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uncleGen updated SPARK-3373:
Target Version/s: 1.3.0, 1.2.1 (was: 1.1.1, 1.2.0)
Affects Version/s: (was: 1.0.2
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uncleGen updated SPARK-3376:
Priority: Major (was: Minor)
> Memory-based shuffle strategy to reduce overhead of disk
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uncleGen updated SPARK-3376:
Priority: Minor (was: Trivial)
> Memory-based shuffle strategy to reduce overhead of disk
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]
uncleGen commented on SPARK-3376:
-
[~rxin] Yeah, I agree with you. We can improve the
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uncleGen updated SPARK-3376:
Description:
I think a memory-based shuffle can reduce some overhead of disk I/O. I just
want to know is
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https://issues.apache.org/jira/browse/SPARK-3376?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
uncleGen updated SPARK-3376:
Description:
I think a memory-based shuffle can reduce some overhead of disk I/O. I just
want to know is
[
https://issues.apache.org/jira/browse/SPARK-3376?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
uncleGen updated SPARK-3376:
Description:
I think a memory-based shuffle can reduce some overhead of disk I/O. I just
want to know is
[
https://issues.apache.org/jira/browse/SPARK-3376?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
uncleGen updated SPARK-3376:
Description:
I think a memory-based shuffle can reduce some overhead of disk I/O. I just
want to know is
[
https://issues.apache.org/jira/browse/SPARK-3376?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
uncleGen updated SPARK-3376:
Labels: performance (was: )
> Memory-based shuffle strategy to reduce overhead of disk
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https://issues.apache.org/jira/browse/SPARK-3376?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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uncleGen updated SPARK-3376:
Target Version/s: 1.3.0
> Memory-based shuffle strategy to reduce overhead of disk
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uncleGen updated SPARK-3376:
Affects Version/s: 1.1.0
> Memory-based shuffle strategy to reduce overhead of disk
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uncleGen updated SPARK-3376:
Component/s: Shuffle
> Memory-based shuffle strategy to reduce overhead of disk
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uncleGen updated SPARK-3376:
Issue Type: New Feature (was: Planned Work)
> Memory-based shuffle strategy to reduce overhead of disk
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uncleGen updated SPARK-3376:
Description:
I think a memory-based shuffle can reduce some overhead of disk I/O. I just
want to know is
[
https://issues.apache.org/jira/browse/SPARK-3376?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
uncleGen updated SPARK-3376:
Description:
I think a memory-based shuffle can reduce some overhead of disk I/O. I just
want to know is
[
https://issues.apache.org/jira/browse/SPARK-3376?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
uncleGen updated SPARK-3376:
Description:
I think a memory-based shuffle can reduce some overhead of disk I/O. I just
want to know is
[
https://issues.apache.org/jira/browse/SPARK-3376?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
uncleGen updated SPARK-3376:
Description:
I think a memory-based shuffle can reduce some overhead of disk I/O. I just
want to know is
[
https://issues.apache.org/jira/browse/SPARK-3376?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
uncleGen updated SPARK-3376:
Description:
I think a memory-based shuffle can reduce some overhead of disk I/O. I just
want to know is
[
https://issues.apache.org/jira/browse/SPARK-3376?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
uncleGen updated SPARK-3376:
Description:
I think a memory-based shuffle can reduce some overhead of disk I/O. I just
want to know is
[
https://issues.apache.org/jira/browse/SPARK-3376?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
uncleGen updated SPARK-3376:
Description:
I think a memory-based shuffle can reduce some overhead of disk I/O. I just
want to know is
[
https://issues.apache.org/jira/browse/SPARK-3376?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
uncleGen updated SPARK-3376:
Description:
I think a memory-based shuffle can reduce some overhead of disk I/O. I just
want to know is
[
https://issues.apache.org/jira/browse/SPARK-3376?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
uncleGen updated SPARK-3376:
Description:
I think a memory-based shuffle can reduce some overhead of disk I/O. I just
want to know is
[
https://issues.apache.org/jira/browse/SPARK-3376?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
uncleGen updated SPARK-3376:
Description:
I think a memory-based shuffle can reduce some overhead of disk I/O. I just
want to know is
[
https://issues.apache.org/jira/browse/SPARK-3376?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
uncleGen updated SPARK-3376:
Description:
I think a memory-based shuffle can reduce some overhead of disk I/O. I just
want to know is
[
https://issues.apache.org/jira/browse/SPARK-3376?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
uncleGen updated SPARK-3376:
Description:
I think a memory-based shuffle can reduce some overhead of disk I/O. I just
want to know is
[
https://issues.apache.org/jira/browse/SPARK-3376?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
uncleGen updated SPARK-3376:
Description:
I think a memory-based shuffle can reduce some overhead of disk I/O. I just
want to know is
[
https://issues.apache.org/jira/browse/SPARK-3376?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
uncleGen updated SPARK-3376:
Description:
I think a memory-based shuffle can reduce some overhead of disk I/O. I just
want to know is
Github user uncleGen commented on the pull request:
https://github.com/apache/spark/pull/3366#issuecomment-63831692
@davies Could you help reviewing this patch? Thank you!
