CentOS 7下安装集群Hadoop-2.7.3

hostname与/etc/hosts的关系

很过人一提到更改hostname首先就想到修改/etc/hosts文件，认为hostname的配置文件就是/etc/hosts。其实不是的。 hosts文件的作用相当如DNS，提供IP地址到hostname的对应。早期的互联网计算机少，单机hosts文件里足够存放所有联网计算机。不过随着互联网的发展，这就远远不够了。于是就出现了分布式的DNS系统。由DNS服务器来提供类似的IP地址到域名的对应。具体可以man hosts。 Linux系统在向DNS服务器发出域名解析请求之前会查询/etc/hosts文件，如果里面有相应的记录，就会使用hosts里面的记录。/etc/hosts文件通常里面包含这一条记录 

转至 https://my.oschina.net/xhhuang/blog/807914

一、硬件环境

我使用的硬件是云创的一个minicloud设备。由三个节点（每个节点8GB内存+128GB SSD+3块3TB SATA）和一个千兆交换机组成。

二、安装前准备

1.在CentOS 7下新建hadoop用户，官方推荐的是hadoop、mapreduce、yarn分别用不同的用户安装，这里我为了省事就全部在hadoop用户下安装了。

2.下载安装包：

1）JDK：jdk-8u112-linux-x64.rpm

下载地址：http://www.oracle.com/technetwork/java/javase/downloads/jdk8-downloads-2133151.html
2）Hadoop-2.7.3：hadoop-2.7.3.tar.gz

下载地址：http://archive.apache.org/dist/hadoop/common/stable2/
3.卸载CentOS 7自带的OpenJDK（root权限下）

1）首先查看系统已有的openjdk

rpm -qa|grep jdk

看到如下结果：

[hadoop@localhost Desktop]$ rpm -qa|grep jdkjava-1.7.0-openjdk-1.7.0.111-2.6.7.2.el7_2.x86_64java-1.8.0-openjdk-headless-1.8.0.101-3.b13.el7_2.x86_64java-1.8.0-openjdk-1.8.0.101-3.b13.el7_2.x86_64java-1.7.0-openjdk-headless-1.7.0.111-2.6.7.2.el7_2.x86_64

2）卸载上述找到的openjdk包

yum -y remove java-1.7.0-openjdk-1.7.0.111-2.6.7.2.el7_2.x86_64yum -y remove java-1.8.0-openjdk-headless-1.8.0.101-3.b13.el7_2.x86_64yum -y remove java-1.8.0-openjdk-1.8.0.101-3.b13.el7_2.x86_64yum -y remove java-1.7.0-openjdk-headless-1.7.0.111-2.6.7.2.el7_2.x86_64

4.安装Oracle JDK（root权限下）

rpm -ivh jdk-8u112-linux-x64.rpm

安装完毕后，jdk的路径为/usr/java/jdk1.8.0_112

接着将安装的jdk的路径添加至系统环境变量中：

vi /etc/profile

在文件末尾加上如下内容：

export JAVA_HOME=/usr/java/jdk1.8.0_112export JRE_HOME=/usr/java/jdk1.8.0_112/jreexport PATH=$PATH:$JAVA_HOME/bin:$JRE_HOME/binexport CLASSPATH=.:$JAVA_HOME/lib/dt.jar:$JAVA_HOME/lib/tools.jar

关闭profile文件，执行下列命令使配置生效：

source /etc/profile

此时我们就可以通过java -version命令检查jdk路径是否配置成功，如下所示：

[root@localhost jdk1.8.0_112]# java -versionjava version "1.8.0_112"Java(TM) SE Runtime Environment (build 1.8.0_112-b15)Java HotSpot(TM) 64-Bit Server VM (build 25.112-b15, mixed mode)[root@localhost jdk1.8.0_112]#

5.关闭防火墙（root权限下）

执行下述命令关闭防火墙：

systemctl stop firewalld.service  systemctl disable firewalld.service

在终端效果如下：

[root@localhost Desktop]# systemctl stop firewalld.service [root@localhost Desktop]# systemctl disable firewalld.serviceRemoved symlink /etc/systemd/system/dbus-org.fedoraproject.FirewallD1.service.Removed symlink /etc/systemd/system/basic.target.wants/firewalld.service.[root@localhost Desktop]#

