1：练习spark的时候，操作大概如我读取hdfs上面的文件，然后spark懒加载以后，我读取详细信息出现如下所示的错误，错误虽然不大，我感觉有必要记录一下，因为错误的起因是对命令的不熟悉造成的，错误如下所示：

 scala> text.collect

 java.net.ConnectException: Call From slaver1/192.168.19.128 to slaver1: failed on connection exception: java.net.ConnectException: Connection refused; For more details see:  http://wiki.apache.org/hadoop/ConnectionRefused

     at sun.reflect.NativeConstructorAccessorImpl.newInstance0(Native Method)

     at sun.reflect.NativeConstructorAccessorImpl.newInstance(NativeConstructorAccessorImpl.java:)

     at sun.reflect.DelegatingConstructorAccessorImpl.newInstance(DelegatingConstructorAccessorImpl.java:)

     at java.lang.reflect.Constructor.newInstance(Constructor.java:)

     at org.apache.hadoop.net.NetUtils.wrapWithMessage(NetUtils.java:)

     at org.apache.hadoop.net.NetUtils.wrapException(NetUtils.java:)

     at org.apache.hadoop.ipc.Client.call(Client.java:)

     at org.apache.hadoop.ipc.Client.call(Client.java:)

     at org.apache.hadoop.ipc.ProtobufRpcEngine$Invoker.invoke(ProtobufRpcEngine.java:)

     at com.sun.proxy.$Proxy36.getFileInfo(Unknown Source)

     at org.apache.hadoop.hdfs.protocolPB.ClientNamenodeProtocolTranslatorPB.getFileInfo(ClientNamenodeProtocolTranslatorPB.java:)

     at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)

     at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:)

     at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:)

     at java.lang.reflect.Method.invoke(Method.java:)

     at org.apache.hadoop.io.retry.RetryInvocationHandler.invokeMethod(RetryInvocationHandler.java:)

     at org.apache.hadoop.io.retry.RetryInvocationHandler.invoke(RetryInvocationHandler.java:)

     at com.sun.proxy.$Proxy37.getFileInfo(Unknown Source)

     at org.apache.hadoop.hdfs.DFSClient.getFileInfo(DFSClient.java:)

     at org.apache.hadoop.hdfs.DistributedFileSystem$.doCall(DistributedFileSystem.java:)

     at org.apache.hadoop.hdfs.DistributedFileSystem$.doCall(DistributedFileSystem.java:)

     at org.apache.hadoop.fs.FileSystemLinkResolver.resolve(FileSystemLinkResolver.java:)

     at org.apache.hadoop.hdfs.DistributedFileSystem.getFileStatus(DistributedFileSystem.java:)

     at org.apache.hadoop.fs.Globber.getFileStatus(Globber.java:)

     at org.apache.hadoop.fs.Globber.glob(Globber.java:)

     at org.apache.hadoop.fs.FileSystem.globStatus(FileSystem.java:)

     at org.apache.hadoop.mapred.FileInputFormat.singleThreadedListStatus(FileInputFormat.java:)

     at org.apache.hadoop.mapred.FileInputFormat.listStatus(FileInputFormat.java:)

     at org.apache.hadoop.mapred.FileInputFormat.getSplits(FileInputFormat.java:)

     at org.apache.spark.rdd.HadoopRDD.getPartitions(HadoopRDD.scala:)

     at org.apache.spark.rdd.RDD$$anonfun$partitions$.apply(RDD.scala:)

     at org.apache.spark.rdd.RDD$$anonfun$partitions$.apply(RDD.scala:)

     at scala.Option.getOrElse(Option.scala:)

     at org.apache.spark.rdd.RDD.partitions(RDD.scala:)

     at org.apache.spark.rdd.MapPartitionsRDD.getPartitions(MapPartitionsRDD.scala:)

     at org.apache.spark.rdd.RDD$$anonfun$partitions$.apply(RDD.scala:)

     at org.apache.spark.rdd.RDD$$anonfun$partitions$.apply(RDD.scala:)

     at scala.Option.getOrElse(Option.scala:)

     at org.apache.spark.rdd.RDD.partitions(RDD.scala:)

     at org.apache.spark.SparkContext.runJob(SparkContext.scala:)

     at org.apache.spark.rdd.RDD$$anonfun$collect$.apply(RDD.scala:)

     at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:)

     at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:)

     at org.apache.spark.rdd.RDD.withScope(RDD.scala:)

     at org.apache.spark.rdd.RDD.collect(RDD.scala:)

     at $iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC.<init>(<console>:)

     at $iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC.<init>(<console>:)

     at $iwC$$iwC$$iwC$$iwC$$iwC$$iwC.<init>(<console>:)

     at $iwC$$iwC$$iwC$$iwC$$iwC.<init>(<console>:)

     at $iwC$$iwC$$iwC$$iwC.<init>(<console>:)

     at $iwC$$iwC$$iwC.<init>(<console>:)

     at $iwC$$iwC.<init>(<console>:)

     at $iwC.<init>(<console>:)

     at <init>(<console>:)

     at .<init>(<console>:)

