title: Spark - Executor heartbeat timed out after X ms
body: <p>My program read data from files in a directory, the size of these files is 5 GB. I apply many function to these data. I am running spark as standalone (local), on a virtual machine having 32 GB RAM.</p>
  
  <p>The used command :</p>
  
  <pre><code>bin/spark-submit --class ripeatlasanalysis.AnalyseTraceroute     --master local --driver-memory 30G  SparkExample-lowprints-0.0.5-SNAPSHOT-jar-with-dependencies.jar  1517961600  1518393600 3600 
  </code></pre>
  
  <p>the <code>1517961600  1518393600 3600</code> are the parameters of jar file.</p>
  
  <p>Sometimes the program run without errors, sometimes not, and the gotten error :</p>
  
  <pre><code>Exception in thread "main" org.apache.spark.SparkException: Job aborted due 
   to stage failure: Task 0 in stage 2.0 failed 1 times, most recent   failure: Lost task 
  0.0 in stage 2.0 (TID 119, localhost, executor driver):  
  ExecutorLostFailure (executor driver exited caused by one of the running   tasks) 
  Reason: Executor heartbeat timed out after 128839 ms
   Driver stacktrace:
     at org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGSchedule  r$$failJobAndIndependentStages(DAGScheduler.scala:1887)
     at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1875)
  </code></pre>
  
  <p>The question already asked <a href="https://stackoverflow.com/questions/39317625/spark-executor-heartbeat-timed-out">here</a> without responses. </p>