我要评论pc基本配置如下：处理器：intel(r) core(tm) i5-3230m cpu @ 2.6ghz 2.60ghz 安装内存（ram）: 12.0gb 系统类型：64位操作系统
ubuntu-14.04_x64虚拟机，配置如下：内存：2gb 处理器：1 硬盘：40g 网络适配器：nat 系统：linux ubuntu 4.4.0-142-generic #168~14.04.1-ubuntu smp sat jan 19 11:26:28 utc 2019 x86_64 x86_64 x86_64 gnu/linux
~ sudo timedatectl set-timezone "asia/shanghai"
安装插件；
设置
vim行号；安装
ssh插件服务；安装
vsftpd插件服务并加以配置，方便文件上传下载；在
pc上安装xshell客户端；在
pc上安装ftp客户端。
jdk-7u51-linux-x64.gz 链接：http://pan.baidu.com/s/1dfft1gp 密码：cc5t hadoop-2.2.0-x64.tar.gz https://download.csdn.net/download/wwyymmddbb/10203840
在虚拟机做如下步骤：创建目录，存储工具包/home/zhangbocheng，并利用ftp上传相关软件包。
安装java1.7.0
~ mkdir java ~ cd java ➜ java tar -xf /home/zhangbocheng/jdk-7u51-linux-x64.gz ➜ java ln -s jdk1.7.0_51 jdk ➜ java vi ~/.bashrc ➜ java vi ~/.zshrc export java_home=$home/java/java export path=$java_home/bin:$path :wq ➜ java source ~/.bashrc ➜ java source ~/.zshrc ➜ java java -version java version "1.7.0_51" java(tm) se runtime environment (build 1.7.0_51-b13) java hotspot(tm) 64-bit server vm (build 24.51-b03, mixed mode)
hadoop2.2.0➜ ~ tar -xf /home/zhangbocheng/hadoop-2.2.0-x64.tar.gz ➜ ~ mv hadoop-2.2.0 hadoop2.2.0 ➜ ~ mkdir hadoop2.2.0/hdfs ➜ ~ mkdir hadoop2.2.0/hdfs/name ➜ ~ mkdir hadoop2.2.0/hdfs/data ➜ ~ mkdir hadoop2.2.0/logs ➜ ~ mkdir hadoop2.2.0/tmp
➜ ~ vi .zshrc export java_home=$home/java/jdk export classpath=$java_home/lib/tool.jar:$java_home/lib/dt.jar export path=$java_home/bin:$path ➜ ~ source .zshrc ➜ ~ echo $classpath /home/zhangbc/java/jdk/lib/tool.jar:/home/zhangbc/java/jdk/lib/dt.jar ➜ ~ vi .zshrc export hadoop_home=$home/hadoop2.2.0 export path=$hadoop_home/sbin:$hadoop_home/bin:$java_home/bin:$path export hadoop_log_dir=$hadoop_home/logs export yarn_log_dir=$hadoop_log_dir ➜ ~ source .zshrc ➜ ~ hadoop version hadoop 2.2.0 subversion unknown -r unknown compiled by root on 2014-09-21t22:41z compiled with protoc 2.5.0 from source with checksum 79e53ce7994d1628b240f09af91e1af4 this command was run using /home/zhangbc/hadoop2.2.0/share/hadoop/common/hadoop-common-2.2.0.jar
hadoop2.2.0配置文件# 检查并修改以下三个文件中java_home的值
➜ ~ vi hadoop2.2.0/etc/hadoop/hadoop-env.sh
➜ ~ vi hadoop2.2.0/etc/hadoop/yarn-env.sh
➜ ~ vi hadoop2.2.0/etc/hadoop/mapred-env.sh # 只需要去掉注释加以修改
export java_home=${java_home} # 错误
export java_home=/home/zhangbc/java/jdk # 正确
# 添加集群的slave节点
➜ ~ vi hadoop2.2.0/etc/hadoop/slaves
# localhost
slave_1
slave_2
slave_3
➜ ~ vi hadoop2.2.0/etc/hadoop/core-site.xml
<configuration>
<property>
<name>fs.defaultfs</name>
<value>hdfs://master:9000/</value>
<descrption>设定namenode的主机名及其端口</descrption>
</property>
<property>
<name>hadoop.tmp.dir</name>
