Has anyone encountered this “port out of range” error when launching PySpark jobs on YARN? It is sporadic (e.g. 2/3 jobs get this error).
LOG: 15/06/19 11:49:44 INFO scheduler.TaskSetManager: Lost task 0.3 in stage 39.0 (TID 211) on executor xxx.xxx.xxx.com <http://xxx.xxx.xxx.com/>: java.lang.IllegalArgumentException (port out of range:1315905645) [duplicate 7] Traceback (most recent call last): File "<stdin>", line 1, in <module> 15/06/19 11:49:44 INFO cluster.YarnScheduler: Removed TaskSet 39.0, whose tasks have all completed, from pool File "/home/john/spark-1.4.0/python/pyspark/rdd.py", line 745, in collect port = self.ctx._jvm.PythonRDD.collectAndServe(self._jrdd.rdd()) File "/home/john/spark-1.4.0/python/lib/py4j-0.8.2.1-src.zip/py4j/java_gateway.py", line 538, in __call__ File "/home/john/spark-1.4.0/python/lib/py4j-0.8.2.1-src.zip/py4j/protocol.py", line 300, in get_return_value py4j.protocol.Py4JJavaError15/06/19 11:49:44 INFO storage.BlockManagerInfo: Removed broadcast_38_piece0 on 17.134.160.35:47455 in memory (size: 2.2 KB, free: 265.4 MB) : An error occurred while calling z:org.apache.spark.api.python.PythonRDD.collectAndServe. : org.apache.spark.SparkException: Job aborted due to stage failure: Task 1 in stage 39.0 failed 4 times, most recent failure: Lost task 1.3 in stage 39.0 (TID 210, xxx.xxx.xxx.com <http://xxx.xxx.xxx.com/>): java.lang.IllegalArgumentException: port out of range:1315905645 at java.net.InetSocketAddress.checkPort(InetSocketAddress.java:143) at java.net.InetSocketAddress.<init>(InetSocketAddress.java:185) at java.net.Socket.<init>(Socket.java:241) at org.apache.spark.api.python.PythonWorkerFactory.createSocket$1(PythonWorkerFactory.scala:75) at org.apache.spark.api.python.PythonWorkerFactory.liftedTree1$1(PythonWorkerFactory.scala:90) at org.apache.spark.api.python.PythonWorkerFactory.createThroughDaemon(PythonWorkerFactory.scala:89) at org.apache.spark.api.python.PythonWorkerFactory.create(PythonWorkerFactory.scala:62) at org.apache.spark.SparkEnv.createPythonWorker(SparkEnv.scala:130) at org.apache.spark.api.python.PythonRDD.compute(PythonRDD.scala:73) at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:277) at org.apache.spark.rdd.RDD.iterator(RDD.scala:244) at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:63) at org.apache.spark.scheduler.Task.run(Task.scala:70) at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:213) at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145) at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615) at java.lang.Thread.run(Thread.java:745) Driver stacktrace: at org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$failJobAndIndependentStages(DAGScheduler.scala:1266) at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1257) at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1256) at scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59) at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:47) at org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:1256) at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:730) at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:730) at scala.Option.foreach(Option.scala:236) at org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:730) at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1450) at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1411) at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:48) * Spark 1.4.0 build: build/mvn -Pyarn -Phive -Phadoop-2.3 -Dhadoop.version=2.3.0-cdh5.1.4 -DskipTests clean package LAUNCH CMD: export HADOOP_CONF_DIR=/path/to/conf export PYSPARK_PYTHON=/path/to/python-2.7.2/bin/python ~/spark-1.4.0/bin/pyspark \ --conf spark.yarn.jar=/home/john/spark-1.4.0/assembly/target/scala-2.10/spark-assembly-1.4.0-hadoop2.3.0-cdh5.1.4.jar \ --master yarn-client \ --num-executors 3 \ --executor-cores 18 \ --executor-memory 48g TEST JOB IN REPL: words = [‘hi’, ‘there’, ‘yo’, ‘baby’] wordsRdd = sc.parallelize(words) words.map(lambda x: (x,1)).collect()
