[jira] [Created] (SPARK-27112) Spark Scheduler encounters two independent Deadlocks when trying to kill executors either due to dynamic allocation or blacklisting

["Parth Gandhi (JIRA)" <ji...@apache.org>]

Parth Gandhi created SPARK-27112:
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             Summary: Spark Scheduler encounters two independent Deadlocks when trying to kill executors either due to dynamic allocation or blacklisting 
                 Key: SPARK-27112
                 URL: https://issues.apache.org/jira/browse/SPARK-27112
             Project: Spark
          Issue Type: Bug
          Components: Scheduler, Spark Core
    Affects Versions: 2.4.0, 3.0.0
            Reporter: Parth Gandhi


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:

 
{code:java}
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()
}
}
{code}
 

Additionally, to ensure that the deadlock surfaces up soon enough, I also added a small delay in the Spark code here:

[https://github.com/apache/spark/blob/master/core/src/main/scala/org/apache/spark/scheduler/BlacklistTracker.scala#L256]

 
{code:java}
executorIdToFailureList.remove(exec)
updateNextExpiryTime()
Thread.sleep(2000)
killBlacklistedExecutor(exec)
{code}



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