spark1.5.2 spark-shell报错：java.util.concurrent.RejectedExecutionException

用spark-shell启动spark时，报以下错误：

17/11/17 14:04:36 WARN metrics.MetricsSystem: Using default name DAGScheduler for source because spark.app.id is not set.17/11/17 14:04:36 INFO client.AppClient$ClientEndpoint: Connecting to master spark://Master:7077...17/11/17 14:04:56 ERROR util.SparkUncaughtExceptionHandler: Uncaught exception in thread Thread[appclient-registration-retry-thread,5,main]java.util.concurrent.RejectedExecutionException: Task java.util.concurrent.FutureTask@4b63252d rejected from java.util.concurrent.ThreadPoolExecutor@2b2a787c[Running, pool size = 1, active threads = 0, queued tasks = 0, completed tasks = 1]    at java.util.concurrent.ThreadPoolExecutor$AbortPolicy.rejectedExecution(ThreadPoolExecutor.java:2063)    at java.util.concurrent.ThreadPoolExecutor.reject(ThreadPoolExecutor.java:830)    at java.util.concurrent.ThreadPoolExecutor.execute(ThreadPoolExecutor.java:1379)    at java.util.concurrent.AbstractExecutorService.submit(AbstractExecutorService.java:112)    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: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:1149)    at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)    at java.lang.Thread.run(Thread.java:748)

查了一些资料，这是spark配置错误，在spark-env.sh中，

export MASTER=spark://Master:${SPARK_MASTER_PORT}

改成

export MASTER=spark://10.0.0.130:${SPARK_MASTER_PORT}

重启spark，就ok了。特此记一下。