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Github user uncleGen commented on the pull request:
https://github.com/apache/spark/pull/2249#issuecomment-63654065
@ankurdave Hi, can you review it again. Thank you!
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uncleGen updated SPARK-3373:
Target Version/s: 1.1.1, 1.2.0 (was: 1.1.0, 1.0.3)
> Filtering operations should optionally rebu
Github user uncleGen closed the pull request at:
https://github.com/apache/spark/pull/2574
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Github user uncleGen commented on the pull request:
https://github.com/apache/spark/pull/2574#issuecomment-63651117
@JoshRosen [[SPARK-4168][WebUI]
](https://github.com/apache/spark/commit/97a466eca0a629f17e9662ca2b59eeca99142c54)
The patch solved the same problem, and I will close
GitHub user uncleGen opened a pull request:
https://github.com/apache/spark/pull/3366
[SPARK-4488][PySpark] Add control over map-side aggregation
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Github user uncleGen closed the pull request at:
https://github.com/apache/spark/pull/3365
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GitHub user uncleGen reopened a pull request:
https://github.com/apache/spark/pull/3365
[SPARK-4488][PySpark] Add control over map-side aggregation
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Github user uncleGen closed the pull request at:
https://github.com/apache/spark/pull/3365
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GitHub user uncleGen opened a pull request:
https://github.com/apache/spark/pull/3365
[SPARK-4488][PySpark] Add control over map-side aggregation
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uncleGen created SPARK-4488:
---
Summary: Add control over map-side aggregation
Key: SPARK-4488
URL: https://issues.apache.org/jira/browse/SPARK-4488
Project: Spark
Issue Type: Improvement
Github user uncleGen commented on the pull request:
https://github.com/apache/spark/pull/2679#issuecomment-59037906
@ankurdave I see. And I think it is worthy to provide a memory-based
shuffle manager in some cases, like sufficient memory resources, stringent
performance requirement
Github user uncleGen commented on the pull request:
https://github.com/apache/spark/pull/2679#issuecomment-58885039
@ankurdave I have some doubts, but not about this patch. In [GraphX OSDI
paper](http://ankurdave.com/dl/graphx-osdi14.pdf) , I find that you have
implemented a "m
Github user uncleGen commented on the pull request:
https://github.com/apache/spark/pull/2574#issuecomment-58735669
@JoshRosen Sorry for my misunderstanding, I will correct it as soon as
possible.
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Github user uncleGen commented on a diff in the pull request:
https://github.com/apache/spark/pull/2574#discussion_r18622733
--- Diff:
core/src/main/scala/org/apache/spark/ui/jobs/JobProgressPage.scala ---
@@ -70,11 +72,11 @@ private[ui] class JobProgressPage(parent
Github user uncleGen commented on a diff in the pull request:
https://github.com/apache/spark/pull/2574#discussion_r18561760
--- Diff:
core/src/main/scala/org/apache/spark/ui/jobs/JobProgressPage.scala ---
@@ -70,11 +72,11 @@ private[ui] class JobProgressPage(parent
GitHub user uncleGen opened a pull request:
https://github.com/apache/spark/pull/2574
[SPARK-3719][CORE]:"complete/failed stages" is better to show the total ...
...number of stages
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uncleGen created SPARK-3719:
---
Summary: Spark UI: "complete/failed stages" is better to show the
total number of stages
Key: SPARK-3719
URL: https://issues.apache.org/jira/browse/SPARK-3719
Proj
Github user uncleGen commented on the pull request:
https://github.com/apache/spark/pull/2562#issuecomment-57087576
@jerryshao Thanks for your comments! I want to abstract an independent
DStream to achieve the aim. I feel it is weird to update a rdd by passing a
closure. Maybe, this
Github user uncleGen closed the pull request at:
https://github.com/apache/spark/pull/2562
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Github user uncleGen commented on the pull request:
https://github.com/apache/spark/pull/2562#issuecomment-57083416
Test failure appears to be unrelated to my patch.