6.修改主机名并配置相关网络（root权限下）

1）修改主机名

在master主机上

hostnamectl set-hostname Master

在slave1主机上

hostnamectl set-hostname slave1

在slave2主机上

hostnamectl set-hostname slave2

2）配置网络

以master主机为例，演示如何配置静态网络及host文件。

我的机器每个节点有两块网卡，我配置其中一块网卡为静态IP作为节点内部通信使用。

vi /etc/sysconfig/network-scripts/ifcfg-enp7s0

（注：我的master机器上要配置的网卡名称为ifcfg-enp7s0）

ifcfg-enp7s0原始内容如下：

TYPE=EthernetBOOTPROTO=dhcpDEFROUTE=yesPEERDNS=yesPEERROUTES=yesIPV4_FAILURE_FATAL=noIPV6INIT=yesIPV6_AUTOCONF=yesIPV6_DEFROUTE=yesIPV6_PEERDNS=yesIPV6_PEERROUTES=yesIPV6_FAILURE_FATAL=noNAME=enp7s0UUID=914595f1-e6f9-4c9b-856a-c4bd79ffe987DEVICE=enp7s0ONBOOT=no

修改为：

TYPE=EthernetONBOOT=yesDEVICE=enp7s0UUID=914595f1-e6f9-4c9b-856a-c4bd79ffe987BOOTPROTO=staticIPADDR=59.71.229.189GATEWAY=59.71.229.254DEFROUTE=yesIPV6INIT=noIPV4_FAILURE_FATAL=yes

3）修改/etc/hosts文件

vi /etc/hosts

加入以下内容：

59.71.229.189 master59.71.229.190 slave159.71.229.191 slave2

为集群中所有节点执行上述的网络配置及hosts文件配置。

7.配置集群节点SSH免密码登录（hadoop权限下）

这里我为了方便，是配置的集群中任意节点能够SSH免密码登录到集群其他任意节点。具体步骤如下：

1）对于每一台机器，在hadoop用户下执行以下指令：

ssh-keygen -t rsa -P ''

直接按Enter到底。

2）对于每台机器，首先将自己的公钥加到authorized_keys中，保证ssh localhost无密码登录：

cat id_rsa.pub >> authorized_keys

3）然后将自己的公钥添加至其他每台机器的authorized_keys中，在此过程中需要输入其他机器的密码：

master：scp /home/hadoop/.ssh/id_rsa.pub hadoop@slave1:/home/hadoop/.ssh/id_rsa_master.pubscp /home/hadoop/.ssh/id_rsa.pub hadoop@slave2:/home/hadoop/.ssh/id_rsa_master.pubslave1：scp /home/hadoop/.ssh/id_rsa.pub hadoop@master:/home/hadoop/.ssh/id_rsa_slave1.pubscp /home/hadoop/.ssh/id_rsa.pub hadoop@slave2:/home/hadoop/.ssh/id_rsa_slave1.pubslave2：scp /home/hadoop/.ssh/id_rsa.pub hadoop@master:/home/hadoop/.ssh/id_rsa_slave2.pubscp /home/hadoop/.ssh/id_rsa.pub hadoop@slave1:/home/hadoop/.ssh/id_rsa_slave2.pub

4）分别进每一台主机的/home/hadoop/.ssh/目录下，将除本机产生的公钥（id_rsa.pub）之外的其他公钥使用cat命令添加至authorized_keys中。添加完毕之后使用chmod命令给authorized_keys文件设置权限，然后使用rm命令删除所有的公钥：

master：cat id_rsa_slave1.pub >> authorized_keyscat id_rsa_slave2.pub >> authorized_keyschmod 600 authorized_keysrm id_rsa*.pubslave1：cat id_rsa_master.pub >> authorized_keyscat id_rsa_slave2.pub >> authorized_keyschmod 600 authorized_keysrm id_rsa*.pubslave2：cat id_rsa_master.pub >> authorized_keyscat id_rsa_slave1.pub >> authorized_keyschmod 600 authorized_keysrm id_rsa*.pub

完成上述步骤，就可以实现从任意一台机器通过ssh命令免密码登录任意一台其他机器了。

三、安装和配置Hadoop（下述步骤在hadoop用户下执行）

1.将hadoop-2.7.3.tar.gz文件解压至/home/hadoop/目录下（在本文档中，文件所在地是hadoop账户下桌面上）可通过下述命令先解压至文件所在地：

tar -zxvf hadoop-2.7.3.tar.gz

然后将解压的文件hadoop-2.7.3所有内容拷贝至/home/hadoop目录下，拷贝之后删除文件所在地的hadoop文件夹：

cp -r /home/hadoop/Desktop/hadoop-2.7.3 /home/hadoop/

2.具体配置过程：

1）在master上，首先/home/hadoop/目录下创建以下目录：

mkdir -p /home/hadoop/hadoopdir/namemkdir -p /home/hadoop/hadoopdir/datamkdir -p /home/hadoop/hadoopdir/tempmkdir -p /home/hadoop/hadoopdir/logsmkdir -p /home/hadoop/hadoopdir/pids

