SPARK java.net.NoRouteToHostException:主机没有路由

时间:2019-04-03 20:44:04

标签: java scala apache-spark

美好的一天,

我正在尝试运行以下链接中提供的用于火花的scala示例:

https://www.tutorialkart.com/apache-spark/scala-spark-shell-example/

我使用以下命令启动spark-shell(我已经添加了端口号,因为端口4040-4045已被使用)

spark-shell --master local[4] --conf spark.ui.port=4046

一旦出现火花,我会尝试输入提供的三行,但在第二行中,它会显示“主机没有路由”投诉:

scala> ^C^C[twagenhals@login-1 downloads]$ spark-shell --master local --conf spark.ui.port=4047
Setting default log level to "WARN".
To adjust logging level use sc.setLogLevel(newLevel). For SparkR, use setLogLevel(newLevel).
Spark context Web UI available at http://login-1:4047
Spark context available as 'sc' (master = local, app id = local-1554323767110).
Spark session available as 'spark'.
Welcome to
      ____              __
     / __/__  ___ _____/ /__
    _\ \/ _ \/ _ `/ __/  '_/
   /___/ .__/\_,_/_/ /_/\_\   version 2.4.0
      /_/

Using Scala version 2.11.12 (OpenJDK 64-Bit Server VM, Java 1.8.0_171)
Type in expressions to have them evaluated.
Type :help for more information.

scala> var map = sc.textFile("wordcount_input.txt").flatMap(line => line.split(" ")).map(word => (word,1));
map: org.apache.spark.rdd.RDD[(String, Int)] = MapPartitionsRDD[3] at map at <console>:24

scala> var counts = map.reduceByKey(_ + _);
java.net.NoRouteToHostException: No Route to Host from  login-1/10.2.0.2 to localhost:9000 failed on socket timeout exception: java.net.NoRouteToHostException: No route to host; For more details see:  http://wiki.apache.org/hadoop/NoRouteToHost
  at sun.reflect.NativeConstructorAccessorImpl.newInstance0(Native Method)
  at sun.reflect.NativeConstructorAccessorImpl.newInstance(NativeConstructorAccessorImpl.java:62)
  at sun.reflect.DelegatingConstructorAccessorImpl.newInstance(DelegatingConstructorAccessorImpl.java:45)
  at java.lang.reflect.Constructor.newInstance(Constructor.java:423)
  at org.apache.hadoop.net.NetUtils.wrapWithMessage(NetUtils.java:792)
  at org.apache.hadoop.net.NetUtils.wrapException(NetUtils.java:758)
  at org.apache.hadoop.ipc.Client.call(Client.java:1479)
  at org.apache.hadoop.ipc.Client.call(Client.java:1412)
  at org.apache.hadoop.ipc.ProtobufRpcEngine$Invoker.invoke(ProtobufRpcEngine.java:229)
  at com.sun.proxy.$Proxy23.getFileInfo(Unknown Source)
  at org.apache.hadoop.hdfs.protocolPB.ClientNamenodeProtocolTranslatorPB.getFileInfo(ClientNamenodeProtocolTranslatorPB.java:771)
  at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
  at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
  at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
  at java.lang.reflect.Method.invoke(Method.java:498)
  at org.apache.hadoop.io.retry.RetryInvocationHandler.invokeMethod(RetryInvocationHandler.java:191)
  at org.apache.hadoop.io.retry.RetryInvocationHandler.invoke(RetryInvocationHandler.java:102)
  at com.sun.proxy.$Proxy24.getFileInfo(Unknown Source)
  at org.apache.hadoop.hdfs.DFSClient.getFileInfo(DFSClient.java:2108)
  at org.apache.hadoop.hdfs.DistributedFileSystem$22.doCall(DistributedFileSystem.java:1305)
  at org.apache.hadoop.hdfs.DistributedFileSystem$22.doCall(DistributedFileSystem.java:1301)
  at org.apache.hadoop.fs.FileSystemLinkResolver.resolve(FileSystemLinkResolver.java:81)
  at org.apache.hadoop.hdfs.DistributedFileSystem.getFileStatus(DistributedFileSystem.java:1317)
  at org.apache.hadoop.fs.Globber.getFileStatus(Globber.java:57)
  at org.apache.hadoop.fs.Globber.glob(Globber.java:252)
  at org.apache.hadoop.fs.FileSystem.globStatus(FileSystem.java:1676)
  at org.apache.hadoop.mapred.FileInputFormat.singleThreadedListStatus(FileInputFormat.java:259)
  at org.apache.hadoop.mapred.FileInputFormat.listStatus(FileInputFormat.java:229)
  at org.apache.hadoop.mapred.FileInputFormat.getSplits(FileInputFormat.java:315)
  at org.apache.spark.rdd.HadoopRDD.getPartitions(HadoopRDD.scala:204)
  at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:253)
  at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:251)
  at scala.Option.getOrElse(Option.scala:121)
  at org.apache.spark.rdd.RDD.partitions(RDD.scala:251)
  at org.apache.spark.rdd.MapPartitionsRDD.getPartitions(MapPartitionsRDD.scala:49)
  at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:253)
  at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:251)
  at scala.Option.getOrElse(Option.scala:121)
  at org.apache.spark.rdd.RDD.partitions(RDD.scala:251)
  at org.apache.spark.rdd.MapPartitionsRDD.getPartitions(MapPartitionsRDD.scala:49)
  at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:253)
  at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:251)
  at scala.Option.getOrElse(Option.scala:121)
  at org.apache.spark.rdd.RDD.partitions(RDD.scala:251)
  at org.apache.spark.rdd.MapPartitionsRDD.getPartitions(MapPartitionsRDD.scala:49)
  at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:253)
  at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:251)
  at scala.Option.getOrElse(Option.scala:121)
  at org.apache.spark.rdd.RDD.partitions(RDD.scala:251)
  at org.apache.spark.Partitioner$$anonfun$4.apply(Partitioner.scala:78)
  at org.apache.spark.Partitioner$$anonfun$4.apply(Partitioner.scala:78)
  at scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:234)
  at scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:234)
  at scala.collection.immutable.List.foreach(List.scala:392)
  at scala.collection.TraversableLike$class.map(TraversableLike.scala:234)
  at scala.collection.immutable.List.map(List.scala:296)
  at org.apache.spark.Partitioner$.defaultPartitioner(Partitioner.scala:78)
  at org.apache.spark.rdd.PairRDDFunctions$$anonfun$reduceByKey$3.apply(PairRDDFunctions.scala:326)
  at org.apache.spark.rdd.PairRDDFunctions$$anonfun$reduceByKey$3.apply(PairRDDFunctions.scala:326)
  at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
  at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:112)
  at org.apache.spark.rdd.RDD.withScope(RDD.scala:363)
  at org.apache.spark.rdd.PairRDDFunctions.reduceByKey(PairRDDFunctions.scala:325)
  ... 49 elided
Caused by: java.net.NoRouteToHostException: No route to host
  at sun.nio.ch.SocketChannelImpl.checkConnect(Native Method)
  at sun.nio.ch.SocketChannelImpl.finishConnect(SocketChannelImpl.java:717)
  at org.apache.hadoop.net.SocketIOWithTimeout.connect(SocketIOWithTimeout.java:206)
  at org.apache.hadoop.net.NetUtils.connect(NetUtils.java:531)
  at org.apache.hadoop.net.NetUtils.connect(NetUtils.java:495)
  at org.apache.hadoop.ipc.Client$Connection.setupConnection(Client.java:614)
  at org.apache.hadoop.ipc.Client$Connection.setupIOstreams(Client.java:712)
  at org.apache.hadoop.ipc.Client$Connection.access$2900(Client.java:375)
  at org.apache.hadoop.ipc.Client.getConnection(Client.java:1528)
  at org.apache.hadoop.ipc.Client.call(Client.java:1451)
  ... 105 more

