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【Hadoop踩雷】无法上传文件?有办法!

正文之前

一鼓作气!肝死它!!!!

【Hadoop踩雷】无法上传文件?有办法!

正文

前面都已经配置好了。我就准备试试伪分布式了!!结果??!啊哈?!?!

localhost:hadoop zhangzhaobo$ cd 3.1.0/ localhost:3.1.0 zhangzhaobo$ hdfs dfs -put /Users/zhangzhaobo/program/python/KnowledgeGame.py logs 2018-06-03 14:38:52,230 WARN util.NativeCodeLoader: Unable to load native-hadoop library for your platform... using builtin-java classes where applicable 2018-06-03 14:38:53,685 WARN hdfs.DataStreamer: DataStreamer Exception org.apache.hadoop.ipc.RemoteException(java.io.IOException): File /user/zhangzhaobo/logs._COPYING_ could only be written to 0 of the 1 minReplication nodes. There are 0 datanode(s) running and no node(s) are excluded in this operation.     at org.apache.hadoop.hdfs.server.blockmanagement.BlockManager.chooseTarget4NewBlock(BlockManager.java:2116)     at org.apache.hadoop.hdfs.server.namenode.FSDirWriteFileOp.chooseTargetForNewBlock(FSDirWriteFileOp.java:287)     at org.apache.hadoop.hdfs.server.namenode.FSNamesystem.getAdditionalBlock(FSNamesystem.java:2688)     at org.apache.hadoop.hdfs.server.namenode.NameNodeRpcServer.addBlock(NameNodeRpcServer.java:875)     at org.apache.hadoop.hdfs.protocolPB.ClientNamenodeProtocolServerSideTranslatorPB.addBlock(ClientNamenodeProtocolServerSideTranslatorPB.java:559)     at org.apache.hadoop.hdfs.protocol.proto.ClientNamenodeProtocolProtos$ClientNamenodeProtocol$2.callBlockingMethod(ClientNamenodeProtocolProtos.java)     at org.apache.hadoop.ipc.ProtobufRpcEngine$Server$ProtoBufRpcInvoker.call(ProtobufRpcEngine.java:523)     at org.apache.hadoop.ipc.RPC$Server.call(RPC.java:991)     at org.apache.hadoop.ipc.Server$RpcCall.run(Server.java:869)     at org.apache.hadoop.ipc.Server$RpcCall.run(Server.java:815)     at java.security.AccessController.doPrivileged(Native Method)     at javax.security.auth.Subject.doAs(Subject.java:422)     at org.apache.hadoop.security.UserGroupInformation.doAs(UserGroupInformation.java:1682)     at org.apache.hadoop.ipc.Server$Handler.run(Server.java:2675)      at org.apache.hadoop.ipc.Client.getRpcResponse(Client.java:1491)     at org.apache.hadoop.ipc.Client.call(Client.java:1437)     at org.apache.hadoop.ipc.Client.call(Client.java:1347)     at org.apache.hadoop.ipc.ProtobufRpcEngine$Invoker.invoke(ProtobufRpcEngine.java:228)     at org.apache.hadoop.ipc.ProtobufRpcEngine$Invoker.invoke(ProtobufRpcEngine.java:116)     at com.sun.proxy.$Proxy11.addBlock(Unknown Source)     at org.apache.hadoop.hdfs.protocolPB.ClientNamenodeProtocolTranslatorPB.addBlock(ClientNamenodeProtocolTranslatorPB.java:504)     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:422)     at org.apache.hadoop.io.retry.RetryInvocationHandler$Call.invokeMethod(RetryInvocationHandler.java:165)     at org.apache.hadoop.io.retry.RetryInvocationHandler$Call.invoke(RetryInvocationHandler.java:157)     at org.apache.hadoop.io.retry.RetryInvocationHandler$Call.invokeOnce(RetryInvocationHandler.java:95)     at org.apache.hadoop.io.retry.RetryInvocationHandler.invoke(RetryInvocationHandler.java:359)     at com.sun.proxy.$Proxy12.addBlock(Unknown Source)     at org.apache.hadoop.hdfs.DFSOutputStream.addBlock(DFSOutputStream.java:1078)     at org.apache.hadoop.hdfs.DataStreamer.locateFollowingBlock(DataStreamer.java:1865)     at org.apache.hadoop.hdfs.DataStreamer.nextBlockOutputStream(DataStreamer.java:1668)     at org.apache.hadoop.hdfs.DataStreamer.run(DataStreamer.java:716) put: File /user/zhangzhaobo/logs._COPYING_ could only be written to 0 of the 1 minReplication nodes. There are 0 datanode(s) running and no node(s) are excluded in this operation. 

