spark-issues mailing list archives

Site index · List index
Message view « Date » · « Thread »
Top « Date » · « Thread »
From "Meenakshi sundaram sekar (JIRA)" <j...@apache.org>
Subject [jira] [Commented] (SPARK-5243) Spark will hang if (driver memory + executor memory) exceeds limit on a 1-worker cluster
Date Fri, 16 Mar 2018 19:48:00 GMT

    [ https://issues.apache.org/jira/browse/SPARK-5243?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16402398#comment-16402398
] 

Meenakshi sundaram sekar commented on SPARK-5243:
-------------------------------------------------

Hi - i faced this issue when i had one master and on worker. i had driver and executor memory
set to 8G . 

After reading this issue trail ,i increased my worker count to 2 instances  with 30g of memory
each. My jobs ran fine. Thanks 

> 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 would like to know your opinions about if a fix is needed (is this by design?) and
better fix options.



--
This message was sent by Atlassian JIRA
(v7.6.3#76005)

---------------------------------------------------------------------
To unsubscribe, e-mail: issues-unsubscribe@spark.apache.org
For additional commands, e-mail: issues-help@spark.apache.org


Mime
View raw message