我不确定为什么会发生此问题,并且在互联网上搜索并没有给出明确的原因。我尝试不包括--master,但默认值仍为local [*],因此结果相似。我不知道我可以在这里键入哪些其他选项来尝试使其正常工作。是否需要添加某种属性文件,以便在启动Spark之前了解某种关系?我之前在hadoop中已经看到过此问题,它与配置一些.xml文件有关,因此这是我想到的唯一另一件事,但是我不知道每个程序和配置文件之间的关系。谁能指出我正确的方向?

编辑:问题的一部分似乎在hadoop的core-site.xml文件中。当我将其设置为以下配置时,它将失败:

[twagenhals@login-1 scripts]$ cat $HADOOP_HOME/etc/hadoop/core-site.xml
<?xml version="1.0" encoding="UTF-8"?>
<?xml-stylesheet type="text/xsl" href="configuration.xsl"?>
<!--
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License. See accompanying LICENSE file.
-->
<!-- Put site-specific property overrides in this file. -->
<configuration>
<property>
<name>hadoop.tmp.dir</name>
<value>/state/partition1/hadoop-twagenhals</value>
</property>
<property>
<name>fs.default.name</name>
<value>hdfs://localhost:9000</value>
</property>
</configuration>

删除所有属性可以使Spark运行,尽管我真的不知道为什么。

<?xml version="1.0" encoding="UTF-8"?>
<?xml-stylesheet type="text/xsl" href="configuration.xsl"?>
<!--
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License. See accompanying LICENSE file.
-->
<!-- Put site-specific property overrides in this file. -->
<configuration>
</configuration>

0 个答案:

没有答案
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