SPARK-34168:
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Summary: Support DPP in AQE When the join is Broadcast hash join
before applying the AQE rules
Key: SPARK-34168
URL: https://issues.apache.org/jira/browse/SPARK-34168
Project:
Ke Jia created SPARK-31524:
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Summary: Add metric to the split number for skew partition when
enable AQE
Key: SPARK-31524
URL: https://issues.apache.org/jira/browse/SPARK-31524
Project: Spark
Ke Jia created SPARK-30922:
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Summary: Remove the max split config after changing the multi sub
joins to multi sub partitions
Key: SPARK-30922
URL: https://issues.apache.org/jira/browse/SPARK-30922
Project:
Ke Jia created SPARK-30864:
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Summary: Add the user guide for Adaptive Query Execution
Key: SPARK-30864
URL: https://issues.apache.org/jira/browse/SPARK-30864
Project: Spark
Issue Type: Bug
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Ke Jia updated SPARK-30188:
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Description: Fix the failed unit tests when enable Adaptive Query
Execution. (was: Enable Adaptive Query
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Ke Jia updated SPARK-30549:
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Summary: Fix the subquery metrics showing issue in UI When enable AQE
(was: Fix the subquery metrics
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Ke Jia updated SPARK-30549:
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Description: After merged [https://github.com/apache/spark/pull/25316], the
subquery metrics can not be
Ke Jia created SPARK-30549:
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Summary: Fix the subquery metrics showing issue in UI
Key: SPARK-30549
URL: https://issues.apache.org/jira/browse/SPARK-30549
Project: Spark
Issue Type: Bug
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Ke Jia updated SPARK-30524:
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Description: The OptimizeSkewedJoin will break the outputPartitioning of
origin SMJ. And it may introduce
Ke Jia created SPARK-30524:
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Summary: Disable OptimizeSkewJoin rule if introducing additional
shuffle.
Key: SPARK-30524
URL: https://issues.apache.org/jira/browse/SPARK-30524
Project: Spark
Issue
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Ke Jia updated SPARK-30407:
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Description:
Working on [https://github.com/apache/spark/pull/26813]. With on AQE, the
metric info of
Ke Jia created SPARK-30407:
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Summary: reset the metrics info of AdaptiveSparkPlanExec plan when
enable aqe
Key: SPARK-30407
URL: https://issues.apache.org/jira/browse/SPARK-30407
Project: Spark
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Ke Jia updated SPARK-30403:
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Description: After merged [https://github.com/apache/spark/pull/25854], we
also need to handle the
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Ke Jia updated SPARK-30403:
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Description: After merged [link
title|[https://github.com/apache/spark/pull/25854]], we also need to handle
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Ke Jia updated SPARK-30403:
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Description: After merged
[PR25854|[https://github.com/apache/spark/pull/25854]], we also need to handle
Ke Jia created SPARK-30403:
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Summary: Fix the NoSuchElementException exception when enable AQE
with InSubquery use case
Key: SPARK-30403
URL: https://issues.apache.org/jira/browse/SPARK-30403
Project: Spark
Ke Jia created SPARK-30291:
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Summary: Catch the exception when do materialize in AQE
Key: SPARK-30291
URL: https://issues.apache.org/jira/browse/SPARK-30291
Project: Spark
Issue Type: Bug
Ke Jia created SPARK-30232:
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Summary: Fix the the ArthmeticException by zero when enable AQE
Key: SPARK-30232
URL: https://issues.apache.org/jira/browse/SPARK-30232
Project: Spark
Issue Type: Bug
Ke Jia created SPARK-30213:
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Summary: Remove the mutable status in QueryStage when enable AQE
Key: SPARK-30213
URL: https://issues.apache.org/jira/browse/SPARK-30213
Project: Spark
Issue Type: New
Ke Jia created SPARK-30188:
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Summary: Enable Adaptive Query Execution default
Key: SPARK-30188
URL: https://issues.apache.org/jira/browse/SPARK-30188
Project: Spark
Issue Type: New Feature
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Ke Jia commented on SPARK-29954:
[~hyukjin.kwon] Add the Jira description. Thanks.
