Hadoop zookeeper HA高可靠集群部署搭建，及错误诊断

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篇首语：本文由小常识网(cha138.com)小编为大家整理，主要介绍了Hadoop zookeeper HA高可靠集群部署搭建，及错误诊断相关的知识，希望对你有一定的参考价值。

http://archive-primary.cloudera.com/cdh5/cdh/5/

一.准备工作
1.修改Linux主机名，每台都得配置
[[email protected] ~]# vim /etc/sysconfig/network
NETWORKING=yes
HOSTNAME=h201
2.修改IP /etc/sysconfig/network-scripts/ifcfg-eth0
3.修改主机名和IP的映射关系（h24，h25为主，h21，h22,h23为从）
[[email protected] ~]# vim /etc/hosts
192.168.1.21 h21
192.168.1.22 h22
192.168.1.23 h23
192.168.1.24 h24
192.168.1.25 h25
######注意######如果你们公司是租用的服务器或是使用的云主机（如华为用主机、阿里云主机等）
/etc/hosts里面要配置的是内网IP地址和主机名的映射关系

4.关闭防火墙
#查看防火墙状态
[[email protected] ~]# service iptables status
#关闭防火墙
[[email protected] ~]# service iptables stop
#查看防火墙开机启动状态
[[email protected] ~]# chkconfig iptables --list
#关闭防火墙开机启动
[[email protected] ~]# chkconfig iptables off
5台机器 创建hadoop 用户
[[email protected] ~]# useradd hadoop
[[email protected] ~]# passwd hadoop
hadoop 密码:123456
前4步用root用户操作，操作完后重启机器

5.ssh免登陆hadoop用户操作
[[email protected] ~]# su - hadoop
#生成ssh免登陆密钥
#进入到我的home目录
cd ~/.ssh
ssh-keygen -t rsa （四个回车）
执行完这个命令后，会生成两个文件id_rsa（私钥）、id_rsa.pub（公钥）
将公钥拷贝到要免密登陆的目标机器上
[[email protected] ~]$ ssh-keygen -t rsa
[[email protected] ~]$ ssh-keygen -t rsa
[[email protected] ~]$ ssh-keygen -t rsa
[[email protected] ~]$ ssh-keygen -t rsa
[[email protected] ~]$ ssh-keygen -t rsa

[[email protected] ~]$ ssh-copy-id -i /home/hadoop/.ssh/id_rsa.pub h21
[[email protected] ~]$ ssh-copy-id -i /home/hadoop/.ssh/id_rsa.pub h22
[[email protected] ~]$ ssh-copy-id -i /home/hadoop/.ssh/id_rsa.pub h23
[[email protected] ~]$ ssh-copy-id -i /home/hadoop/.ssh/id_rsa.pub h24
[[email protected] ~]$ ssh-copy-id -i /home/hadoop/.ssh/id_rsa.pub h25

[[email protected] ~]$ ssh-copy-id -i /home/hadoop/.ssh/id_rsa.pub h21
[[email protected] ~]$ ssh-copy-id -i /home/hadoop/.ssh/id_rsa.pub h22
[[email protected] ~]$ ssh-copy-id -i /home/hadoop/.ssh/id_rsa.pub h23
[[email protected] ~]$ ssh-copy-id -i /home/hadoop/.ssh/id_rsa.pub h24
[[email protected] ~]$ ssh-copy-id -i /home/hadoop/.ssh/id_rsa.pub h25

[[email protected] ~]$ ssh-copy-id -i /home/hadoop/.ssh/id_rsa.pub h21
[[email protected] ~]$ ssh-copy-id -i /home/hadoop/.ssh/id_rsa.pub h22
[[email protected] ~]$ ssh-copy-id -i /home/hadoop/.ssh/id_rsa.pub h23
[[email protected] ~]$ ssh-copy-id -i /home/hadoop/.ssh/id_rsa.pub h24
[[email protected] ~]$ ssh-copy-id -i /home/hadoop/.ssh/id_rsa.pub h25