<value>/home/zhangbc/hadoop2.2.0/tmp/hadoop-${user.name}</value>
<descrption>存储临时文件</descrption>
</property>
<property>
<name>hadoop.proxyuser.hadoop.hosts</name>
<value>*</value>
</property>
<property>
<name>hadoop.proxyuser.hadoop.groups</name>
<value>*</value>
</property>
</configuration>
➜ ~ vi hadoop2.2.0/etc/hadoop/hdfs-site.xml
<configuration>
<property>
<name>dfs.namenode.http-address</name>
<value>master:50070</value>
<descrption>设定namenode地址及其端口</descrption>
</property>
<property>
<name>dfs.namenode.secondary.http-address</name>
<value>slave_1:50090</value>
<descrption>设定secondnamenode地址及其端口</descrption>
</property>
<property>
<name>dfs.replication</name>
<value>3</value>
<descrption>设定hdfs存储文件的副本个数，默认为3</descrption>
</property>
<property>
<name>dfs.namenode.name.dir</name>
<value>file:///home/zhangbc/hadoop2.2.0/hdfs/name</value>
<descrption>设置namenode用来持续存储命名空间和交换日志的本地文件系统路径</descrption>
</property>
<property>
<name>dfs.datanode.data.dir</name>
<value>file:///home/zhangbc/hadoop2.2.0/hdfs/data</value>
<descrption>设置datanode在本地存储文件的目录列表</descrption>
</property>
<property>
<name>dfs.namenode.checkpoint.dir</name>
<value>file:///home/zhangbc/hadoop2.2.0/hdfs/namesecondary</value>
<descrption>设置secondarynamenode存储临时镜像的本地文件系统路径，
若这是一个用逗号分隔的列表，则镜像会冗余复制到所有目录</descrption>
</property>
<property>
<name>dfs.webhdfs.enable</name>
<value>true</value>
<descrption>是否允许网页浏览hdfs文件</descrption>
</property>
<property>
<name>dfs.stream-buffer-size</name>
<value>131072</value>
<descrption>默认为4kb,作为hadoop的缓冲区，用于hapdoop读写hdfs的文件，
还有map的输出都用到了这个缓冲区容量，131072=128kb</descrption>
</property>
</configuration>
➜ ~ vi hadoop2.2.0/etc/hadoop/mapred-site.xml
<configuration>
<property>
<name>mapreduce.framework.name</name>
<value>yarn</value>
</property>
<property>
<name>mapreduce.jobhistory.address</name>
<value>master:10020</value>
</property>
<property>
<name>mapreduce.jobhistory.webapp.address</name>
<value>master:19888</value>
</property>
</configuration>
➜ ~ vi hadoop2.2.0/etc/hadoop/yarn-site.xml
<configuration>
<property>
<name>yarn.resourcemanager.hostname</name>
<value>master</value>
</property>
<property>
<name>yarn.nodemanager.aux-services</name>
<value>mapreduce_shuffle</value>
</property>
<property>
<name>yarn.nodemanager.aux-services.mapreduce.shuffle.class</name>
<value>org.apache.hadoop.mapred.shufflehandler</value>
</property>
<property>
<name>yarn.resourcemanager.address</name>
<value>master:8032</value>
</property>
<property>
<name>yarn.resourcemanager.scheduler.address</name>
<value>master:8030</value>
</property>
<property>
<name>yarn.resourcemanager.resource-tracker.address</name>