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GitHub user uncleGen opened a pull request:
https://github.com/apache/spark/pull/2562
[SPARK-3712][STREAMING]: add a new UpdateDStream to update a rdd dynamically
Maybe, we can achieve the aim by using "forEachRdd" function. But it is
weird in this way, because I need
uncleGen created SPARK-3712:
---
Summary: add a new UpdateDStream to update a rdd dynamically
Key: SPARK-3712
URL: https://issues.apache.org/jira/browse/SPARK-3712
Project: Spark
Issue Type
Github user uncleGen commented on a diff in the pull request:
https://github.com/apache/spark/pull/710#discussion_r17951094
--- Diff:
core/src/test/scala/org/apache/spark/deploy/SparkSubmitSuite.scala ---
@@ -192,15 +236,17 @@ class SparkSubmitSuite extends FunSuite with
Github user uncleGen closed the pull request at:
https://github.com/apache/spark/pull/2488
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Github user uncleGen commented on the pull request:
https://github.com/apache/spark/pull/2488#issuecomment-56505578
@pwendell ah, make sense, I will close this PR. Thank you!
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GitHub user uncleGen opened a pull request:
https://github.com/apache/spark/pull/2488
[SPARK-3636][CORE]:It is not friendly to interrupt a Job when user passe...
... different storageLevels to a RDD
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$ git pull
uncleGen created SPARK-3636:
---
Summary: It is not friendly to interrupt a Job when user passes
different storageLevels to a RDD
Key: SPARK-3636
URL: https://issues.apache.org/jira/browse/SPARK-3636
Project
Github user uncleGen commented on a diff in the pull request:
https://github.com/apache/spark/pull/2249#discussion_r17095835
--- Diff: graphx/src/main/scala/org/apache/spark/graphx/Graph.scala ---
@@ -262,13 +262,61 @@ abstract class Graph[VD: ClassTag, ED: ClassTag]
protected
Github user uncleGen commented on the pull request:
https://github.com/apache/spark/pull/2249#issuecomment-54399143
@ankurdave Thanks for you comments, I will update it as soon as possible.
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uncleGen updated SPARK-3376:
Description: I think a memory-based shuffle can reduce some overhead of
disk I/O. I just want to know is
[
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]
uncleGen updated SPARK-3376:
Description: I think a memory-based shuffle can reduce some overhead of
disk I/O. I just want to know is
uncleGen created SPARK-3376:
---
Summary: Memory-based shuffle strategy to reduce overhead of disk
I/O
Key: SPARK-3376
URL: https://issues.apache.org/jira/browse/SPARK-3376
Project: Spark
Issue Type
uncleGen created SPARK-3373:
---
Summary: trim some useless informations of VertexRDD in some cases
Key: SPARK-3373
URL: https://issues.apache.org/jira/browse/SPARK-3373
Project: Spark
Issue Type
GitHub user uncleGen opened a pull request:
https://github.com/apache/spark/pull/2249
[GraphX]: trim some useless informations of VertexRDD in some cases
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Github user uncleGen closed the pull request at:
https://github.com/apache/spark/pull/1429
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Github user uncleGen commented on the pull request:
https://github.com/apache/spark/pull/1696#issuecomment-54102947
@pwendell OKï¼
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Github user uncleGen commented on the pull request:
https://github.com/apache/spark/pull/1356#issuecomment-53977557
okay!
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Github user uncleGen commented on the pull request:
https://github.com/apache/spark/pull/2131#issuecomment-53549872
@andrewor14 sorry for my poor coding. Unit test passed locally, test it
again pls.
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Github user uncleGen commented on a diff in the pull request:
https://github.com/apache/spark/pull/2131#discussion_r16762096
--- Diff: core/src/test/scala/org/apache/spark/CacheManagerSuite.scala ---
@@ -87,4 +99,12 @@ class CacheManagerSuite extends FunSuite with
BeforeAndAfter
Github user uncleGen commented on a diff in the pull request:
https://github.com/apache/spark/pull/2131#discussion_r16761636
--- Diff: core/src/main/scala/org/apache/spark/CacheManager.scala ---
@@ -68,7 +68,9 @@ private[spark] class CacheManager(blockManager:
BlockManager
Github user uncleGen commented on the pull request:
https://github.com/apache/spark/pull/2131#issuecomment-53521662
Hi @andrewor14, test it again please
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Github user uncleGen closed the pull request at:
https://github.com/apache/spark/pull/2076
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Github user uncleGen commented on the pull request:
https://github.com/apache/spark/pull/2076#issuecomment-53383270
@andrewor14 @pwendell @srowen
As my branch is not up to date, I decide to close this and submit a new PR.
Please Review It : https://github.com/apache/spark
GitHub user uncleGen opened a pull request:
https://github.com/apache/spark/pull/2131
[SPARK-3170][CORE][BUG]:RDD info loss in "StorageTab" and "ExecutorTab"
compeleted stage only need to remove its own partitions that are no longer
cached. However, "Stora
Github user uncleGen commented on the pull request:
https://github.com/apache/spark/pull/2076#issuecomment-53144395
@pwendell Okay! I will add them as soon as possible and pay more attention.