[[email protected] ~]$ ssh-copy-id -i /home/hadoop/.ssh/id_rsa.pub h21
[[email protected] ~]$ ssh-copy-id -i /home/hadoop/.ssh/id_rsa.pub h22
[[email protected] ~]$ ssh-copy-id -i /home/hadoop/.ssh/id_rsa.pub h23
[[email protected] ~]$ ssh-copy-id -i /home/hadoop/.ssh/id_rsa.pub h24
[[email protected] ~]$ ssh-copy-id -i /home/hadoop/.ssh/id_rsa.pub h25

[[email protected] ~]$ ssh-copy-id -i /home/hadoop/.ssh/id_rsa.pub h21
[[email protected] ~]$ ssh-copy-id -i /home/hadoop/.ssh/id_rsa.pub h22
[[email protected] ~]$ ssh-copy-id -i /home/hadoop/.ssh/id_rsa.pub h23
[[email protected] ~]$ ssh-copy-id -i /home/hadoop/.ssh/id_rsa.pub h24
[[email protected] ~]$ ssh-copy-id -i /home/hadoop/.ssh/id_rsa.pub h25

6.安装JDK，配置环境变量等root用户操作（ //根据自己的路金配置）
卸载系统之前jdk版本（便于已安装的jdk生效）
[[email protected] ~]$rpm -e --nodeps java-1.4.2-gcj-compat-1.4.2.0-40jpp.115

[[email protected] tmp]# tar -zxvf jdk-7u25-linux-i586.tar.gz -C /usr/local
[[email protected] ~]# vim /etc/profile 或者在用户下 vim .bash_profile
export JAVA_HOME=/usr/local/jdk1.7.0_25
export HADOOP_HOME=/usr/local/hadoop-2.6.0
export PATH=$PATH:$JAVA_HOME/bin:$HADOOP_HOME/bin:$HADOOP_HOME/sbin
source /etc/profile 或者 source .bash_profile
查看java版本
[[email protected] ~]# java -version
————————————————————————————————

（/etc/bashrc

export JAVA_HOME=/usr/jdk1.7.0_25

export JRE_HOME=$JAVA_HOME/jre

export PATH=$JAVA_HOME/bin:$PATH）

————————————————————————————————

二.集群规划：
主机名 IP 安装软件 运行进程
h24 192.168.1.24:jdk、hadoop
namenode resourcemanage
DFSZKFailoverController(zkfc)
h25 192.168.1.25:jdk、hadoop
namenode resourcemanage
DFSZKFailoverController(zkfc)
h21 192.168.1.21:jdk、hadoop、zookeeper
datanode nodemanage
journalnode QuorumPeerMain

h22 192.168.1.22:jdk、hadoop、zookeeper
datanode nodemanage
journalnode QuorumPeerMain
h23 192.168.1.23:jdk、hadoop、zookeeper
datanode nodemanage
journalnode QuorumPeerMain

三.安装步骤：
1.安装配置zooekeeper集群（在hadoop-server3上）
1.1解压
[[email protected] tmp]# tar zxvf zookeeper-3.4.5-cdh5.5.2.tar.gz -C /usr/local/
1.2修改配置
[[email protected] tmp]# cd /usr/localzookeeper-3.4.5/conf/
[[email protected] conf]# cp zoo_sample.cfg zoo.cfg
[[email protected] conf]# vim zoo.cfg
修改添加：
dataDir=/usr/local/zookeeper-3.4.5-cdh5.5.2/data
dataLogDir=/usr/local/zookeeper-3.4.5-cdh5.5.2/log
在最后添加：
server.1=192.168.1.23:2888:3888
server.2=192.168.1.24:2888:3888
server.3=192.168.1.25:2888:3888
保存退出
然后创建一个data文件夹
[[email protected] ~]# cd /usr/local/zookeeper-3.4.5-cdh5.5.2/
[[email protected] zookeeper-3.4.5-cdh5.5.2]# mkdir -pv data log
再创建一个空文件
touch /usr/localzookeeper-3.4.5/data/myid
最后向该文件写入ID
echo 1 > /usr/localzookeeper-3.4.5/data/myid
1.3将配置好的zookeeper拷贝到其他节点
[[email protected] ~]# scp -r /usr/localzookeeper-3.4.5/ h22:/usr/local
[[email protected] ~]# scp -r /usr/localzookeeper-3.4.5/ h23:/usr/local
注意：修改hadoop-server4、hadoop-server5对应/usr/localzookeeper-3.4.5/data/myid内容
hadoop-server4：
echo 2 > /usr/localzookeeper-3.4.5/data/myid
hadoop-server5：
echo 3 > /usr/localzookeeper-3.4.5/data/myid

