spark-issues mailing list archives

Site index · List index
Message view « Date » · « Thread »
Top « Date » · « Thread »
From "Andrew Or (JIRA)" <j...@apache.org>
Subject [jira] [Updated] (SPARK-4951) A busy executor may be killed when dynamicAllocation is enabled
Date Wed, 07 Jan 2015 22:58:36 GMT

     [ https://issues.apache.org/jira/browse/SPARK-4951?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]

Andrew Or updated SPARK-4951:
-----------------------------
    Assignee: Shixiong Zhu

> A busy executor may be killed when dynamicAllocation is enabled
> ---------------------------------------------------------------
>
>                 Key: SPARK-4951
>                 URL: https://issues.apache.org/jira/browse/SPARK-4951
>             Project: Spark
>          Issue Type: Bug
>          Components: Spark Core
>    Affects Versions: 1.2.0
>            Reporter: Shixiong Zhu
>            Assignee: Shixiong Zhu
>
> If a task runs more than `spark.dynamicAllocation.executorIdleTimeout`, the executor
which runs this task will be killed.
> The following steps (yarn-client mode) can reproduce this bug:
> 1. Start `spark-shell` using
> {code}
> ./bin/spark-shell --conf "spark.shuffle.service.enabled=true" \
>     --conf "spark.dynamicAllocation.minExecutors=1" \
>     --conf "spark.dynamicAllocation.maxExecutors=4" \
>     --conf "spark.dynamicAllocation.enabled=true" \
>     --conf "spark.dynamicAllocation.executorIdleTimeout=30" \
>     --master yarn-client \
>     --driver-memory 512m \
>     --executor-memory 512m \
>     --executor-cores 1
> {code}
> 2. Wait more than 30 seconds until there is only one executor.
> 3. Run the following code (a task needs at least 50 seconds to finish)
> {code}
> val r = sc.parallelize(1 to 1000, 20).map{t => Thread.sleep(1000); t}.groupBy(_ %
2).collect()
> {code}
> 4. Executors will be killed and allocated all the time, which makes the Job fail.



--
This message was sent by Atlassian JIRA
(v6.3.4#6332)

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


Mime
View raw message