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Github user uncleGen commented on the pull request:
https://github.com/apache/spark/pull/2076#issuecomment-52908740
@srowen yes! Not only in "StorageTab", "ExectutorTab" may also lose some
rdd-infos which have been overwritten by following rdd in a same task.
[
https://issues.apache.org/jira/browse/SPARK-3170?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
uncleGen updated SPARK-3170:
Description: current compeleted stage only need to remove its own
partitions that are no longer cached
GitHub user uncleGen opened a pull request:
https://github.com/apache/spark/pull/2076
[SPARK-3170][CORE]: Bug Fix in Storage UI
current compeleted stage only need to remove its own partitions that are no
longer cached. Currently, "Storage" in Spark UI may lost some rdds
uncleGen created SPARK-3170:
---
Summary: Bug Fix in Storage UI
Key: SPARK-3170
URL: https://issues.apache.org/jira/browse/SPARK-3170
Project: Spark
Issue Type: Bug
Components: Spark Core
uncleGen created SPARK-3123:
---
Summary: override the "setName" function to set EdgeRDD's name
manually just as VertexRDD does.
Key: SPARK-3123
URL: https://issues.apache.org/jira/browse/SPARK-3123
GitHub user uncleGen opened a pull request:
https://github.com/apache/spark/pull/2033
[GraphX]: override the "setName" function to set EdgeRDD's name manually
just as VertexRDD does.
You can merge this pull request into a Git repository by running:
$
Github user uncleGen commented on the pull request:
https://github.com/apache/spark/pull/1696#issuecomment-50958278
@rxin Thanks for your attention, I have updated my jira.
https://issues.apache.org/jira/browse/SPARK-2773
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uncleGen updated SPARK-2773:
Description: Right now, Spark uses the total usage of "shuffle" memory of
each thread to predi
[
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uncleGen updated SPARK-2773:
Description: Right now, Spark uses the total usage of "shuffle" memory of
each thread to predi
[
https://issues.apache.org/jira/browse/SPARK-2773?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
uncleGen updated SPARK-2773:
Description: Right now, Spark uses the total usage of "shuffle" memory of
each thread to predi
[
https://issues.apache.org/jira/browse/SPARK-2773?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14081161#comment-14081161
]
uncleGen commented on SPARK-2773:
-
here is my improvement: https://github.com/ap
uncleGen created SPARK-2773:
---
Summary: Shuffle:use growth rate to predict if need to spill
Key: SPARK-2773
URL: https://issues.apache.org/jira/browse/SPARK-2773
Project: Spark
Issue Type
GitHub user uncleGen opened a pull request:
https://github.com/apache/spark/pull/1696
Spark Shuffleï¼use growth rate to predict if need to spill
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$ git pull https://github.com/uncleGen/spark master
Github user uncleGen commented on the pull request:
https://github.com/apache/spark/pull/1429#issuecomment-49751553
@tgravescs ok, and any suggestions?
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]
uncleGen commented on SPARK-2506:
-
Here is a simple PR fix this problem: h
[
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uncleGen updated SPARK-2506:
Description:
when i call sc.stop manually, some strange ERRORs will appear:
1. in driver log:
INFO
GitHub user uncleGen opened a pull request:
https://github.com/apache/spark/pull/1429
Bug Fix: In yarn-cluster mode, ApplicationMaster does not clean up corre...
...ctly at the end of the job if users call sc.stop manually. There are two
minor bugs:
1. At the end of a job
uncleGen created SPARK-2506:
---
Summary: In yarn-cluster mode, ApplicationMaster does not clean up
correctly at the end of the job if users call sc.stop manually
Key: SPARK-2506
URL: https://issues.apache.org/jira/browse
Github user uncleGen commented on the pull request:
https://github.com/apache/spark/pull/1356#issuecomment-48691872
@pwendell yeah, it is not a handsome way to resolve the bug. My fix is a
compromise way. Actualy, is will not cause frequent put/get opertions in
blockManager when
Github user uncleGen commented on the pull request:
https://github.com/apache/spark/pull/1356#issuecomment-48691344
@pwendell yeah, this is not a handsome way to resolve the bug. My fix is a
compromised way. Actually, there are no frequent get/put opertions in
blockManager when
GitHub user uncleGen opened a pull request:
https://github.com/apache/spark/pull/1356
Bug Fix: LiveListenerBus Queue Overflow
As we know, the size of "eventQueue" is fixed. When event comes faster
than consume speed of listener, overflow events will be thrown away with
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