2.安装配置hadoop集群（在hadoop-server1上操作）
2.1解压
[[email protected] tmp]# tar -zxvf hadoop-2.6.0-cdh5.5.2.tar.gz -C /usr/local/
mv hadoop-2.6.0-cdh5.5.2 hadoop-2.6.0
2.2配置HDFS（hadoop2.0所有的配置文件都在$HADOOP_HOME/etc/hadoop目录下）
#将hadoop添加到环境变量中
vim /etc/profile或者在用户下 vim .bash_profile
export JAVA_HOME=/usr/local/jdk1.7.0_25
export HADOOP_HOME=/usr/local/hadoop-2.6.0
export PATH=$PATH:$JAVA_HOME/bin:$HADOOP_HOME/bin

#hadoop2.0的配置文件全部在$HADOOP_HOME/etc/hadoop下
[[email protected] local]# cd /usr/local/hadoop-2.6.0/etc/hadoop

2.2.1修改vim hadoop-env.sh
export JAVA_HOME=/usr/local/jdk1.7.0_25

2.2.2修改vim core-site.xml
<configuration>

fs.defaultFS hdfs://ns1/ hadoop.tmp.dir /usr/local/hadoop-2.6.0/tmp ha.zookeeper.quorum h21:2181,h22:2181,h23:2181 2.2.3修改vim hdfs-site.xml dfs.nameservices ns1 dfs.ha.namenodes.ns1 nn1,nn2 dfs.namenode.rpc-address.ns1.nn1 h24:9000 dfs.namenode.http-address.ns1.nn1 h24:50070 dfs.namenode.rpc-address.ns1.nn2 h25:9000 dfs.namenode.http-address.ns1.nn2 h25:50070 dfs.namenode.shared.edits.dir qjournal://h21:8485;h22:8485;h23:8485/ns1 dfs.journalnode.edits.dir /usr/local/hadoop-2.6.0/journaldata dfs.ha.automatic-failover.enabled true dfs.client.failover.proxy.provider.ns1 org.apache.hadoop.hdfs.server.namenode.ha.ConfiguredFailoverProxyProvider dfs.ha.fencing.methods sshfence shell(/bin/true) dfs.ha.fencing.ssh.private-key-files /home/hadoop/.ssh/id_rsa dfs.ha.fencing.ssh.connect-timeout 30000 2.2.4 拷贝生成 [[email protected] hadoop]# cp mapred-site.xml.template mapred-site.xml 修改vim mapred-site.xml mapreduce.framework.name yarn 2.2.5修改vim yarn-site.xml yarn.resourcemanager.ha.enabled true yarn.resourcemanager.cluster-id yrc yarn.resourcemanager.ha.rm-ids rm1,rm2 yarn.resourcemanager.hostname.rm1 h24 yarn.resourcemanager.hostname.rm2 h25 yarn.resourcemanager.zk-address h21:2181,h22:2181,h23:2181 yarn.nodemanager.aux-services mapreduce_shuffle 2.2.6修改vim slaves(slaves是指定子节点的位置) h21 h22 h23 —————————————————————————————————————————————————————————————------------------------------------------- ******************************************************************************************************** 2.2.7配置免密码登陆 #首先要配置hadoop-server1到hadoop-server2、hadoop-server3、hadoop-server4、hadoop-server5的免密码登陆 #在hadoop-server1上生产一对钥匙 ssh-keygen -t rsa #将公钥拷贝到其他节点，包括自己 ssh-copy-id h201 ssh-copy-id h202 ssh-copy-id h203 ssh-copy-id h204 ssh-copy-id h205 #注意:resourcemanager到nodemanager要配置免密登录 #注意：两个namenode之间要配置ssh免密码登陆，别忘了配置hadoop-server2到hadoop-server1的免登陆 在hadoop-server2上生产一对钥匙 ssh-keygen -t rsa ssh-copy-id -i h201 ********************************************************************************************************** ____________________________________________________________________________________________________________ 2.4将配置好的hadoop拷贝到其他节点 [[email protected] ~]$ scp -r /usr/local/hadoop-2.6.0/ h21:/usr/local/ [[email protected] ~]$ scp -r /usr/local/hadoop-2.6.0/ h22:/usr/local/ [[email