数据节点不见了???WTF?

【Hadoop踩雷】无法上传文件?有办法!

现在是有的 ,一开始没有!

所以就去找呀找~ 最后找到了两个法子。。

启动Hadoop时,DataNode启动后一会儿自动消失的解决方法

从日志中可以看出,原因是因为datanode的clusterID 和 namenode的clusterID 不匹配。

(在slaver端上修改)

打开hdfs-site.xml里配置的datanode和namenode对应的目录,分别打开current文件夹里的VERSION,可以看到clusterID项正如日志里记录的一样,确实不一致,修改datanode里VERSION文件的clusterID 与namenode里的一致,再重新启动dfs(执行start-dfs.sh)再执行jps命令可以看到datanode已正常启动。

上面这个是比较正统的做法!我是个正统的人吗??是!当然是。。但是这次不行。伪分布式。。。比较任性。猥琐一波!!

直接删除掉前面产生的文件就ok!

【Hadoop踩雷】无法上传文件?有办法!

我的是这样,看你把你的文件系统挂在哪儿了!!

然后运行下面的代码:

 ./sbin/stop-all.sh ./bin/hdfs namenode -format ./sbin/start-dfs.sh  ./bin/hdfs dfs -mkdir /user  ./bin/hdfs dfs -mkdir /user/zhangzhaobo  ./sbin/start-yarn.sh  hdfs dfs -put  Know.py 

当然一把就成功啦!!

【Hadoop踩雷】无法上传文件?有办法!

然后试试按照例程来哈~

进入mapreduce目录

【Hadoop踩雷】无法上传文件?有办法!

运行程序:

localhost:mapreduce zhangzhaobo$ hadoop jar hadoop-mapreduce-examples-3.1.0.jar wordcount /user/zhangzhaobo/in /user/zhangzhaobo/out/resultWordCount 
【Hadoop踩雷】无法上传文件?有办法!

查看result

【Hadoop踩雷】无法上传文件?有办法!

这是运行成功的过程:

