大数据-hadoop HA集群搭建

一、安装hadoop、HA及配置journalnode

实现namenode HA

实现resourcemanager HA

namenode节点之间通过journalnode同步元数据

首先下载需要版本的hadoop，我用的版本是hadoop-2.9.1

安装到5台机器上

master1 master2上安装namenode

master1 master2上配置resourcemanager

slave1 slave2 slave3上安装datanode

slave1 slave2 slave3上配置journalnode

slave1 slave2 slave3上配置nodemanager

1、将文件下载到、opt/workspace/目录下

2、解压缩

tar -zxvf hadoop-2.9..tar.gz

3、进行文件配置

对hadoop-env.sh mapred-site.xml hdfs-site.xml yarn-site.xml core-site.xml slaves进行修改

（1）对core-site.xml进行配置

<?xml version="1.0" encoding="UTF-8"?>

<?xml-stylesheet type="text/xsl" href="configuration.xsl"?>

<!--

  Licensed under the Apache License, Version 2.0 (the "License");

  you may not use this file except in compliance with the License.

  You may obtain a copy of the License at

    http://www.apache.org/licenses/LICENSE-2.0

  Unless required by applicable law or agreed to in writing, software

  distributed under the License is distributed on an "AS IS" BASIS,

  WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.

  See the License for the specific language governing permissions and

  limitations under the License. See accompanying LICENSE file.

-->

<!-- Put site-specific property overrides in this file. -->

<configuration>

<property>

        <name>hadoop.tmp.dir</name>

        <value>/opt/hadoop/tmp</value>

        <description>Abase for other temporary directories.</description>

</property>

<property>

        <name>fs.default.name</name>

        <value>hdfs://hadoop-test</value>

</property>

<property>

       <name>io.file.buffer.size</name>

       <value></value>

</property>

<!-- 指定zookeeper地址 -->

<property>

        <name>ha.zookeeper.quorum</name>

        <value>master1:,master2:,slave1:,slave2:,slave3:</value>

</property>

<!-- hadoop链接zookeeper的超时时长设置 -->

<property>

        <name>ha.zookeeper.session-timeout.ms</name>

        <value></value>

        <description>ms</description>

</property>

<property>

  　　　　<name>hadoop.native.lib</name>

  　　　　<value>false</value>

  　　　　<description>Should native hadoop libraries, if present, be used.</description>

</property>

<property>

  　　　　<name>hadoop.proxyuser.root.hosts</name>

  　　　　<value>*</value>

</property>

<property>

  　　　　<name>hadoop.proxyuser.root.groups</name>

  　　　　<value>*</value>

</property>

</configuration>

（2）对hadoop-env.sh进行配置添加

export JAVA_HOME=/opt/workspace/jdk1.8
有需要时才添加端口，不是22默认端口

export HADOOP_SSH_OPTS="-p 61333"

（3）对mapred-site.xml进行配置

<?xml version="1.0"?>

<?xml-stylesheet type="text/xsl" href="configuration.xsl"?>

<!--

  Licensed under the Apache License, Version 2.0 (the "License");

  you may not use this file except in compliance with the License.

  You may obtain a copy of the License at

    http://www.apache.org/licenses/LICENSE-2.0

  Unless required by applicable law or agreed to in writing, software

  distributed under the License is distributed on an "AS IS" BASIS,

  WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.

  See the License for the specific language governing permissions and

  limitations under the License. See accompanying LICENSE file.

-->

<!-- Put site-specific property overrides in this file. -->

<configuration>

<!-- MR YARN Application properties -->

<property>

     <name>mapreduce.framework.name</name>

     <value>yarn</value>

     <description>The runtime framework for executing MapReduce jobs. Can be one of local, classic or yarn.</description>

</property>

<!-- jobhistory properties -->

<property>

     <name>mapreduce.jobhistory.address</name>

     <value>159.226.48.203:</value>

     <description>MapReduce JobHistory Server IPC host:port</description>

</property>

<property>

     <name>mapreduce.jobhistory.webapp.address</name>

     <value>159.226.48.203:</value>

     <description>MapReduce JobHistory Server Web UI host:port</description>

</property>

<property>

        <name>mapreduce.task.io.sort.mb</name>

        <value></value>

</property>

<property>

        <name>mapreduce.reduce.shuffle.parallelcopies</name>

        <value></value>

</property>

<property>

        <name>mapred.child.java.opts</name>

        <value>-Xmx1024m</value>

</property>

<!--MR ApplicationMaster -->

<property>

        <name>yarn.app.mapreduce.am.resource.mb</name>

        <value></value>

</property>

<property>

        <name>yarn.app.mapreduce.am.command-opts</name>

        <value>-Xmx2867m</value>

</property>

</configuration>

（4）对hdfs-site.xml进行配置

<?xml version="1.0" encoding="UTF-8"?>

<?xml-stylesheet type="text/xsl" href="configuration.xsl"?>

<!--

  Licensed under the Apache License, Version 2.0 (the "License");

  you may not use this file except in compliance with the License.