<value>master:8031</value>
</property>
<property>
<name>yarn.resourcemanager.admin.address</name>
<value>master:8033</value>
</property>
<property>
<name>yarn.resourcemanager.webapp.address</name>
<value>master:8088</value>
</property>
</configuration>
_）➜ ~ sudo hostname master # 只对当前状态生效 [sudo] password for zhangbc: ➜ ~ hostname master ➜ ~ sudo vi /etc/hostname # 永久修改 master :wq
➜ ~ service ufw status ufw start/running ➜ ~ sudo service ufw stop [sudo] password for zhangbc: ufw stop/waiting ➜ ~ service ufw status ufw stop/waiting
vm通过 vmware workstation工具，关闭当前虚拟机，对其克隆三台虚拟机作为从机使用。
克隆方法选择“创建完整克隆(f)”，如图所示：
slave的host，并再重启使之生效。➜ ~ sudo vi /etc/hostname ➜ ~ sudo vi /etc/hosts ➜ ~ sudo reboot
➜ ~ sudo service ufw status [sudo] password for zhangbc: ufw start/running ➜ ~ sudo service ufw stop ufw stop/waiting ➜ ~ sudo service ufw status ufw stop/waiting ➜ ~ sudo ufw disable firewall stopped and disabled on system startup
hostname与ip➜ ~ sudo vi /etc/hosts 192.168.71.128 master 192.168.71.129 slave_1 192.168.71.130 slave_2 192.168.71.131 slave_3
ssh密钥，完成相关验证，注意保留原有的其他密钥，以备他用➜ .ssh mv id_rsa id_rsa_git ➜ .ssh mv id_rsa.pub id_rsa_git.pub ➜ .ssh ssh-keygen -t rsa -p '' -f ~/.ssh/id_rsa # 生成authorized_keys ➜ .ssh cat id_rsa.pub >> authorized_keys # 设置权限 ➜ .ssh sudo chmod 600 authorized_keys # ssh登录本机，并退出 ➜ .ssh ssh localhost the authenticity of host 'localhost (127.0.0.1)' can't be established. ecdsa key fingerprint is b6:fa:8d:2b:2d:0d:e4:fd:4f:44:ed:37:3f:79:b6:ce. are you sure you want to continue connecting (yes/no)? yes warning: permanently added 'localhost' (ecdsa) to the list of known hosts. welcome to ubuntu 14.04.6 lts (gnu/linux 4.4.0-142-generic x86_64) * documentation: https://help.ubuntu.com/ new release '16.04.6 lts' available. run 'do-release-upgrade' to upgrade to it. your hardware enablement stack (hwe) is supported until april 2019. last login: wed nov 13 20:17:41 2019 from 192.168.71.1 ➜ ~ exit connection to localhost closed. ➜ .ssh
# 将slave_1节点rsa通过ssh-copy-id分别复制到master，slave_2，slave_3 ➜ ~ ssh-copy-id -i ~/.ssh/id_rsa.pub master ➜ ~ ssh-copy-id -i ~/.ssh/id_rsa.pub slave_2 ➜ ~ ssh-copy-id -i ~/.ssh/id_rsa.pub slave_3 # 验证登录 ➜ ~ ssh master ➜ ~ ssh slave_2 ➜ ~ ssh slave_3 # 其他节点同步骤
五，hadoop启动与测试➜ ~ hdfs namenode -format 19/11/13 21:57:48 info namenode.namenode: startup_msg: /************************************************************ startup_msg: starting namenode startup_msg: host = master/192.168.71.128 startup_msg: args = [-format] startup_msg: version = 2.2.0 ......... 19/11/13 21:57:55 info util.exitutil: exiting with status 0 # 表示成功 .........
