每次出现此错误时，我都试图运行单词计数火花应用程序。请帮助，以下是wordcount.scala文件，在sbt包之后，我运行了spark-submit命令
package main
import org.apache.spark.SparkContext
import org.apache.spark.SparkContext._
import org.apache.spark.SparkConf
object WordCount {
def main(args: Array[String]) {
val conf = new SparkConf().setAppName("Word Count")
val sc = new SparkContext(conf)
val textfile = sc.textFile("file:///usr/local/spark/README.md")
val tokenizeddata = textfile.flatMap(line => line.split(" "))
val countprep = tokenizeddata.map(word => (word,1))
val counts = countprep.reduceByKey((accumvalue,newvalue)=>(accumvalue+newvalue))
val sortedcount = counts.sortBy(kvpair=>kvpair._2,false)
sortedcount.saveAsTextFile("file:///usr/local/wordcount")
}
}
我执行下一个命令。
bin/spark-submit --class "main.WordCount" --master "local[*]" "/home/hadoop/SparkApps/target/scala-2.10/word-count_2.10-1.0.jar"
Spark程序集已使用Hive构建，包括上的Datanucleus jarclasspath Java HotSpot（TM）64位服务器VM警告：
忽略选项MaxPermSize=128m；8.0中删除了支持15/11/28 07:38:51错误执行程序：1.0阶段任务1.0中出现异常
（TID 1）java.net.NoRouteToHostException：没有到主机的路由位于java.net.PlainSocketImpl.socketConnect（本机方法）位于java.net.AbstractPlainSocketImpl.doConnect（AbstractPlainSOCetImpl.java:350）位于java.net.AbstractPlainSocketImpl.connectToAddress（AbstractPlainSOCetImpl.java:206）位于java.net.AbstractPlainSocketImpl.connect（AbstractPlainSOCetImpl.java:188）位于java.net.SocksSocketImpl.connect（SocksSocketImpl.java:392）位于java.net.Socket.connect（Socket.java:589）位于sun.net.NetworkClient.doConnect（NetworkClient.java:175）网址：sun.net。www.http.HttpClient.openServer（HttpClient.java:432）网址：sun.net。www.http.HttpClient.openServer（HttpClient.java：527）网址：sun.net。www.http.HttpClient.（HttpClient.java:211）网址：sun.net。www.http.HttpClient.New（HttpClient.java：308）网址：sun.net。www.http.HttpClient.New（HttpClient.java:326）网址：sun.net。www.protocol.HttpURLConnection.getNewHttpClient（HttpURLConnection.java:1169）网址：sun.net。www.protocol.HttpURLConnection.plainConnect0（HttpURLConnection.java:1105）网址：sun.net。www.protocol.HttpURLConnection.plainConnect（HttpURLConnection.java:999）网址：sun.net。www.protocol.HttpURLConnection.connect（HttpURLConnection.java:933）网址：org.apache.spark.util.Utils$.fetchFile（Utils.scala:375）在org.apache.spark.executor.executor$$anonfun$org.apache$spark$executor$executor$$updateDependencies$6.apply（executor.scala:325）在org.apache.spark.executor.executor$$anonfun$org.apache$spark$executor$executor$$updateDependencies$6.apply（executor.scala:323）在scala.collection.TraversableLike$WithFilter$$anonfun$foreach$1.apply（TraversableLike.scala:772）位于scala.collection.mutable.HashMap$$anonfun$foreach$1.apply（HashMap.scala:98）位于scala.collection.mutable.HashMap$$anonfun$foreach$1.apply（HashMap.scala:98）位于scala.collection.mutable.HashTable$class.foreachEntry（HashTable.scala:226）位于scala.collection.mutable.HashMap.foreachEntry（HashMap.scala:39）位于scala.collection.mutable.HashMap.foreach（HashMap.scala:98）位于scala.collection.TraversableLike$WithFilter.foreach（TraversableLike.scala:771）在org.apache.spark.executor.executor.org.apache$spark$executor$executor$$updateDependencies（executor.scala:323）网址：org.apache.spark.executor.executor$TaskRunner.run（executor.scala:158）位于java.util.concurrent.ThreadPoolExecutiator.runWorker（ThreadPoolExecutiator.java:1142）位于java.util.concurrent.ThreadPoolExecutor$Worker.run（ThreadPoolExecutor.java:617）在java.lang.Thread.run（Thread.java:745）
也许您应该添加.setMaster（"local"）