     at .<clinit>(<console>)

     at .<init>(<console>:)

     at .<clinit>(<console>)

     at $print(<console>)

     at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)

     at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:)

     at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:)

     at java.lang.reflect.Method.invoke(Method.java:)

     at org.apache.spark.repl.SparkIMain$ReadEvalPrint.call(SparkIMain.scala:)

     at org.apache.spark.repl.SparkIMain$Request.loadAndRun(SparkIMain.scala:)

     at org.apache.spark.repl.SparkIMain.loadAndRunReq$(SparkIMain.scala:)

     at org.apache.spark.repl.SparkIMain.interpret(SparkIMain.scala:)

     at org.apache.spark.repl.SparkIMain.interpret(SparkIMain.scala:)

     at org.apache.spark.repl.SparkILoop.reallyInterpret$(SparkILoop.scala:)

     at org.apache.spark.repl.SparkILoop.interpretStartingWith(SparkILoop.scala:)

     at org.apache.spark.repl.SparkILoop.command(SparkILoop.scala:)

     at org.apache.spark.repl.SparkILoop.processLine$(SparkILoop.scala:)

     at org.apache.spark.repl.SparkILoop.innerLoop$(SparkILoop.scala:)

     at org.apache.spark.repl.SparkILoop.org$apache$spark$repl$SparkILoop$$loop(SparkILoop.scala:)

     at org.apache.spark.repl.SparkILoop$$anonfun$org$apache$spark$repl$SparkILoop$$process$.apply$mcZ$sp(SparkILoop.scala:)

     at org.apache.spark.repl.SparkILoop$$anonfun$org$apache$spark$repl$SparkILoop$$process$.apply(SparkILoop.scala:)

     at org.apache.spark.repl.SparkILoop$$anonfun$org$apache$spark$repl$SparkILoop$$process$.apply(SparkILoop.scala:)

     at scala.tools.nsc.util.ScalaClassLoader$.savingContextLoader(ScalaClassLoader.scala:)

     at org.apache.spark.repl.SparkILoop.org$apache$spark$repl$SparkILoop$$process(SparkILoop.scala:)

     at org.apache.spark.repl.SparkILoop.process(SparkILoop.scala:)

     at org.apache.spark.repl.Main$.main(Main.scala:)

     at org.apache.spark.repl.Main.main(Main.scala)

     at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)

     at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:)

     at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:)

     at java.lang.reflect.Method.invoke(Method.java:)

     at org.apache.spark.deploy.SparkSubmit$.org$apache$spark$deploy$SparkSubmit$$runMain(SparkSubmit.scala:)

     at org.apache.spark.deploy.SparkSubmit$.doRunMain$(SparkSubmit.scala:)

     at org.apache.spark.deploy.SparkSubmit$.submit(SparkSubmit.scala:)

     at org.apache.spark.deploy.SparkSubmit$.main(SparkSubmit.scala:)

     at org.apache.spark.deploy.SparkSubmit.main(SparkSubmit.scala)

 Caused by: java.net.ConnectException: Connection refused

     at sun.nio.ch.SocketChannelImpl.checkConnect(Native Method)

     at sun.nio.ch.SocketChannelImpl.finishConnect(SocketChannelImpl.java:)

     at org.apache.hadoop.net.SocketIOWithTimeout.connect(SocketIOWithTimeout.java:)

     at org.apache.hadoop.net.NetUtils.connect(NetUtils.java:)

     at org.apache.hadoop.net.NetUtils.connect(NetUtils.java:)

     at org.apache.hadoop.ipc.Client$Connection.setupConnection(Client.java:)

     at org.apache.hadoop.ipc.Client$Connection.setupIOstreams(Client.java:)

     at org.apache.hadoop.ipc.Client$Connection.access$(Client.java:)

     at org.apache.hadoop.ipc.Client.getConnection(Client.java:)

     at org.apache.hadoop.ipc.Client.call(Client.java:)

     ...  more

2：错误原因如下所示：

我使用了如下所示命令来读取hdfs上面的文件，scala> var text = sc.textFile("hdfs://slaver1:/input.txt");，然后使用text.collect命令来查看详细信息，就是查看详细信息的时候报的上面的错误，错误原因是因为我读取hdfs文件的时候少了端口号，造成的错误；

修改为如下所示即可：

scala> var text = sc.textFile("hdfs://slaver1:9000/input.txt");

scala> text.collect

java.net.ConnectException: Call From slaver1/192.168.19.128 to slaver1:8020 failed on connection exception: java.net.ConnectException: Connection refused; For more details see: http://wiki.apache.org的更多相关文章

  1. exception: java.net.ConnectException: Connection refused; For more details see: http://wiki.apache.org/hadoop/ConnectionRefused

    1.虽然,不是大错,还说要贴一下,由于我运行run-example streaming.NetworkWordCount localhost 9999的测试案例,出现的错误,第一感觉就是Spark没有 ...

  2. Caused by: java.net.ConnectException: Call From master/192.168.199.130 to master:9000 failed on connection exception: java.net.ConnectException: Connection refused; For more details see: http://wiki.