2）然后通过scp命令将hadoopdir目录复制至其他节点：

scp -r /home/hadoop/hadoopdir hadoop@slave1:/home/hadoop/scp -r /home/hadoop/hadoopdir hadoop@slave2:/home/hadoop/

3）进入/home/hadoop/hadoop-2.7.3/etc/hadoop目录下，修改以下文件：

hadoop-env.sh：export JAVA_HOME=/usr/java/jdk1.8.0_112export HADOOP_LOG_DIR=/home/hadoop/hadoopdir/logsexport HADOOP_PID_DIR=/home/hadoop/hadoopdir/pidsmapred-env.sh：export JAVA_HOME=/usr/java/jdk1.8.0_112export HADOOP_MAPRED_LOG_DIR=/home/hadoop/hadoopdir/logsexport HADOOP_MAPRED_PID_DIR=/home/hadoop/hadoopdir/pidsyarn-env.sh：export JAVA_HOME=/usr/java/jdk1.8.0_112YARN_LOG_DIR=/home/hadoop/hadoopdir/logsSlaves文件：#localhostslave1slave2

（注意：如果slaves文件里面不注释localhost，意思是把本机也作为一个DataNode节点）

core-site.xml：<configuration>    <property>        <name>fs.defaultFS</name>        <value>hdfs://master:9000</value>       </property>    <property>        <name>io.file.buffer.size</name>        <value>131072</value>    </property>    <property>        <name>hadoop.tmp.dir</name>        <value>file:///home/hadoop/hadoopdir/temp</value>    </property></configuration>hdfs-site.xml：<configuration>    <property>        <name>dfs.namenode.name.dir</name>        <value>file:///home/hadoop/hadoopdir/name</value>    </property>    <property>        <name>dfs.datanode.data.dir</name>        <value>file:///home/hadoop/hadoopdir/data</value>    </property>    <property>        <name>dfs.replication</name>        <value>2</value>    </property>    <property>        <name>dfs.blocksize</name>        <value>64m</value>    </property>    <property>        <name>dfs.namenode.secondary.http-address</name>        <value>master:9001</value>    </property>    <property>        <name>dfs.webhdfs.enabled</name>        <value>true</value>    </property></configuration>mapred-site.xml：cp mapred-site.xml.template mapred-site.xmlvi mapred-site.xml<configuration>    <property>        <name>mapreduce.framework.name</name>        <value>yarn</value>        <final>true</final>    </property>    <property>        <name>mapreduce.jobhistory.address</name>        <value>master:10020</value>    </property>    <property>        <name>mapreduce.jobtracker.http.address</name>        <value>master:50030</value>    </property>    <property>        <name>mapred.job.tracker</name>        <value>http://master:9001</value>    </property>    <property>        <name>mapreduce.jobhistory.webapp.address</name>        <value>master:19888</value>    </property></configuration>yarn-site.xml：<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.hostname</name>    <value>master</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.address</name>    <value>master:8032</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>

4）master机器下，将/home/hadoop/hadoop-2.7.3目录里面所有内容拷贝至其他节点

scp -r /home/hadoop/hadoop-2.7.3 hadoop@slave1:/home/hadoop/scp -r /home/hadoop/hadoop-2.7.3 hadoop@slave2:/home/hadoop/