hdfszhangbc@master:~$ start-dfs.sh starting namenodes on [master] master: starting namenode, logging to /home/zhangbc/hadoop2.2.0/logs/hadoop-zhangbc-namenode-master.out slave_1: starting datanode, logging to /home/zhangbc/hadoop2.2.0/logs/hadoop-zhangbc-datanode-slave_1.out slave_3: starting datanode, logging to /home/zhangbc/hadoop2.2.0/logs/hadoop-zhangbc-datanode-slave_3.out slave_2: starting datanode, logging to /home/zhangbc/hadoop2.2.0/logs/hadoop-zhangbc-datanode-slave_2.out zhangbc@master:~$ jps 6524 jps 5771 namenode zhangbc@slave_1:~$ jps 4919 jps 4818 datanode zhangbc@slave_2:~$ jps 4919 jps 4801 datanode zhangbc@slave_3:~$ jps 4705 datanode 4800 jps
web验证：http://192.168.71.128:50070
yarnzhangbc@master:~$ start-yarn.sh starting yarn daemons starting resourcemanager, logging to /home/zhangbc/hadoop2.2.0/logs/yarn-zhangbc-resourcemanager-master.out slave_2: starting nodemanager, logging to /home/zhangbc/hadoop2.2.0/logs/yarn-zhangbc-nodemanager-slave_2.out slave_1: starting nodemanager, logging to /home/zhangbc/hadoop2.2.0/logs/yarn-zhangbc-nodemanager-slave_1.out slave_3: starting nodemanager, logging to /home/zhangbc/hadoop2.2.0/logs/yarn-zhangbc-nodemanager-slave_3.out zhangbc@master:~$ jps 5771 namenode 6642 jps zhangbc@slave_1:~$ jps 5099 jps 4818 datanode 5011 nodemanager zhangbc@slave_2:~$ jps 5101 jps 5016 nodemanager 4801 datanode zhangbc@slave_2:~$ jps 5101 jps 5016 nodemanager 4801 datanode
web验证：http://192.168.71.128:8088
jobhistory serverzhangbc@master:~$ mr-jobhistory-daemon.sh start historyserver starting historyserver, logging to /home/zhangbc/hadoop2.2.0/logs/mapred-zhangbc-historyserver-master.out zhangbc@master:~$ mr-jobhistory-daemon.sh stop historyserver
web验证：http://192.168.71.128:19888
# 创建目录 zhangbc@master:~$ hdfs dfs -mkdir -p /data/wordscount zhangbc@master:~$ hdfs dfs -mkdir -p /output # 查看数据目录 zhangbc@master:~$ hdfs dfs -ls /data # 上传本地文件 zhangbc@master:~$ hdfs dfs -put hadoop2.2.0/etc/hadoop/core-site.xml /data/wordscount # 执行 zhangbc@master:~$ hadoop jar hadoop2.2.0/share/hadoop/mapreduce/hadoop-mapreduce-examples-2.2.0.jar wordcount /data/wordscount /output/wordscount ............................... 19/11/14 13:04:45 info mapreduce.job: the url to track the job: http://master:8088/proxy/application_1573705994579_0001/ 19/11/14 13:04:45 info mapreduce.job: running job: job_1573705994579_0001 19/11/14 13:04:59 info mapreduce.job: job job_1573705994579_0001 running in uber mode : false 19/11/14 13:04:59 info mapreduce.job: map 0% reduce 0% 19/11/14 13:05:14 info mapreduce.job: map 100% reduce 0% 19/11/14 13:05:27 info mapreduce.job: map 100% reduce 100% 19/11/14 13:05:27 info mapreduce.job: job job_1573705994579_0001 completed successfully 19/11/14 13:05:27 info mapreduce.job: counters: 43 ............................................ # 查看运行结果 zhangbc@master:~$ hdfs dfs -cat /output/wordscount/part-r-00000
zhangbc@master:~$ hdfs dfs -put hadoop2.2.0/etc/hadoop/core-site.xml /data/wordcount
19/11/14 10:13:24 warn hdfs.dfsclient: datastreamer exception
org.apache.hadoop.ipc.remoteexception(java.io.ioexcept、ion): file /data/wordcount/core-site.xml._copying_ could only be replicated to 0 nodes instead of minreplication (=1). there are 0 datanode(s) running and no node(s) are excluded in this operation.