2018-06-03 15:25:38,662 WARN util.NativeCodeLoader: Unable to load native-hadoop library for your platform... using builtin-java classes where applicable 2018-06-03 15:25:39,697 INFO client.RMProxy: Connecting to ResourceManager at /0.0.0.0:8032 2018-06-03 15:25:40,514 INFO mapreduce.JobResourceUploader: Disabling Erasure Coding for path: /tmp/hadoop-yarn/staging/zhangzhaobo/.staging/job_1528008869850_0003 2018-06-03 15:25:40,819 INFO input.FileInputFormat: Total input files to process : 1 2018-06-03 15:25:40,910 INFO mapreduce.JobSubmitter: number of splits:1 2018-06-03 15:25:40,960 INFO Configuration.deprecation: yarn.resourcemanager.system-metrics-publisher.enabled is deprecated. Instead, use yarn.system-metrics-publisher.enabled 2018-06-03 15:25:41,104 INFO mapreduce.JobSubmitter: Submitting tokens for job: job_1528008869850_0003 2018-06-03 15:25:41,106 INFO mapreduce.JobSubmitter: Executing with tokens: [] 2018-06-03 15:25:41,372 INFO conf.Configuration: resource-types.xml not found 2018-06-03 15:25:41,373 INFO resource.ResourceUtils: Unable to find 'resource-types.xml'. 2018-06-03 15:25:41,463 INFO impl.YarnClientImpl: Submitted application application_1528008869850_0003 2018-06-03 15:25:41,513 INFO mapreduce.Job: The url to track the job: http://localhost:8088/proxy/application_1528008869850_0003/ 2018-06-03 15:25:41,514 INFO mapreduce.Job: Running job: job_1528008869850_0003 2018-06-03 15:25:50,700 INFO mapreduce.Job: Job job_1528008869850_0003 running in uber mode : false 2018-06-03 15:25:50,702 INFO mapreduce.Job:  map 0% reduce 0% 2018-06-03 15:25:57,808 INFO mapreduce.Job:  map 100% reduce 0% 2018-06-03 15:26:04,871 INFO mapreduce.Job:  map 100% reduce 100% 2018-06-03 15:26:04,887 INFO mapreduce.Job: Job job_1528008869850_0003 completed successfully 2018-06-03 15:26:05,005 INFO mapreduce.Job: Counters: 49     File System Counters         FILE: Number of bytes read=2684         FILE: Number of bytes written=431255         FILE: Number of read operations=0         FILE: Number of large read operations=0         FILE: Number of write operations=0         HDFS: Number of bytes read=2281         HDFS: Number of bytes written=2126         HDFS: Number of read operations=8         HDFS: Number of large read operations=0         HDFS: Number of write operations=2     Job Counters          Launched map tasks=1         Launched reduce tasks=1         Data-local map tasks=1         Total time spent by all maps in occupied slots (ms)=4094         Total time spent by all reduces in occupied slots (ms)=4530         Total time spent by all map tasks (ms)=4094         Total time spent by all reduce tasks (ms)=4530         Total vcore-milliseconds taken by all map tasks=4094         Total vcore-milliseconds taken by all reduce tasks=4530         Total megabyte-milliseconds taken by all map tasks=4192256         Total megabyte-milliseconds taken by all reduce tasks=4638720     Map-Reduce Framework         Map input records=36         Map output records=191         Map output bytes=2902         Map output materialized bytes=2684         Input split bytes=126         Combine input records=191         Combine output records=138         Reduce input groups=138         Reduce shuffle bytes=2684         Reduce input records=138         Reduce output records=138         Spilled Records=276         Shuffled Maps =1         Failed Shuffles=0         Merged Map outputs=1         GC time elapsed (ms)=154         CPU time spent (ms)=0         Physical memory (bytes) snapshot=0         Virtual memory (bytes) snapshot=0         Total committed heap usage (bytes)=407896064     Shuffle Errors         BAD_ID=0         CONNECTION=0         IO_ERROR=0         WRONG_LENGTH=0         WRONG_MAP=0         WRONG_REDUCE=0     File Input Format Counters          Bytes Read=2155     File Output Format Counters          Bytes Written=2126 

弄了三次才成功的!!

【Hadoop踩雷】无法上传文件?有办法!

原因是一开始有一个地方一直报错。。说我的主类加载不到???WTF?

[2018-06-03 15:15:24.474]Container exited with a non-zero exit code 1. Error file: prelaunch.err. Last 4096 bytes of prelaunch.err : Last 4096 bytes of stderr : 错误: 找不到或无法加载主类 org.apache.hadoop.mapreduce.v2.app.MRAppMaster   [2018-06-03 15:15:24.474]Container exited with a non-zero exit code 1. Error file: prelaunch.err. Last 4096 bytes of prelaunch.err : Last 4096 bytes of stderr : 错误: 找不到或无法加载主类 org.apache.hadoop.mapreduce.v2.app.MRAppMaster 

然后找到了如下文章,贼有用!

解决运行 Hadoop MapReduce 任务时错误: 找不到或无法加载主类

然后例程主要是参考的这个人来的:

https://blog.csdn.net/dr_guo/article/details/50890582

正文之后

溜了溜了,在测试一个例程就睡觉,然后去健身房咯!晚上回去搭建集群~

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