  You may obtain a copy of the License at

    http://www.apache.org/licenses/LICENSE-2.0

  Unless required by applicable law or agreed to in writing, software

  distributed under the License is distributed on an "AS IS" BASIS,

  WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.

  See the License for the specific language governing permissions and

  limitations under the License. See accompanying LICENSE file.

-->

<!-- Put site-specific property overrides in this file. -->

<configuration>

<property>

     <name>dfs.nameservices</name>

     <value>hadoop-test</value>

     <description>

           Comma-separated list of nameservices.

     </description>

</property>

<property>

     <name>dfs.ha.namenodes.hadoop-test</name>

     <value>nn1,nn2</value>

     <description>

           The prefix for a given nameservice, contains a comma-separated

           list of namenodes for a given nameservice (eg EXAMPLENAMESERVICE).

     </description>

</property>

<property>

      <name>dfs.namenode.rpc-address.hadoop-test.nn1</name>

      <value>master1:</value>

      <description>

             RPC address for nomenode1 of hadoop-test

      </description>

</property>

<property>

      <name>dfs.namenode.rpc-address.hadoop-test.nn2</name>

      <value>master2:</value>

      <description>

             RPC address for nomenode2 of hadoop-test

      </description>

</property>

<property>

      <name>dfs.namenode.http-address.hadoop-test.nn1</name>

      <value>master1:</value>

      <description>

             The address and the base port where the dfs namenode1 web ui will listen on.

      </description>

</property>

<property>

      <name>dfs.namenode.http-address.hadoop-test.nn2</name>

      <value>master2:</value>

      <description>

             The address and the base port where the dfs namenode2 web ui will listen on.

      </description>

</property>

<!-- 启用webhdfs -->

<property>

       <name>dfs.webhdfs.enabled</name>

       <value>true</value>

</property>

<property>

      <name>dfs.namenode.name.dir</name>

      <value>/opt/hadoop/dfs/name</value>

      <description>Path on the local filesystem where theNameNode stores the namespace and transactions logs persistently.</description>

</property>

  <!--配置journalnode-->

<property>

  <name>dfs.namenode.shared.edits.dir</name>

  <value>qjournal://slave1:8485;slave2:8485;slave3:8485/hadoop-test</value>

  <description>A directory on shared storage between the multiple namenodes

  in an HA cluster. This directory will be written by the active and read

  by the standby in order to keep the namespaces synchronized. This directory

  does not need to be listed in dfs.namenode.edits.dir above. It should be

  left empty in a non-HA cluster.

  </description>

</property>

<property>

   　　<name>dfs.datanode.data.dir</name>

   　　<value>/opt/hadoop/dfs/data</value>

   　　<description>Comma separated list of paths on the localfilesystem of a DataNode where it should store its blocks.</description>

</property>

<property>

   　　<name>dfs.replication</name>

   　　<value></value>

</property>

<property>

  　　<name>dfs.ha.automatic-failover.enabled</name>

  　　<value>true</value>

  　　<description>

    　　Whether automatic failover is enabled. See the HDFS High

    　　Availability documentation for details on automatic HA

    　　configuration.

  　　</description>

</property>

<property>

  　　<name>dfs.journalnode.edits.dir</name>

  　　<value>/opt/hadoop/dfs/journalnode</value>

</property>

<!-- 开启NameNode失败自动切换 -->

<!-- 配置失败自动切换实现方式 -->

<property>

        <name>dfs.client.failover.proxy.provider.hadoop-test</name>

        <value>org.apache.hadoop.hdfs.server.namenode.ha.ConfiguredFailoverProxyProvider</value>

</property>

<!-- 配置隔离机制方法，多个机制用换行分割，即每个机制暂用一行 -->

<property>

        <name>dfs.ha.fencing.methods</name>

        <value>

            sshfence

            shell(/bin/true)

        </value>

</property>

<!-- 使用sshfence隔离机制时需要ssh免登陆 -->

<property>

        <name>dfs.ha.fencing.ssh.private-key-files</name>

        <value>/root/hadoop/.ssh/id_rsa</value>

</property>

<!-- 配置sshfence隔离机制超时时间 -->

<property>

        <name>dfs.ha.fencing.ssh.connect-timeout</name>

        <value></value>

</property>

<property>

        <name>ha.failover-controller.cli-check.rpc-timeout.ms</name>

        <value></value>

</property>

<property>

    　　<name>dfs.permissions</name>

    　　<value>false</value>

 </property>

</configuration>

（5）对yarn-site.xml进行配置（注意修改下面第一段代码，不同的master需要修改value值）

<property>

　　<name>yarn.resourcemanager.ha.id</name>

　　<value>rm2</value>

　　<description>If we want to launch more than one RM in single node,we need this configuration</description>

