[jira] [Resolved] (SPARK-3571) Spark standalone cluster mode doesn't work.

["Patrick Wendell (JIRA)" <ji...@apache.org>]

     [ https://issues.apache.org/jira/browse/SPARK-3571?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

Patrick Wendell resolved SPARK-3571.
------------------------------------
       Resolution: Fixed
    Fix Version/s: 1.2.0

Issue resolved by pull request 2436
[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
>             Fix For: 1.2.0
>
>
> 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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