at org.apache.hadoop.hdfs.server.blockmanagement.blockmanager.choosetarget(blockmanager.java:1384)
at org.apache.hadoop.hdfs.server.namenode.fsnamesystem.getadditionalblock(fsnamesystem.java:2477)
at org.apache.hadoop.hdfs.server.namenode.namenoderpcserver.addblock(namenoderpcserver.java:555)
at org.apache.hadoop.hdfs.protocolpb.clientnamenodeprotocolserversidetranslatorpb.addblock(clientnamenodeprotocolserversidetranslatorpb.java:387)
at org.apache.hadoop.hdfs.protocol.proto.clientnamenodeprotocolprotos$clientnamenodeprotocol$2.callblockingmethod(clientnamenodeprotocolprotos.java:59582)
at org.apache.hadoop.ipc.protobufrpcengine$server$protobufrpcinvoker.call(protobufrpcengine.java:585)
at org.apache.hadoop.ipc.rpc$server.call(rpc.java:928)
at org.apache.hadoop.ipc.server$handler$1.run(server.java:2048)
at org.apache.hadoop.ipc.server$handler$1.run(server.java:2044)
at java.security.accesscontroller.doprivileged(native method)
at javax.security.auth.subject.doas(subject.java:415)
at org.apache.hadoop.security.usergroupinformation.doas(usergroupinformation.java:1491)
at org.apache.hadoop.ipc.server$handler.run(server.java:2042)
at org.apache.hadoop.ipc.client.call(client.java:1347)
at org.apache.hadoop.ipc.client.call(client.java:1300)
at org.apache.hadoop.ipc.protobufrpcengine$invoker.invoke(protobufrpcengine.java:206)
at com.sun.proxy.$proxy9.addblock(unknown source)
at sun.reflect.nativemethodaccessorimpl.invoke0(native method)
at sun.reflect.nativemethodaccessorimpl.invoke(nativemethodaccessorimpl.java:57)
at sun.reflect.delegatingmethodaccessorimpl.invoke(delegatingmethodaccessorimpl.java:43)
at java.lang.reflect.method.invoke(method.java:606)
at org.apache.hadoop.io.retry.retryinvocationhandler.invokemethod(retryinvocationhandler.java:186)
at org.apache.hadoop.io.retry.retryinvocationhandler.invoke(retryinvocationhandler.java:102)
at com.sun.proxy.$proxy9.addblock(unknown source)
at org.apache.hadoop.hdfs.protocolpb.clientnamenodeprotocoltranslatorpb.addblock(clientnamenodeprotocoltranslatorpb.java:330)
at org.apache.hadoop.hdfs.dfsoutputstream$datastreamer.locatefollowingblock(dfsoutputstream.java:1226)
at org.apache.hadoop.hdfs.dfsoutputstream$datastreamer.nextblockoutputstream(dfsoutputstream.java:1078)
at org.apache.hadoop.hdfs.dfsoutputstream$datastreamer.run(dfsoutputstream.java:514)
put: file /data/wordcount/core-site.xml._copying_ could only be replicated to 0 nodes instead of minreplication (=1). there are 0 datanode(s) running and no node(s) are excluded in this operation.
19/11/14 10:13:24 error hdfs.dfsclient: failed to close file /data/wordcount/core-site.xml._copying_
org.apache.hadoop.ipc.remoteexception(java.io.ioexception): file /data/wordcount/core-site.xml._copying_ could only be replicated to 0 nodes instead of minreplication (=1). there are 0 datanode(s) running and no node(s) are excluded in this operation.
