You are viewing a plain text version of this content. The canonical link for it is here.
Posted to issues@spark.apache.org by "zhoukang (JIRA)" <ji...@apache.org> on 2017/07/27 02:04:00 UTC
[jira] [Reopened] (SPARK-21539) Job should not be aborted when
dynamic allocation is enabled or spark.executor.instances larger then
current allocated number by yarn
[ https://issues.apache.org/jira/browse/SPARK-21539?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
zhoukang reopened SPARK-21539:
------------------------------
> Job should not be aborted when dynamic allocation is enabled or spark.executor.instances larger then current allocated number by yarn
> -------------------------------------------------------------------------------------------------------------------------------------
>
> Key: SPARK-21539
> URL: https://issues.apache.org/jira/browse/SPARK-21539
> Project: Spark
> Issue Type: Improvement
> Components: Spark Core
> Affects Versions: 1.6.1, 2.1.0
> Reporter: zhoukang
>
> For spark on yarn.
> Right now, when TaskSet can not run on any node or host.Which means blacklistedEverywhere is true in TaskSetManager#abortIfCompleteBlacklisted.
> However, if dynamic allocation is enabled, we should wait for yarn to allocate new nodemanager in order to execute job successfully.
> How to reproduce?
> 1、Set up a yarn cluster with 5 nodes.And assign a node1 with much larger cpu core and memory,which can let yarn launch container on this node even it is blacklisted by TaskScheduler.
> 2、modify BlockManager#registerWithExternalShuffleServer
> {code:java}
> logInfo("Registering executor with local external shuffle service.")
> val shuffleConfig = new ExecutorShuffleInfo(
> diskBlockManager.localDirs.map(_.toString),
> diskBlockManager.subDirsPerLocalDir,
> shuffleManager.getClass.getName)
> val MAX_ATTEMPTS = conf.get(config.SHUFFLE_REGISTRATION_MAX_ATTEMPTS)
> val SLEEP_TIME_SECS = 5
> for (i <- 1 to MAX_ATTEMPTS) {
> try {
> {color:red}if (shuffleId.host.equals("node1's address")) {
> throw new Exception
> }{color}
> // Synchronous and will throw an exception if we cannot connect.
> shuffleClient.asInstanceOf[ExternalShuffleClient].registerWithShuffleServer(
> shuffleServerId.host, shuffleServerId.port, shuffleServerId.executorId, shuffleConfig)
> return
> } catch {
> case e: Exception if i < MAX_ATTEMPTS =>
> logError(s"Failed to connect to external shuffle server, will retry ${MAX_ATTEMPTS - i}"
> + s" more times after waiting $SLEEP_TIME_SECS seconds...", e)
> Thread.sleep(SLEEP_TIME_SECS * 1000)
> case NonFatal(e) =>
> throw new SparkException("Unable to register with external shuffle server due to : " +
> e.getMessage, e)
> }
> }
> {code}
> add logic in red.
> 3、set shuffle service enable as true and open shuffle service for yarn.
> Then yarn will always launch executor on node1 but failed since shuffle service can not register success.
> Then job will be aborted.
--
This message was sent by Atlassian JIRA
(v6.4.14#64029)
---------------------------------------------------------------------
To unsubscribe, e-mail: issues-unsubscribe@spark.apache.org
For additional commands, e-mail: issues-help@spark.apache.org