    1:安装好hive,准备启动的时候出现下面的错误(由于hive是基于Hadoop的,所以必须先将你的集群启动起来,我就是没有启动集群,直接启动hive导致的错误): [root@master bin] ...

  3. ls: Call From hdoop2/192.168.18.87 to hdoop2:8020 failed on connection exception: java.net.ConnectException: 拒绝连接; For more details see

    场景:  预发环境中,同事已经搭建了一套hadoop集群,由于版本与所需不符,所以需要替换版本 问题描述: 在配置文件都准确的情况下,启动hadoop,出现以下报错: 启动之前初始化:   初始化目录 ...

  4. Error: java.net.ConnectException: Call From tuge1/192.168.40.100 to tuge2:8032 failed on connection exception

    先看解决方案,再看唠嗑,唠嗑可以忽略. 解决方案: 使用start yarn.sh启动yarn就可以了. 唠嗑: 今天学习Spark基于Yarn部署.然后总以为Yarn是让Spark启动的,提交程序的 ...

  5. Call From master/192.168.128.135 to master:8485 failed on connection exception: java.net.ConnectException: Connection refused

    hadoop集群搭建了ha,初次启动正常,最近几天启动时偶尔发现,namenode1节点启动后一段时间(大约10几秒-半分钟左右),namenode1上namenode进程停掉,查看日志: -- :: ...

  6. Hadoop格式化 From hu-hadoop1/192.168.11.11 to hu-hadoop2:8485 failed on connection exception: java.net.

    192.168.11.12:8485: Call From hu-hadoop1/192.168.11.11 to hu-hadoop2:8485 failed on connection excep ...

  7. INFO org.apache.hadoop.ipc.RPC: Server at master/192.168.200.128:9000 not available yet, Zzzzz...

    hadoop 启动时namenode和datanode可以启动,使用jps命令也可以看到进程,但是在浏览器中输入master:50070却没有显示datanode 查看datanode的log日志: ...

  8. Bad connection to FS. command aborted. exception: Call to chaoren/192.168.80.100:9000 failed on connection exception: java.net.ConnectException: Connection refused

    Bad connection to FS. command aborted. exception: Call to chaoren/192.168.80.100:9000 failed on conn ...

  9. 格式化namenode时 报错 No Route to Host from node1/192.168.1.111 to node3:8485 failed on socket timeout exception: java.net.NoRouteToHostException: No route to host

    // :: FATAL namenode.NameNode: Failed to start namenode. org.apache.hadoop.hdfs.qjournal.client.Quor ...

随机推荐

  1. 【转】Python的神奇方法指南

    [转]Python的神奇方法指南 有关Python内编写类的各种技巧和方法(构建和初始化.重载操作符.类描述.属性访问控制.自定义序列.反射机制.可调用对象.上下文管理.构建描述符对象.Picklin ...

  2. python中// 和/有什么区别

    python中// 和/有什么区别 通常C/C++中,"/ " 算术运算符的计算结果是根据参与运算的两边的数据决定的,比如: 6 / 3 = 2 ; 6,3都是整数,那么结果也就是 ...

  3. 使用Crash工具分析 Linux dump文件【转】

    转自:https://blog.csdn.net/bytxl/article/details/45025183 前言 Linux 内核(以下简称内核)是一个不与特定进程相关的功能集合,内核的代码很难轻 ...

  4. Boost property_tree解析json

    使用Boost property_tree解析json 之前使用jsoncpp解析json,现在才知道boost就有解析的库,学习一下吧 property_tree可以解析xml,json,ini,i ...

  5. struts2框架之重复提交问题

    防止重复提交 1. 什么是重复提交 * 提交表单时,点击一次后,页面没有刷新时,马上又点击一次,就是重复提交 * 提交后,通过浏览器的回退,又回到了表单页面,再次提交 * 提交后,按F5刷新,也是重复 ...

  6. "贪吃蛇"-css3效果

    clip  :  http://www.w3school.com.cn/cssref/pr_pos_clip.asp 姜糖水  :  http://www.cnphp6.com/archives/60 ...

  7. elasticsearch自动按天创建索引脚本

    elasticsearch保存在一个索引中数据量太大无法查询,现在需要将索引按照天来建,查询的时候关联查询即可 有时候es集群创建了很多索引,删不掉,如果是测试环境或者初始化es集群(清空所有数据), ...

  8. windows 中java开发环境搭建

    安装jdk1.6 1.下载tomcat服务器 2. 解压缩tomcat  * 不要使用含有空格和中文目录 3.启动tomcat之前 配置 JAVA_HOME 环境变量 ------ 配置JDK安装路径 ...

  9. mariadb：分区自动创建与删除

    参考文章:https://blog.csdn.net/xlxxcc/article/details/52486426 1.以日自动创建与删除分区 调用示例:CALL proc_day_partitio ...

  10. centos7 部署rabbitmq

    1.安装 Erlang 就想我们编写Java引用程序需要安装 JDK一样,安装 RabbitMQ ,我们也需要安装 Erlang . ①.下载 erlang 安装包 将安装包下载到 /home/erl ...