protected] ~]$ scp -r /usr/local/hadoop-2.6.0/ h23:/usr/local/ [[email protected] ~]$ scp -r /usr/local/hadoop-2.6.0/ h25:/usr/local/ 授权 [[email protected] ~]$chown hadoop.hadoop /usr/local/hadoop-2.6.0/ -R [[email protected] ~]$chown hadoop.hadoop /usr/local/hadoop-2.6.0/ -R [[email protected] ~]$chown hadoop.hadoop /usr/local/hadoop-2.6.0/ -R [[email protected] ~]$chown hadoop.hadoop /usr/local/hadoop-2.6.0/ -R [[email protected] ~]$chown hadoop.hadoop /usr/local/hadoop-2.6.0/ -R 配置环境变量 [[email protected] ~]$ su - hadoop [[email protected] ~]$ vi .bash_profile /etc/profile export JAVA_HOME=/usr/local/jdk1.7.0_25 export JAVA_BIN=/usr/local/jdk1.7.0_25/bin export PATH=$PATH:$JAVA_HOME/bin export CLASSPATH=.:$JAVA_HOME/lib/dt.jar:$JAVA_HOME/lib/tools.jar export JAVA_HOME JAVA_BIN PATH CLASSPATH HADOOP_HOME=/usr/local/hadoop-2.6.0 HADOOP_SBIN=/usr/local/hadoop-2.6.0/sbin HADOOP_CONF_DIR=$HADOOP_HOME/etc/hadoop PATH=$HADOOP_HOME/bin:$PATH export HADOOP_HOME HADOOP_CONF_DIR PATH [[email protected] ~]$ su - hadoop [[email protected] ~]$ vi .bash_profile /etc/profile export JAVA_HOME=/usr/local/jdk1.7.0_25 export JAVA_BIN=/usr/local/jdk1.7.0_25/bin export PATH=$PATH:$JAVA_HOME/bin export CLASSPATH=.:$JAVA_HOME/lib/dt.jar:$JAVA_HOME/lib/tools.jar export JAVA_HOME JAVA_BIN PATH CLASSPATH HADOOP_HOME=/usr/local/hadoop-2.6.0 HADOOP_SBIN=/usr/local/hadoop-2.6.0/sbin HADOOP_CONF_DIR=$HADOOP_HOME/etc/hadoop PATH=$HADOOP_HOME/bin:$PATH export HADOOP_HOME HADOOP_CONF_DIR PATH [[email protected] ~]$ source .bash_profile 或 su - root su - hadoop 或 reboot [email protected]:/usr/local ###注意：严格按照下面的步骤 2.5启动zookeeper集群（分别在hadoop-server3、hadoop-server4、hadoop-server5上启动zk） [[email protected] ~]$ cd /usr/local/zookeeper-3.4.5-cdh5.5.2/bin/ [[email protected] bin]$ ./zkServer.sh start [[email protected] bin]$ ./zkServer.sh status [[email protected] ~]$ cd /usr/local/zookeeper-3.4.5-cdh5.5.2/bin/ [[email protected] bin]$ ./zkServer.sh start [[email protected] bin]$ ./zkServer.sh status [[email protected] ~]$ cd /usr/local/zookeeper-3.4.5-cdh5.5.2/bin/ [[email protected] bin]$ ./zkServer.sh start [[email protected] bin]$ ./zkServer.sh status #查看状态：一个leader，两个follower 2.6启动journalnode（分别在在hadoop-server3、hadoop-server4、hadoop-server5上执行） [[email protected] hadoop]$ cd /usr/local/hadoop-2.6.0 [[email protected] hadoop-2.6.0]$ sbin/hadoop-daemon.sh start journalnode [[email protected] hadoop-2.6.0]$ jps 12744 JournalNode 4133 QuorumPeerMain 12790 Jps [[email protected] hadoop]$ cd /usr/local/hadoop-2.6.0 [[email protected] hadoop-2.6.0]$ sbin/hadoop-daemon.sh start journalnode [[email protected] hadoop-2.6.0]$ jps 12744 JournalNode 4133 QuorumPeerMain 12790 Jps [[email protected] hadoop]$ cd /usr/local/hadoop-2.6.0 [[email protected] hadoop-2.6.0]$ sbin/hadoop-daemon.sh start journalnode [[email protected] hadoop-2.6.0]$ jps 12744 JournalNode 4133 QuorumPeerMain 12790 Jps #运行jps命令检验，hadoop-server3、hadoop-server4、hadoop-server5上多了JournalNode进程 ________________________________ ******************************** [[email protected] hadoop-2.6.0]$ jps 12744 JournalNode 4133 QuorumPeerMain 12790 Jps ********************************* _________________________________ 2.7格式化HDFS #在hadoop-server1上执行命令: [[email protected] hadoop]$ cd /usr/local/hadoop-2.6.0/ [[email protected] hadoop-2.6.0]$ bin/hdfs namenode -format #格式化后会在根据core-site.xml中的hadoop.tmp.dir配置生成个文件，这里我配置的 是/usr/local/hadoop-2.6.0/tmp，然 后将/usr/local/hadoop-2.6.0/tmp拷贝到hadoop-server2的/usr/local/hadoop-2.6.0/下。 [[email protected] hadoop-2.6.0]$ scp -r tmp/ h25:/usr/local/hadoop-2.6.0/ ##也可以这样，在hadoop-server2上执行命令：建议hdfs namenode -bootstrapStandby 2.8格式化ZKFC(在hadoop-server1上执行即可) [[email protected] hadoop-2.6.0]$ bin/hdfs zkfc -formatZK 2.9启动HDFS(在hadoop-server1上执行,输入密码两次) [[email protected] hadoop-2.6.0]$ sbin/start-dfs.sh ___________________________________________________________________________________________________________________________________________________ *************************************************************************************************************************************************** [[email protected] hadoop-2.6.0]$ sbin/start-dfs.sh 18/06/21 02:01:57 WARN util.NativeCodeLoader: Unable to load native-hadoop library for your platform... using builtin-java classes where applicable Starting namenodes on [h24 h25] [email protected]‘s password: h24: starting namenode, logging to /usr/local/hadoop-2.6.0/logs/hadoop-hadoop-namenode-h24.out h25: Connection closed by 192.168.1.25 h21: starting datanode, logging to /usr/local/hadoop-2.6.0/logs/hadoop-hadoop-datanode-h21.out h22: starting datanode, logging to /usr/local/hadoop-2.6.0/logs/hadoop-hadoop-datanode-h22.out h23: starting datanode, logging to /usr/local/hadoop-2.6.0/logs/hadoop-hadoop-datanode-h23.out Starting journal nodes [h21 h22 h23] h22: journalnode running as process 12589. Stop it first. h23: journalnode running as process 12709. Stop it first. h21: journalnode running as process 12744. Stop it first. 18/06/21 02:06:49 WARN util.NativeCodeLoader: Unable to load native-hadoop library for your platform... using builtin-java classes where applicable Starting ZK Failover Controllers on NN hosts [h24 h25] [email protected]‘s password: h24: starting zkfc, logging to /usr/local/hadoop-2.6.0/logs/hadoop-hadoop-zkfc-h24.out *************************************************************************************************************************************************** ____________________________________________________________________________________________________________________________________________________ [[email protected] hadoop-2.6.0]$ sbin/start-dfs.sh 18/06/21 02:09:30 WARN util.NativeCodeLoader: Unable to load native-hadoop library for your platform... using builtin-java classes where applicable Starting namenodes on [h24 h25] [email protected]‘s password: h24: starting namenode, logging to /usr/local/hadoop-2.6.0/logs/hadoop-hadoop-namenode-h24.out h25: starting namenode, logging to /usr/local/hadoop-2.6.0/logs/hadoop-hadoop-namenode-h25.out h22: starting datanode, logging to /usr/local/hadoop-2.6.0/logs/hadoop-hadoop-datanode-h22.out h21: starting datanode, logging to /usr/local/hadoop-2.6.0/logs/hadoop-hadoop-datanode-h21.out h23: starting datanode, logging to /usr/local/hadoop-2.6.0/logs/hadoop-hadoop-datanode-h23.out Starting journal nodes [h21 h22 h23] h21: starting journalnode, logging to /usr/local/hadoop-2.6.0/logs/hadoop-hadoop-journalnode-h21.out h23: starting journalnode, logging to /usr/local/hadoop-2.6.0/logs/hadoop-hadoop-journalnode-h23.out h22: starting journalnode, logging to /usr/local/hadoop-2.6.0/logs/hadoop-hadoop-journalnode-h22.out 18/06/21 02:09:52 WARN util.NativeCodeLoader: Unable to load native-hadoop library for your platform... using builtin-java classes where applicable Starting ZK Failover Controllers on NN hosts [h24 h25] [email protected]‘s password: h24: starting zkfc, logging to /usr/local/hadoop-2.6.0/logs/hadoop-hadoop-zkfc-h24.out h25: starting zkfc, logging to /usr/local/hadoop-2.6.0/logs/hadoop-hadoop-zkfc-h25.out 2.10启动YARN(#####注意#####：是在hadoop-server1上执行start-yarn.sh) [[email protected] hadoop-2.6.0]$ sbin/start-yarn.sh 在hadoop-server2上启动 yarn-daemon.sh start resourcemanager [[email protected] sbin]$ ./yarn-daemon.sh start resourcemanager 到此，hadoop-2.6.0配置完毕，可以统计浏览器访问: http://192.168.1.24:50070 NameNode ‘h24:9000‘ (active) http://192.168.1.25:50070 NameNode ‘h25:9000‘ (standby) 验证HDFS HA 首先向hdfs上传一个文件 h24 [[email protected] hadoop]$ hadoop fs -mkdir /profile hadoop fs -put /etc/profile /profile hadoop fs -ls / 然后再kill掉active的NameNode —————————————————————————————————————————————————————— ****************************************************** [[email protected] hadoop-2.6.0]$ sbin/hadoop-daemon.sh start namenode namenode running as process 17838. Stop it first. 通过这种方法也可以查看进程号 **************************************************** ———————————————————————————————————————————————————————— [[email protected] hadoop]$ ps -ef | grep ‘NameNode‘ 结果显示 hadoop 18783 16379 0 02:40 pts/1 00:00:00 grep NameNode kill -9 16379 kill -9 通过浏览器访问：http://192.168.1.212:50070 NameNode ‘h212:9000‘ (active) 这个时候hadoop-server2上的NameNode变成了active 这个时候hadoop-server1的网页刷新后 无显示处于宕机状态 在执行命令： hadoop fs -ls / -rw-r--r-- 3 root supergroup 1926 2015-06-24 15:36 /profile 刚才上传的文件依然存在！！！ 手动启动那个挂掉的NameNode sbin/hadoop-daemon.sh start namenode 通过浏览器访问：http://192.168.1.24:50070 NameNode ‘h24:9000‘ (standby) 验证YARN： 运行一下hadoop提供的demo中的WordCount程序： hadoop jar share/hadoop/mapreduce/hadoop-mapreduce-examples-2.4.1.jar wordcount /profile /out OK，大功告成！！！ 