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https://issues.apache.org/jira/browse/SPARK-5243?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14278502#comment-14278502
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Takumi Yoshida commented on SPARK-5243:
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Hi!
I found, Spark hangs with following situation. i guess there would be some
other condition.
> 1. the cluster has only one worker.
yes, running standalone.
> 2. driver memory + executor memory > worker memory
I use following settings, but it hang.
driver memory = 1g
executor memory = 1g
worker memory = 3g
> 3. deploy-mode = cluster
no, deploy-mode was "client" as default.
I use follwing code.
https://gist.github.com/yoshi0309/33bd912d91c0bb5cdf30
command.
./bin/spark-submit ./ldgourmetALS.py s3n://abc-takumiyoshida/datasets/
--driver-memory 1g
machine.
Amazon EC2 / m3.medium (3ECU and 3.75GB RAM)
> Spark will hang if (driver memory + executor memory) exceeds limit on a
> 1-worker cluster
> ----------------------------------------------------------------------------------------
>
> Key: SPARK-5243
> URL: https://issues.apache.org/jira/browse/SPARK-5243
> Project: Spark
> Issue Type: Improvement
> Components: Deploy
> Affects Versions: 1.2.0
> Environment: centos, others should be similar
> Reporter: yuhao yang
> Priority: Minor
>
> Spark will hang if calling spark-submit under the conditions:
> 1. the cluster has only one worker.
> 2. driver memory + executor memory > worker memory
> 3. deploy-mode = cluster
> This usually happens during development for beginners.
> There should be some exit mechanism or at least a warning message in the
> output of the spark-submit.
> I am preparing PR for the case. And I would like to know your opinions about
> if a fix is needed and better fix options.
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