at org.apache.hadoop.hdfs.server.blockmanagement.blockmanager.choosetarget(blockmanager.java:1384)
at org.apache.hadoop.hdfs.server.namenode.fsnamesystem.getadditionalblock(fsnamesystem.java:2477)
at org.apache.hadoop.hdfs.server.namenode.namenoderpcserver.addblock(namenoderpcserver.java:555)
at org.apache.hadoop.hdfs.protocolpb.clientnamenodeprotocolserversidetranslatorpb.addblock(clientnamenodeprotocolserversidetranslatorpb.java:387)
at org.apache.hadoop.hdfs.protocol.proto.clientnamenodeprotocolprotos$clientnamenodeprotocol$2.callblockingmethod(clientnamenodeprotocolprotos.java:59582)
at org.apache.hadoop.ipc.protobufrpcengine$server$protobufrpcinvoker.call(protobufrpcengine.java:585)
at org.apache.hadoop.ipc.rpc$server.call(rpc.java:928)
at org.apache.hadoop.ipc.server$handler$1.run(server.java:2048)
at org.apache.hadoop.ipc.server$handler$1.run(server.java:2044)
at java.security.accesscontroller.doprivileged(native method)
at javax.security.auth.subject.doas(subject.java:415)
at org.apache.hadoop.security.usergroupinformation.doas(usergroupinformation.java:1491)
at org.apache.hadoop.ipc.server$handler.run(server.java:2042)
at org.apache.hadoop.ipc.client.call(client.java:1347)
at org.apache.hadoop.ipc.client.call(client.java:1300)
at org.apache.hadoop.ipc.protobufrpcengine$invoker.invoke(protobufrpcengine.java:206)
at com.sun.proxy.$proxy9.addblock(unknown source)
at sun.reflect.nativemethodaccessorimpl.invoke0(native method)
at sun.reflect.nativemethodaccessorimpl.invoke(nativemethodaccessorimpl.java:57)
at sun.reflect.delegatingmethodaccessorimpl.invoke(delegatingmethodaccessorimpl.java:43)
at java.lang.reflect.method.invoke(method.java:606)
at org.apache.hadoop.io.retry.retryinvocationhandler.invokemethod(retryinvocationhandler.java:186)
at org.apache.hadoop.io.retry.retryinvocationhandler.invoke(retryinvocationhandler.java:102)
at com.sun.proxy.$proxy9.addblock(unknown source)
at org.apache.hadoop.hdfs.protocolpb.clientnamenodeprotocoltranslatorpb.addblock(clientnamenodeprotocoltranslatorpb.java:330)
at org.apache.hadoop.hdfs.dfsoutputstream$datastreamer.locatefollowingblock(dfsoutputstream.java:1226)
at org.apache.hadoop.hdfs.dfsoutputstream$datastreamer.nextblockoutputstream(dfsoutputstream.java:1078)
at org.apache.hadoop.hdfs.dfsoutputstream$datastreamer.run(dfsoutputstream.java:514)
主要原因是重新格式化文件系统，导致master节点下的hadoop2.2.0/hdfs/name/current/version中的clusterid和slave节点下的hadoop2.2.0/hdfs/data/current/version中的clusterid不一致。在浏览器输入可以发现live nodes为0。
解决方案是修改master节点下的clusterid使之与slave节点下的clusterid一致，然后重启服务即可。
jar报错问题container launch failed for container_1573700741821_0001_01_000007 : java.lang.illegalargumentexception: does not contain a valid host:port authority: slave_1:33775
主要原因：hadoop nodemanager结点主机名不能带下划线_。
解决方案：修改主机名称。
sudo: unable to resolve host master解决方案如下：
➜ ~ sudo vi /etc/hosts 1 127.0.0.1 localhost 2 127.0.1.1 ubuntu 3 127.0.1.1 master :wq!
通过本次实验，对集群概念有个基本的认识，在搭建过程中遇到问题不算太多，主要是对局域网组建缺乏认识深度，本集群环境可以进一步扩展，如动态增减节点，借助zookeeper技术加以融合等在企业中是比较常见的做法。
如对本文有疑问， 点击进行留言回复！！
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