Get SparkUncaughtExceptionHandler when run spark-perf

Question

We have setup distributed spark cluster(version 1.5.0) and try to run spark-perf. But we got this error and have no idea how to fix it.

15/10/05 20:14:37 ERROR SparkUncaughtExceptionHandler: Uncaught exception in thread Thread[appclient-registration-retry-thread,5,main]
java.util.concurrent.RejectedExecutionException: Task java.util.concurrent.FutureTask@43ff6bf rejected from java.util.concurrent.ThreadPoolExecutor@36077c7[Running, pool size = 1, active threads = 1, queued tasks = 0, completed tasks = 0]
        at java.util.concurrent.ThreadPoolExecutor$AbortPolicy.rejectedExecution(ThreadPoolExecutor.java:2048)
        at java.util.concurrent.ThreadPoolExecutor.reject(ThreadPoolExecutor.java:821)
        at java.util.concurrent.ThreadPoolExecutor.execute(ThreadPoolExecutor.java:1372)
        at java.util.concurrent.AbstractExecutorService.submit(AbstractExecutorService.java:110)
        at org.apache.spark.deploy.client.AppClient$ClientEndpoint$$anonfun$tryRegisterAllMasters$1.apply(AppClient.scala:96)
        at org.apache.spark.deploy.client.AppClient$ClientEndpoint$$anonfun$tryRegisterAllMasters$1.apply(AppClient.scala:95)
        at scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:244)
        at scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:244)
        at scala.collection.IndexedSeqOptimized$class.foreach(IndexedSeqOptimized.scala:33)
        at scala.collection.mutable.ArrayOps$ofRef.foreach(ArrayOps.scala:108)
        at scala.collection.TraversableLike$class.map(TraversableLike.scala:244)
        at scala.collection.mutable.ArrayOps$ofRef.map(ArrayOps.scala:108)
        at org.apache.spark.deploy.client.AppClient$ClientEndpoint.tryRegisterAllMasters(AppClient.scala:95)
        at org.apache.spark.deploy.client.AppClient$ClientEndpoint.org$apache$spark$deploy$client$AppClient$ClientEndpoint$$registerWithMaster(AppClient.scala:121)
        at org.apache.spark.deploy.client.AppClient$ClientEndpoint$$anon$2$$anonfun$run$1.apply$mcV$sp(AppClient.scala:132)
        at org.apache.spark.util.Utils$.tryOrExit(Utils.scala:1119)
        at org.apache.spark.deploy.client.AppClient$ClientEndpoint$$anon$2.run(AppClient.scala:124)
        at java.util.concurrent.Executors$RunnableAdapter.call(Executors.java:471)
        at java.util.concurrent.FutureTask.runAndReset(FutureTask.java:304)
        at java.util.concurrent.ScheduledThreadPoolExecutor$ScheduledFutureTask.access$301(ScheduledThreadPoolExecutor.java:178)
        at java.util.concurrent.ScheduledThreadPoolExecutor$ScheduledFutureTask.run(ScheduledThreadPoolExecutor.java:293)
        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)
15/10/05 20:14:37 INFO DiskBlockManager: Shutdown hook called
15/10/05 20:14:37 INFO ShutdownHookManager: Shutdown hook called
15/10/05 20:14:37 INFO ShutdownHookManager: Deleting directory /tmp/spark-c5a4a63b-3dc5-4c52-bd2b-e6df22a0c19f

Answer 1

Please check the variable SPARK_CLUSTER_URL in config/config.py.

SPARK_CLUSTER_URL = "spark://Master_Ip:7077"

PS: The Master_Ip is Master's ip address, not hostname.

Answer 2

You have not entered your Spark master URL correctly. It could be because upper case error. Please use this command to ensure the path to hibench.spark.masterin the file conf/99-user_defined_properties.conf is correct. You should be able to connect to the Spark-shell be running the following command.

MASTER=<YOUR-SPARK-MASTER-URL-HERE> bin/spark-shell

In the Spark's standalone mode this url should look something like:

spark://<master-machine-IP>:7077

Generally it is better to use the IP address of Master node instead of the alphabetic hostname that is provided by spark master for e.g spark://Macs-MacBook-Pro.local:7077