scala – Spark中的java.util.concurrent.RejectedExecutionExce

唯一的区别是：

local[*]

VS

spark://<host>.local:7077

为主人

我可以在上面的地址对主人运行spark pi并使用spark gui：所以它正在工作.

这是(普通)spark init代码：

val sconf = new SparkConf().setMaster(master).setAppName("EpisCatalog")
 val sc = new SparkContext(sconf)

这是运行程序的堆栈跟踪：

15/12/03 03:39:04.746 main WARN NativeCodeLoader: Unable to load native-hadoop library for your platform... using builtin-java classes where applicable
15/12/03 03:39:07.706 main WARN MetricsSystem: Using default name DAGScheduler for source because spark.app.id is not set.
15/12/03 03:39:27.739 appclient-registration-retry-thread ERROR SparkUncaughtExceptionHandler: Uncaught exception in thread Thread[appclient-registration-retry-thread,5,main]
java.util.concurrent.RejectedExecutionException: Task java.util.concurrent.FutureTask@b649f0b rejected from java.util.concurrent.ThreadPoolExecutor@5ef7a52b[Running,pool size = 1,active threads = 1,queued tasks = 0,completed tasks = 0]
    at java.util.concurrent.ThreadPoolExecutor$AbortPolicy.rejectedExecution(ThreadPoolExecutor.java:2047)
    at java.util.concurrent.ThreadPoolExecutor.reject(ThreadPoolExecutor.java:823)
    at java.util.concurrent.ThreadPoolExecutor.execute(ThreadPoolExecutor.java:1369)
    at java.util.concurrent.AbstractExecutorService.submit(AbstractExecutorService.java:112)
    at org.apache.spark.deploy.client.AppClient$ClientEndpoint$$anonfun$tryRegisterAllMasters$1.apply(AppClient.scala:103)
    at org.apache.spark.deploy.client.AppClient$ClientEndpoint$$anonfun$tryRegisterAllMasters$1.apply(AppClient.scala:102)
    at scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:245)
    at scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:245)
    at scala.collection.IndexedSeqOptimized$class.foreach(IndexedSeqOptimized.scala:33)
    at scala.collection.mutable.ArrayOps$ofRef.foreach(ArrayOps.scala:186)
    at scala.collection.TraversableLike$class.map(TraversableLike.scala:245)
    at scala.collection.mutable.ArrayOps$ofRef.map(ArrayOps.scala:186)
    at org.apache.spark.deploy.client.AppClient$ClientEndpoint.tryRegisterAllMasters(AppClient.scala:102)
    at org.apache.spark.deploy.client.AppClient$ClientEndpoint.org$apache$spark$deploy$client$AppClient$ClientEndpoint$$registerWithMaster(AppClient.scala:128)
    at org.apache.spark.deploy.client.AppClient$ClientEndpoint$$anon$2$$anonfun$run$1.apply$mcV$sp(AppClient.scala:139)
    at org.apache.spark.util.Utils$.tryOrExit(Utils.scala:1130)
    at org.apache.spark.deploy.client.AppClient$ClientEndpoint$$anon$2.run(AppClient.scala:131)
    at java.util.concurrent.Executors$RunnableAdapter.call(Executors.java:511)
    at java.util.concurrent.FutureTask.runAndReset(FutureTask.java:308)
    at java.util.concurrent.ScheduledThreadPoolExecutor$ScheduledFutureTask.access$301(ScheduledThreadPoolExecutor.java:180)
    at java.util.concurrent.ScheduledThreadPoolExecutor$ScheduledFutureTask.run(ScheduledThreadPoolExecutor.java:294)
    at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
    at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
    at java.lang.Thread.run(Thread.java:745)

我正在运行spark 1.6.0-SNAPSHOT.它已经“安装”到本地maven repo,我已经验证客户端正在使用最新的本地maven repo版本.