</property>

<?xml version="1.0"?>

<configuration>

<!--rm失联后重新链接的时间-->

<property>

　　<name>yarn.resourcemanager.connect.retry-interval.ms</name>

　　<value></value>

</property>

<!--开启resourcemanagerHA,默认为false-->

<property>

　　<name>yarn.resourcemanager.ha.enabled</name>

　　<value>true</value>

</property>

<!--配置resourcemanager-->

<property>

　　<name>yarn.resourcemanager.ha.rm-ids</name>

　　<value>rm1,rm2</value>

</property>

<property>

　　<name>ha.zookeeper.quorum</name>

　　<value>master1:,master2:,slave1:,slave2:,slave3:</value>

</property>

<!--开启故障自动切换-->

<property>

　　<name>yarn.resourcemanager.ha.automatic-failover.enabled</name>

　　<value>true</value>

</property>

<property>

　　<name>yarn.resourcemanager.hostname.rm1</name>

　　<value>master1</value>

</property>

<property>

　　<name>yarn.resourcemanager.hostname.rm2</name>

　　<value>master2</value>

</property>

<!--

     在hadoop001上配置rm1,在hadoop002上配置rm2,

注意：一般都喜欢把配置好的文件远程复制到其它机器上，但这个在YARN的另一个机器上一定要修改

-->

<property>

　　<name>yarn.resourcemanager.ha.id</name>

　　<value>rm2</value>

　　<description>If we want to launch more than one RM in single node,we need this configuration</description>

</property>

<!--开启自动恢复功能-->

<property>

　　<name>yarn.resourcemanager.recovery.enabled</name>

　　<value>true</value>

</property>

<!--配置与zookeeper的连接地址-->

<property>

　　<name>yarn.resourcemanager.zk-state-store.address</name>

　　<value>master1:,master2:,slave1:,slave2:,slave3:</value>

</property>

<property>

　　<name>yarn.resourcemanager.store.class</name>

　　<value>org.apache.hadoop.yarn.server.resourcemanager.recovery.ZKRMStateStore</value>

</property>

<property>

　　<name>yarn.resourcemanager.zk-address</name>

　　<value>master1:,master2:,slave1:,slave2:,slave3:</value>

</property>

<property>

　　<name>yarn.resourcemanager.cluster-id</name>

　　<value>appcluster-yarn</value>

</property>

<!--schelduler失联等待连接时间-->

<property>

　　<name>yarn.app.mapreduce.am.scheduler.connection.wait.interval-ms</name>

　　<value></value>

</property>

<!--配置rm1-->

<property>

　　<name>yarn.resourcemanager.address.rm1</name>

　　<value>master1:</value>

</property>

<property>

　　<name>yarn.resourcemanager.scheduler.address.rm1</name>

　　<value>master1:</value>

</property>

<property>

　　<name>yarn.resourcemanager.webapp.address.rm1</name>

　　<value>159.226.48.202:</value>

</property>

<property>

　　<name>yarn.resourcemanager.resource-tracker.address.rm1</name>

　　<value>master1:</value>

</property>

<property>

　　<name>yarn.resourcemanager.admin.address.rm1</name>

　　<value>master1:</value>

</property>

<property>

  <name>yarn.resourcemanager.ha.admin.address.rm1</name>

  <value>master1:</value>

</property>

<!--配置rm2-->

<property>

  <name>yarn.resourcemanager.address.rm2</name>

  <value>master2:</value>

</property>

<property>

  <name>yarn.resourcemanager.scheduler.address.rm2</name>

  <value>master2:</value>

</property>

<property>

  <name>yarn.resourcemanager.webapp.address.rm2</name>

  <value>159.226.48.203:</value>

</property>

<property>

  <name>yarn.resourcemanager.resource-tracker.address.rm2</name>

  <value>master2:</value>

</property>

<property>

  <name>yarn.resourcemanager.admin.address.rm2</name>

  <value>master2:</value>

</property>

<property>

  <name>yarn.resourcemanager.ha.admin.address.rm2</name>

  <value>master2:</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.nodemanager.local-dirs</name>

  <value>/opt/workspace/hadoop/yarn/local</value>

</property>

<property>

  <name>yarn.nodemanager.log-dirs</name>

  <value>/opt/workspace/hadoop/yarn/log</value>

</property>

<property>

  <name>mapreduce.shuffle.port</name>

  <value></value>

</property>

<!--故障处理类-->

<property>

  <name>yarn.client.failover-proxy-provider</name>

  <value>org.apache.hadoop.yarn.client.ConfiguredRMFailoverProxyProvider</value>

</property>

<property>

<name>yarn.resourcemanager.ha.automatic-failover.zk-base-path</name>

  <value>/yarn-leader-election</value>

  <description>Optionalsetting.Thedefaultvalueis/yarn-leader-election</description>

