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Posted to issues@spark.apache.org by "Apache Spark (JIRA)" <ji...@apache.org> on 2014/09/17 22:10:39 UTC
[jira] [Commented] (SPARK-3571) Spark standalone cluster mode
doesn't work.
[ https://issues.apache.org/jira/browse/SPARK-3571?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14137884#comment-14137884 ]
Apache Spark commented on SPARK-3571:
-------------------------------------
User 'sarutak' has created a pull request for this issue:
https://github.com/apache/spark/pull/2436
> Spark standalone cluster mode doesn't work.
> -------------------------------------------
>
> Key: SPARK-3571
> URL: https://issues.apache.org/jira/browse/SPARK-3571
> Project: Spark
> Issue Type: Bug
> Components: Spark Core
> Affects Versions: 1.2.0
> Reporter: Kousuke Saruta
> Priority: Blocker
>
> Recent changes of Master.scala causes Spark standalone cluster mode not working.
> I think, the loop in Master#schedule never assign worker for driver.
> {code}
> for (driver <- waitingDrivers.toList) { // iterate over a copy of waitingDrivers
> // We assign workers to each waiting driver in a round-robin fashion. For each driver, we
> // start from the last worker that was assigned a driver, and continue onwards until we have
> // explored all alive workers.
> curPos = (curPos + 1) % aliveWorkerNum
> val startPos = curPos
> var launched = false
> while (curPos != startPos && !launched) {
> val worker = shuffledAliveWorkers(curPos)
> if (worker.memoryFree >= driver.desc.mem && worker.coresFree >= driver.desc.cores) {
> launchDriver(worker, driver)
> waitingDrivers -= driver
> launched = true
> }
> curPos = (curPos + 1) % aliveWorkerNum
> }
> {code}
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