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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} -- This message was sent by Atlassian JIRA (v6.3.4#6332) --------------------------------------------------------------------- To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org