</property>

<!--参数解释：启用的资源调度器主类。目前可用的有FIFO、Capacity Scheduler和Fair Scheduler。 -->

<!--<property>

    <description>The class to use as the resource scheduler.</description>

    <name>yarn.resourcemanager.scheduler.class</name>

    <value>org.apache.hadoop.yarn.server.resourcemanager.scheduler.fair.FairScheduler</value>

</property>

<property>

    <description>fair-scheduler conf location</description>

    <name>yarn.scheduler.fair.allocation.file</name>

    <value>${yarn.home.dir}/etc/hadoop/fairscheduler.xml</value>

</property>-->

<property>

    <name>yarn.nodemanager.pmem-check-enabled</name>

    <value>false</value>

</property>

<property>

    <name>yarn.nodemanager.vmem-check-enabled</name>

    <value>false</value>

</property>

<!--参数解释：启用的资源调度器主类。目前可用的有FIFO、Capacity Scheduler和Fair Scheduler。 -->

<property>

    <description>The class to use as the resource scheduler.</description>

    <name>yarn.resourcemanager.scheduler.class</name>

    <value>org.apache.hadoop.yarn.server.resourcemanager.scheduler.capacity.CapacityScheduler</value>

</property>

<!--yarn.scheduler.minimum-allocation-mb/ yarn.scheduler.maximum-allocation-mb

参数解释：单个可申请的最小/最大内存资源量。比如设置为1024和3072，则运行MapRedce作业时，每个Task最少可申请1024MB内存，最多可申请3072MB内存。 -->

<property>

    <description></description>

    <name>yarn.scheduler.minimum-allocation-mb</name>

    <value></value>

</property>

<property>

    <description></description>

    <name>yarn.scheduler.maximum-allocation-mb</name>

    <value></value>

</property>

<!--：单个可申请的最小/最大虚拟CPU个数。比如设置为1和4，则运行MapRedce作业时，每个Task最少可申请1个虚拟CPU，最多可申请4个虚拟CPU。 -->

<property>

    <description></description>

    <name>yarn.scheduler.minimum-allocation-vcores</name>

    <value></value>

</property>

<property>

    <description></description>

    <name>yarn.scheduler.maximum-allocation-vcores</name>

    <value></value>

</property>

<property>

     <description></description>

     <name>yarn.nodemanager.resource.cpu-vcores</name>

     <value></value>

</property>

<property>

     <description></description>

     <name>yarn.nodemanager.resource.memory-mb</name>

     <value></value>

</property>

<property>

        <name>yarn.nodemanager.aux-services</name>

        <value>mapreduce_shuffle</value>

</property>

</configuration>

（6）修改slaves文件

配置完成

二、启动服务

1、首先启动5台服务器的zookeeper服务

cd /opt/workspace/zookeeper/zookeeper-3.4.

bin/zkServer.sh

2、slave1 slave2 slave3 上启动journalnode

[root@slave1 hadoop-2.9.]# sbin/hadoop-daemon.sh start journalnode

[root@slave2 hadoop-2.9.]# sbin/hadoop-daemon.sh start journalnode

[root@slave3 hadoop-2.9.]# sbin/hadoop-daemon.sh start journalnode

3、对master1进行格式化

[root@master1 hadoop-2.9.]# bin/hdfs namenode -format

4、master2进行元数据同步

[root@master2 hadoop-2.9.]# bin/hdfs namenode -bootstrapStandby

5、启动hadoop

[root@master1 hadoop-2.9.]# sbin/start-dfs.sh

6、启动resourcemanager

[root@master1 hadoop-2.9.]# sbin/start-yarn.sh

master2上手动启动resourcemanager

[root@master1 hadoop-2.9.]# sbin/yarn-daemon.sh start resourcemanager

7、成功启动服务后的截图

三、HA功能测试

问题解决：

在进行启动时，出现22端口拒绝访问，因为22端口为默认ssh访问端口，而我们的服务器不是22，所以需要修改一下

在hadoop-env.sh文件中添加

export HADOOP_SSH_OPTS="-p 61333"

防火墙问题：进行操作时需要将机器的防火墙关闭

[root@master1 bin]# systemctl start firewalld.service  #启动firewall

[root@master1 bin]# systemctl stop firewalld.service   #停止firewall

[root@master1 bin]# systemctl disable firewalld.service   #禁止firewall开机启动

参考：https://blog.csdn.net/sinat_25943197/article/details/81906060

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