> collect the
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Ke Jia updated SPARK-29954:
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Description: We need the row count info to more accurately estimate the
data skew situation when too many
Ke Jia created SPARK-29954:
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Summary: collect the runtime statistics of row count in map stage
Key: SPARK-29954
URL: https://issues.apache.org/jira/browse/SPARK-29954
Project: Spark
Issue Type:
Ke Jia created SPARK-29893:
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Summary: Improve the local reader performance by changing the task
number from 1 to multi
Key: SPARK-29893
URL: https://issues.apache.org/jira/browse/SPARK-29893
Project: Spark
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Ke Jia updated SPARK-29792:
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Description: After merged
[SPARK-28583|https://issues.apache.org/jira/browse/SPARK-28583], the subqueries
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Ke Jia updated SPARK-29552:
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Description: AQE will optimize the logical plan once there is query stage
finished. So for inner join, when
Ke Jia created SPARK-29552:
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Summary: Fix the flaky test failed in AdaptiveQueryExecSuite #
multiple joins
Key: SPARK-29552
URL: https://issues.apache.org/jira/browse/SPARK-29552
Project: Spark
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Ke Jia commented on SPARK-29544:
[~wenchen] The attachment is the design doc of skew join optimization.
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Ke Jia updated SPARK-29544:
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Attachment: Skewed Join Optimization Design Doc.docx
> Optimize skewed join at runtime with new Adaptive
Ke Jia created SPARK-29544:
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Summary: Optimize skewed join at runtime with new Adaptive
Execution
Key: SPARK-29544
URL: https://issues.apache.org/jira/browse/SPARK-29544
Project: Spark
Issue Type:
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Ke Jia updated SPARK-28576:
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Description: After enable AE(SPARK-23128), we found the dead lock issue in
Q6 1TB TPC-DS. The root cause is
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Ke Jia updated SPARK-28576:
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Description: After enable
AE([lSPARK-23128|https://issues.apache.org/jira/browse/SPARK-23128]), we found
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Ke Jia updated SPARK-28576:
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Attachment: q6.sql
physical plan.txt
jstack.log
> Fix the dead lock issue
Ke Jia created SPARK-28576:
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Summary: Fix the dead lock issue when enable new adaptive
execution
Key: SPARK-28576
URL: https://issues.apache.org/jira/browse/SPARK-28576
Project: Spark
Issue Type:
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https://issues.apache.org/jira/browse/SPARK-28560?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Ke Jia updated SPARK-28560:
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Description: Implement a rule in the new adaptive execution framework
introduced in SPARK-23128. This rule
Ke Jia created SPARK-28560:
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Summary: Optimize shuffle reader to local shuffle reader when smj
converted to bhj in adaptive execution
Key: SPARK-28560
URL: https://issues.apache.org/jira/browse/SPARK-28560
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Ke Jia updated SPARK-28046:
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Attachment: image-2019-06-14-10-34-53-379.png
> OOM caused by building hash table when the compressed ratio
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Ke Jia updated SPARK-28046:
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Description:
Currently, spark will convert the sort merge join to broadcast hash join when
the small table
Ke Jia created SPARK-28046:
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Summary: OOM caused by building hash table when the compressed
ratio of small table is normal
Key: SPARK-28046
URL: https://issues.apache.org/jira/browse/SPARK-28046
Project:
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https://issues.apache.org/jira/browse/SPARK-26639?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=16744791#comment-16744791
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Ke Jia commented on SPARK-26639:
[~mgaido] Yes, the current master also have above phenomenon.
> The
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Ke Jia commented on SPARK-26639:
[~hyukjin.kwon] Thanks for your interesting.