测试集群工作状态的一些指令 ： bin/hdfs dfsadmin -report 查看hdfs的各节点状态信息 bin/hdfs haadmin -getServiceState nn1 获取一个namenode节点的HA状态 sbin/hadoop-daemon.sh start namenode 单独启动一个namenode进程 ./hadoop-daemon.sh start zkfc 单独启动一个zkfc进程 _____________________________________________________________________________ ***************************************************************************** 报错： [[email protected] bin]$ ./zkServer.sh status JMX enabled by default Using config: /usr/local/zookeeper-3.4.5-cdh5.5.2/bin/../conf/zoo.cfg Error contacting service. It is probably not running. 解决办法 [[email protected] bin]$ vim zkServer.sh 在文件最后添加jdk环境变量 export JAVA_HOME=/usr/jdk1.7.0_25 export HADOOP_HOME=/usr/local/hadoop-2.6.0 export PATH=$PATH:$JAVA_HOME/bin:$HADOOP_HOME/bin [[email protected] bin]$ ./zkServer.sh stop JMX enabled by default Using config: /usr/local/zookeeper-3.4.5-cdh5.5.2/bin/../conf/zoo.cfg [[email protected] bin]$ ./zkServer.sh start JMX enabled by default Using config: /usr/local/zookeeper-3.4.5-cdh5.5.2/bin/../conf/zoo.cfg 此时其他节点也要开启 [[email protected] bin]$ ./zkServer.sh status JMX enabled by default Using config: /usr/local/zookeeper-3.4.5-cdh5.5.2/bin/../conf/zoo.cfg Mode: follower [[email protected] bin]$ ./zkServer.sh status JMX enabled by default Using config: /usr/local/zookeeper-3.4.5-cdh5.5.2/bin/../conf/zoo.cfg Mode: leader [[email protected] bin]$ ./zkServer.sh status JMX enabled by default Using config: /usr/local/zookeeper-3.4.5-cdh5.5.2/bin/../conf/zoo.cfg Mode: follower 警告： [[email protected] ~]$ hadoop fs -put WordCount.txt /profile/ 18/06/21 02:56:39 WARN util.NativeCodeLoader: Unable to load native-hadoop library for your platform... using builtin-java classes where applicable 解决方法： [[email protected] hadoop]$ cd /usr/local/hadoop-2.6.0/etc/hadoop [[email protected] hadoop]$ vim log4j.properties 在文件末行添加 log4j.logger.org.apache.hadoop.util.NativeCodeLoader=ERROR 而后配置所有jar包环境变量 wordcount 执行报错 [[email protected] ~]$ hadoop jar wc.jar WordCount /profile/WordCount.txt /outt 18/06/21 04:18:56 INFO client.ConfiguredRMFailoverProxyProvider: Failing over to rm2 18/06/21 04:18:56 INFO retry.RetryInvocationHandler: Exception while invoking getNewApplication of class ApplicationClientProtocolPBClientImpl over rm2 after 1 fail over attempts. Trying to fail over after sleeping for 25441ms. java.net.ConnectException: Call From h24/192.168.1.24 to h25:8032 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:57) at sun.reflect.DelegatingConstructorAccessorImpl.newInstance(DelegatingConstructorAccessorImpl.java:45) at java.lang.reflect.Constructor.newInstance(Constructor.java:526) at org.apache.hadoop.net.NetUtils.wrapWithMessage(NetUtils.java:791) at org.apache.hadoop.net.NetUtils.wrapException(NetUtils.java:731) at org.apache.hadoop.ipc.Client.call(Client.java:1470) at org.apache.hadoop.ipc.Client.call(Client.java:1403) at org.apache.hadoop.ipc.ProtobufRpcEngine$Invoker.invoke(ProtobufRpcEngine.java:230) at com.sun.proxy.