Details
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Bug
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Status: Resolved
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Major
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Resolution: Fixed
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2.4.0, 3.0.0
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None
Description
Recently, a few spark users in the organization have reported that their jobs were getting stuck. On further analysis, it was found out that there exist two independent deadlocks and either of them occur under different circumstances. The screenshots for these two deadlocks are attached here.
We were able to reproduce the deadlocks with the following piece of code:
import org.apache.hadoop.conf.Configuration import org.apache.hadoop.fs.{FileSystem, Path} import org.apache.spark._ import org.apache.spark.TaskContext // Simple example of Word Count in Scala object ScalaWordCount { def main(args: Array[String]) { if (args.length < 2) { System.err.println("Usage: ScalaWordCount <inputFilesURI> <outputFilesUri>") System.exit(1) } val conf = new SparkConf().setAppName("Scala Word Count") val sc = new SparkContext(conf) // get the input file uri val inputFilesUri = args(0) // get the output file uri val outputFilesUri = args(1) while (true) { val textFile = sc.textFile(inputFilesUri) val counts = textFile.flatMap(line => line.split(" ")) .map(word => {if (TaskContext.get.partitionId == 5 && TaskContext.get.attemptNumber == 0) throw new Exception("Fail for blacklisting") else (word, 1)}) .reduceByKey(_ + _) counts.saveAsTextFile(outputFilesUri) val conf: Configuration = new Configuration() val path: Path = new Path(outputFilesUri) val hdfs: FileSystem = FileSystem.get(conf) hdfs.delete(path, true) } sc.stop() } }
Additionally, to ensure that the deadlock surfaces up soon enough, I also added a small delay in the Spark code here:
executorIdToFailureList.remove(exec)
updateNextExpiryTime()
Thread.sleep(2000)
killBlacklistedExecutor(exec)
Also make sure that the following configs are set when launching the above spark job:
spark.blacklist.enabled=true
spark.blacklist.killBlacklistedExecutors=true
spark.blacklist.application.maxFailedTasksPerExecutor=1