As discussion in
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Ke Jia commented on SPARK-26639:
[@davies|https://github.com/davies]
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Ke Jia updated SPARK-26639:
---
Description:
The subquery reuse feature has done in
[https://github.com/apache/spark/pull/14548]
In my
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Ke Jia updated SPARK-26639:
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Description:
The subquery reuse feature has done in
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Ke Jia updated SPARK-26639:
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Description:
The subquery reuse feature has done in
Ke Jia created SPARK-26639:
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Summary: The reuse subquery function maybe does not work in SPARK
SQL
Key: SPARK-26639
URL: https://issues.apache.org/jira/browse/SPARK-26639
Project: Spark
Issue
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https://issues.apache.org/jira/browse/SPARK-16958?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=16743720#comment-16743720
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Ke Jia edited comment on SPARK-16958 at 1/16/19 7:39 AM:
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[~davies] hi, I left
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Ke Jia commented on SPARK-16958:
[~davies] hi, I left some comments in the
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Ke Jia updated SPARK-26316:
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Description: The code of
Ke Jia created SPARK-26316:
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Summary: Because of the perf degradation in TPC-DS, we currently
partial revert SPARK-21052：Add hash map metrics to join,
Key: SPARK-26316
URL:
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https://issues.apache.org/jira/browse/SPARK-26155?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=16713847#comment-16713847
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Ke Jia commented on SPARK-26155:
Upload the result of all queries in tpcds in 1TB data scale.
> Spark
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Ke Jia updated SPARK-26155:
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Attachment: tpcds.result.xlsx
> Spark SQL performance degradation after apply SPARK-21052 with Q19 of
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Ke Jia commented on SPARK-26155:
[~cloud_fan] [~viirya] Spark2.3 with the optimized patch can have the
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Ke Jia commented on SPARK-26155:
[~cloud_fan] sorry for the delay. The revert PR is
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Ke Jia commented on SPARK-26155:
[~viirya] [~adrian-wang]
Here is the result in spark2.1, spark2.3
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Ke Jia commented on SPARK-26155:
[~viirya] Thanks for your reply.
> "Q19 analysis in Spark2.3 without
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Ke Jia updated SPARK-26155:
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Attachment: (was: Q19 analysis in Spark2.3 without L486 & 487.pdf)
> Spark SQL performance degradation
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Ke Jia updated SPARK-26155:
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Attachment: Q19 analysis in Spark2.3 without L486&487.pdf
> Spark SQL performance degradation after apply
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Ke Jia updated SPARK-26155:
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Attachment: q19.sql
Q19 analysis in Spark2.3 without L486 & 487.pdf
Q19
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Ke Jia edited comment on SPARK-26155 at 11/23/18 7:58 AM:
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*Cluster info:*
|
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Ke Jia commented on SPARK-26155:
*Cluster info:*
| |*Master Node*|*Worker Nodes* |
|*Node*|1x |7x|
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Ke Jia updated SPARK-26155:
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Summary: Spark SQL performance degradation after apply SPARK-21052 with
Q19 of TPC-DS in 3TB scale (was:
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Ke Jia updated SPARK-26155:
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Description: In our test environment, we found a serious performance
degradation issue in Spark2.3 when
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https://issues.apache.org/jira/browse/SPARK-26155?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Ke Jia updated SPARK-26155:
---
Description: In our test environment, we found a serious performance
degradation issue in Spark2.3 when
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https://issues.apache.org/jira/browse/SPARK-26155?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Ke Jia updated SPARK-26155:
---
Description: In our test environment, we found a serious performance
degradation issue in Spark2.3 when
Ke Jia created SPARK-26155:
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Summary: Spark SQL performance degradation after apply
SPARK-21052 with Q19 of TPC-DS in 2.6TB scale
Key: SPARK-26155
URL: https://issues.apache.org/jira/browse/SPARK-26155
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https://issues.apache.org/jira/browse/SPARK-8321?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Ke Jia updated SPARK-8321:
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Attachment: SparkSQLauthorizationDesignDocument.pdf
> Authorization Support(on all operations not only DDL) in
[
https://issues.apache.org/jira/browse/SPARK-8321?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Ke Jia updated SPARK-8321:
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Attachment: SparkSQLauthorizationDesignDocument.pdf
> Authorization Support(on all operations not only DDL) in
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