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Shay Elbaz updated SPARK-41449:
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Description:
Since the total/max number of executor is constant throughout the application -
in dyn
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Shay Elbaz updated SPARK-41449:
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Description:
Since the total/max number of executor is constant throughout the application -
in dyn
Shay Elbaz created SPARK-41449:
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Summary: Stage level scheduling, allow to change number of
executors
Key: SPARK-41449
URL: https://issues.apache.org/jira/browse/SPARK-41449
Project: Spark
Issu
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https://issues.apache.org/jira/browse/SPARK-32578?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17195948#comment-17195948
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Shay Elbaz commented on SPARK-32578:
It turned out the problem was in my benchmark,
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Shay Elbaz updated SPARK-32578:
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Description:
The core sendMessage method is incorrect:
{code:java}
def sendMessage(edge: EdgeTriplet
Shay Elbaz created SPARK-32578:
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Summary: PageRank not sending the correct values in Pergel
sendMessage
Key: SPARK-32578
URL: https://issues.apache.org/jira/browse/SPARK-32578
Project: Spark
Is
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https://issues.apache.org/jira/browse/SPARK-27318?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17162641#comment-17162641
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Shay Elbaz edited comment on SPARK-27318 at 7/22/20, 11:54 AM:
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Shay Elbaz edited comment on SPARK-27318 at 7/22/20, 10:14 AM:
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Shay Elbaz edited comment on SPARK-27318 at 7/22/20, 9:37 AM:
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Shay Elbaz commented on SPARK-27318:
Was able to reproduce on 2.4.3.
Executed vi
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Shay Elbaz commented on SPARK-30399:
Hi [~hyukjin.kwon], thanks for replying.
Perh
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Shay Elbaz updated SPARK-30399:
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Description:
When using Spark Bucketed table, Spark would use as many partitions as the
number of b
Shay Elbaz created SPARK-30399:
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Summary: Bucketing does not compatible with partitioning in
practice
Key: SPARK-30399
URL: https://issues.apache.org/jira/browse/SPARK-30399
Project: Spark
Issu
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https://issues.apache.org/jira/browse/SPARK-30089?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Shay Elbaz updated SPARK-30089:
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Description:
Please consider the following data, where *event_id* has 5 non unique values,
and *tim
Shay Elbaz created SPARK-30089:
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Summary: count over Window function with orderBy gives wrong
results
Key: SPARK-30089
URL: https://issues.apache.org/jira/browse/SPARK-30089
Project: Spark
Issu
Shay Elbaz created SPARK-26438:
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Summary: Driver waits to spark.sql.broadcastTimeout before
throwing OutOfMemoryError - is this by design?
Key: SPARK-26438
URL: https://issues.apache.org/jira/browse/SPARK-26438
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https://issues.apache.org/jira/browse/SPARK-19256?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16700067#comment-16700067
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Shay Elbaz commented on SPARK-19256:
[~chengsu] this is great! If there is anything
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Shay Elbaz commented on SPARK-19256:
+1
[~tejasp] is this still under progress?
>
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Shay Elbaz commented on SPARK-24904:
[~mgaido] Technically you *can* that, you just
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Shay Elbaz updated SPARK-24904:
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Issue Type: Improvement (was: Question)
> Join with broadcasted dataframe causes shuffle of redunda
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Shay Elbaz commented on SPARK-24904:
[~mgaido] indeed this assumption is not always
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Shay Elbaz updated SPARK-24904:
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Description:
When joining a "large" dataframe with broadcasted small one, and join-type is
on the s
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https://issues.apache.org/jira/browse/SPARK-24904?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Shay Elbaz updated SPARK-24904:
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Description:
When joining a "large" dataframe with broadcasted small one, and join-type is
on the s
Shay Elbaz created SPARK-24904:
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Summary: Join with broadcasted dataframe causes shuffle of
redundant data
Key: SPARK-24904
URL: https://issues.apache.org/jira/browse/SPARK-24904
Project: Spark
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Shay Elbaz commented on SPARK-5377:
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+1
This seems like a very useful improvement and w
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