5）进入/home/hadoop/hadoop-2.7.3/bin目录，格式化文件系统：

./hdfs namenode -format

格式化文件系统会产生一系列的终端输出，在输出最后几行看到STATUS=0表示格式化成功，如果格式化失败请详细查看日志确定错误原因。
下面是我的错误和解决方法：

17/10/26 19:44:34 INFO ipc.Client: Retrying connect to server: slave2/192.168.84.202:8485. Already tried 7 time(s); retry policy is RetryUpToMaximumCountWithFixedSleep(maxRetries=10, sleepTime=1000 MILLISECONDS)17/10/26 19:44:34 INFO ipc.Client: Retrying connect to server: slave3/192.168.84.203:8485. Already tried 7 time(s); retry policy is RetryUpToMaximumCountWithFixedSleep(maxRetries=10, sleepTime=1000 MILLISECONDS)17/10/26 19:44:34 INFO ipc.Client: Retrying connect to server: slave1/192.168.84.201:8485. Already tried 7 time(s); retry policy is RetryUpToMaximumCountWithFixedSleep(maxRetries=10, sleepTime=1000 MILLISECONDS)17/10/26 19:44:35 INFO ipc.Client: Retrying connect to server: slave2/192.168.84.202:8485. Already tried 8 time(s); retry policy is RetryUpToMaximumCountWithFixedSleep(maxRetries=10, sleepTime=1000 MILLISECONDS)17/10/26 19:44:35 INFO ipc.Client: Retrying connect to server: slave3/192.168.84.203:8485. Already tried 8 time(s); retry policy is RetryUpToMaximumCountWithFixedSleep(maxRetries=10, sleepTime=1000 MILLISECONDS)17/10/26 19:44:35 INFO ipc.Client: Retrying connect to server: slave1/192.168.84.201:8485. Already tried 8 time(s); retry policy is RetryUpToMaximumCountWithFixedSleep(maxRetries=10, sleepTime=1000 MILLISECONDS)17/10/26 19:44:36 INFO ipc.Client: Retrying connect to server: slave2/192.168.84.202:8485. Already tried 9 time(s); retry policy is RetryUpToMaximumCountWithFixedSleep(maxRetries=10, sleepTime=1000 MILLISECONDS)17/10/26 19:44:36 WARN namenode.NameNode: Encountered exception during format: org.apache.hadoop.hdfs.qjournal.client.QuorumException: Unable to check if JNs are ready for formatting. 1 exceptions thrown:192.168.84.202:8485: Call From master/192.168.84.200 to slave2:8485 failed on connection exception: java.net.ConnectException: Connection refused; For more details see:  http://wiki.apache.org/hadoop/ConnectionRefused    at org.apache.hadoop.hdfs.qjournal.client.QuorumException.create(QuorumException.java:81)    at org.apache.hadoop.hdfs.qjournal.client.QuorumCall.rethrowException(QuorumCall.java:223)    at org.apache.hadoop.hdfs.qjournal.client.QuorumJournalManager.hasSomeData(QuorumJournalManager.java:232)    at org.apache.hadoop.hdfs.server.common.Storage.confirmFormat(Storage.java:901)    at org.apache.hadoop.hdfs.server.namenode.FSImage.confirmFormat(FSImage.java:184)    at org.apache.hadoop.hdfs.server.namenode.NameNode.format(NameNode.java:988)    at org.apache.hadoop.hdfs.server.namenode.NameNode.createNameNode(NameNode.java:1434)    at org.apache.hadoop.hdfs.server.namenode.NameNode.main(NameNode.java:1559)17/10/26 19:44:36 INFO ipc.Client: Retrying connect to server: slave1/192.168.84.201:8485. Already tried 9 time(s); retry policy is RetryUpToMaximumCountWithFixedSleep(maxRetries=10, sleepTime=1000 MILLISECONDS)17/10/26 19:44:36 INFO ipc.Client: Retrying connect to server: slave3/192.168.84.203:8485. Already tried 9 time(s); retry policy is RetryUpToMaximumCountWithFixedSleep(maxRetries=10, sleepTime=1000 MILLISECONDS)17/10/26 19:44:36 ERROR namenode.NameNode: Failed to start namenode.org.apache.hadoop.hdfs.qjournal.client.QuorumException: Unable to check if JNs are ready for formatting. 1 exceptions thrown:192.168.84.202:8485: Call From master/192.168.84.200 to slave2:8485 failed on connection exception: java.net.ConnectException: Connection refused; For more details see:  http://wiki.apache.org/hadoop/ConnectionRefused    at org.apache.hadoop.hdfs.qjournal.client.QuorumException.create(QuorumException.java:81)    at org.apache.hadoop.hdfs.qjournal.client.QuorumCall.rethrowException(QuorumCall.java:223)    at org.apache.hadoop.hdfs.qjournal.client.QuorumJournalManager.hasSomeData(QuorumJournalManager.java:232)    at org.apache.hadoop.hdfs.server.common.Storage.confirmFormat(Storage.java:901)    at org.apache.hadoop.hdfs.server.namenode.FSImage.confirmFormat(FSImage.java:184)    at org.apache.hadoop.hdfs.server.namenode.NameNode.format(NameNode.java:988)    at org.apache.hadoop.hdfs.server.namenode.NameNode.createNameNode(NameNode.java:1434)    at org.apache.hadoop.hdfs.server.namenode.NameNode.main(NameNode.java:1559)17/10/26 19:44:36 INFO util.ExitUtil: Exiting with status 117/10/26 19:44:36 INFO namenode.NameNode: SHUTDOWN_MSG: /************************************************************SHUTDOWN_MSG: Shutting down NameNode at master/192.168.84.200************************************************************/

6）进入/home/hadoop/hadoop-2.7.3/sbin目录：

./start-dfs.sh./start-yarn.sh

上述命令就启动了hdfs和yarn。hadoop集群就跑起来了，如果要关闭，在sbin目录下执行以下命令：

./stop-yarn.sh./stop-dfs.sh

7）HDFS启动示例

执行start-dfs.sh之后，可以在master:50070网页上看到如下结果，可以看到集群信息和datanode相关信息：

执行start-yarn.sh之后，可以在master:8088网页上看到如下结果，可以看到集群信息相关信息：