$Proxy17.getNewApplication(Unknown Source) at org.apache.hadoop.yarn.api.impl.pb.client.ApplicationClientProtocolPBClientImpl.getNewApplication(ApplicationClientProtocolPBClientImpl.java:217) 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:256) at org.apache.hadoop.io.retry.RetryInvocationHandler.invoke(RetryInvocationHandler.java:104) at com.sun.proxy.$Proxy18.getNewApplication(Unknown Source) at org.apache.hadoop.yarn.client.api.impl.YarnClientImpl.getNewApplication(YarnClientImpl.java:206) at org.apache.hadoop.yarn.client.api.impl.YarnClientImpl.createApplication(YarnClientImpl.java:214) at org.apache.hadoop.mapred.ResourceMgrDelegate.getNewJobID(ResourceMgrDelegate.java:187) at org.apache.hadoop.mapred.YARNRunner.getNewJobID(YARNRunner.java:231) at org.apache.hadoop.mapreduce.JobSubmitter.submitJobInternal(JobSubmitter.java:156) at org.apache.hadoop.mapreduce.Job$10.run(Job.java:1307) at org.apache.hadoop.mapreduce.Job$10.run(Job.java:1304) at java.security.AccessController.doPrivileged(Native Method) at javax.security.auth.Subject.doAs(Subject.java:415) at org.apache.hadoop.security.UserGroupInformation.doAs(UserGroupInformation.java:1671) at org.apache.hadoop.mapreduce.Job.submit(Job.java:1304) at org.apache.hadoop.mapreduce.Job.waitForCompletion(Job.java:1325) at WordCount.main(WordCount.java:83) at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method) at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:57) at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43) at java.lang.reflect.Method.invoke(Method.java:606) at org.apache.hadoop.util.RunJar.run(RunJar.java:221) at org.apache.hadoop.util.RunJar.main(RunJar.java:136) Caused by: java.net.ConnectException: Connection refused at sun.nio.ch.SocketChannelImpl.checkConnect(Native Method) at sun.nio.ch.SocketChannelImpl.finishConnect(SocketChannelImpl.java:708) at org.apache.hadoop.net.SocketIOWithTimeout.connect(SocketIOWithTimeout.java:206) at org.apache.hadoop.net.NetUtils.connect(NetUtils.java:530) at org.apache.hadoop.net.NetUtils.connect(NetUtils.java:494) at org.apache.hadoop.ipc.Client$Connection.setupConnection(Client.java:609) at org.apache.hadoop.ipc.Client$Connection.setupiostreams(Client.java:708) at org.apache.hadoop.ipc.Client$Connection.access$2800(Client.java:370) at org.apache.hadoop.ipc.Client.getConnection(Client.java:1519) at org.apache.hadoop.ipc.Client.call(Client.java:1442) ... 30 more 解决方法：检查/etc/hadoop/中配置文件监控页面的端口是否正确，重启集群即可生效。错误异常解除 ************************************************************************************************** ———————————————————————————————— ![](http://i2.51cto.com/images/blog/201806/24/8ce11da25cce75e64ff5e5cec3834ac5.png?x-oss-process=image/watermark,size_16,text_QDUxQ1RP5Y2a5a6i,color_FFFFFF,t_100,g_se,x_10,y_10,shadow_90,type_ZmFuZ3poZW5naGVpdGk=)![](http://i2.51cto.com/images/blog/201806/24/98d5d47c26ecab2fc8d3c9e3a699ddee.png?x-oss-process=image/watermark,size_16,text_QDUxQ1RP5Y2a5a6i,color_FFFFFF,t_100,g_se,x_10,y_10,shadow_90,type_ZmFuZ3poZW5naGVpdGk=)

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