大数据集群环境搭建之一 hadoop-ha高可用安装

1、如果你使用root用户进行安装。 vi /etc/profile 即可 系统变量

2、如果你使用普通用户进行安装。 vi ~/.bashrc 用户变量

export HADOOP_HOME=/export/servers/hadoop-2.8.5

export PATH=$PATH:$HADOOP_HOME/bin:$HADOOP_HOME/sbin:

同步配置文件

[root@jiang01 servers]# vi /etc/profile

[root@jiang01 servers]#

[root@jiang01 servers]# xrsync.sh /etc/profile

=========== jiang02 : /etc/profile ===========

命令执行成功

=========== jiang03 : /etc/profile ===========

命令执行成功

[root@jiang01 servers]#

刷新配置各个机器配置：

source /etc/profile

修改下面各个配置文件：

<?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>
        <!-- 指定hdfs的nameservice为ns1 -->
    <property>
        <name>fs.defaultFS</name>
        <value>hdfs://myha01/</value>
    </property>
        <!-- 指定hadoop临时目录 -->
    <property>
        <name>hadoop.tmp.dir</name>
        <value>/export/servers/hadoop-2.8./hadoopDatas/tempDatas</value>
    </property>
        <!-- 指定zookeeper地址 -->
    <property>
        <name>ha.zookeeper.quorum</name>
        <value>jiang01:,jiang02:,jiang03:</value>
    </property>
</configuration>

core-site.xml

<?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>
    <!--指定hdfs的nameservice为ns1，需要和core-site.xml中的保持一致 -->
    <property>
        <name>dfs.nameservices</name>
        <value>myha01</value>
    </property>
    <!-- ns1下面有两个NameNode，分别是nn1，nn2 -->
    <property>
        <name>dfs.ha.namenodes.myha01</name>
        <value>nn1,nn2</value>
    </property>
    <!-- nn1的RPC通信地址 -->
    <property>
        <name>dfs.namenode.rpc-address.myha01.nn1</name>
        <value>jiang01:</value>
    </property>
    <!-- nn1的http通信地址 -->
    <property>
        <name>dfs.namenode.http-address.myha01.nn1</name>
        <value>jiang01:</value>
    </property>
    <!-- nn2的RPC通信地址 -->
    <property>
        <name>dfs.namenode.rpc-address.myha01.nn2</name>
        <value>jiang02:</value>
    </property>
    <!-- nn2的http通信地址 -->
    <property>
        <name>dfs.namenode.http-address.myha01.nn2</name>
        <value>jiang02:</value>
    </property>
    <!-- 指定NameNode的元数据在JournalNode上的存放位置 -->
    <property>
        <name>dfs.namenode.shared.edits.dir</name>
        <value>qjournal://jiang01:8485;jiang02:8485;jiang03:8485/myha01</value>
    </property>
    <!-- 指定JournalNode在本地磁盘存放数据的位置 -->
    <property>
        <name>dfs.journalnode.edits.dir</name>
        <value>/opt/hadoop-2.8./journal</value>
    </property>
    <!-- 开启NameNode失败自动切换 -->
    <property>
        <name>dfs.ha.automatic-failover.enabled</name>
        <value>true</value>
    </property>
    <!-- 配置失败自动切换实现方式 -->
    <property>
        <name>dfs.client.failover.proxy.provider.myha01</name>
        <value>org.apache.hadoop.hdfs.server.namenode.ha.ConfiguredFailoverProxyProvider</value>
    </property>
    <!-- 配置隔离机制 -->
    <property>
        <name>dfs.ha.fencing.methods</name>
        <value>sshfence</value>
    </property>
    <!-- 使用隔离机制时需要ssh免登陆 -->
    <property>
        <name>dfs.ha.fencing.ssh.private-key-files</name>
        <value>/root/.ssh/id_dsa</value>
    </property>
</configuration>

hdfs-site.xml

<?xml version="1.0"?>
<!--
  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.
-->
<configuration>
   <!-- Site specific YARN configuration properties -->
<!-- 开启RM高可靠 -->
        <property>
            <name>yarn.resourcemanager.ha.enabled</name>
            <value>true</value>
        </property>
        <!-- 指定RM的cluster id -->
        <property>
            <name>yarn.resourcemanager.cluster-id</name>
            <value>yrc</value>
        </property>
        <!-- 指定RM的名字 -->
        <property>
            <name>yarn.resourcemanager.ha.rm-ids</name>
            <value>rm1,rm2</value>
        </property>
        <!-- 分别指定RM的地址 -->
        <property>
            <name>yarn.resourcemanager.hostname.rm1</name>
            <value>jiang02</value>
        </property>
        <property>
            <name>yarn.resourcemanager.hostname.rm2</name>
            <value>jiang03</value>
        </property>
        <!-- 指定zk集群地址 -->
        <property>
            <name>yarn.resourcemanager.zk-address</name>
            <value>jiang01:,jiang02:,jiang03:</value>
        </property>
        <property>
            <name>yarn.nodemanager.aux-services</name>
            <value>mapreduce_shuffle</value>
        </property>
</configuration>

yarn-site.xml

<?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>
         <!-- 指定mr框架为yarn方式 -->
    <property>
        <name>mapreduce.framework.name</name>
        <value>yarn</value>
    </property>
</configuration>

mapred-site.xml

[root@jiang01 servers]#  hadoop version
Hadoop 2.8.
Subversion https://git-wip-us.apache.org/repos/asf/hadoop.git -r 0b8464d75227fcee2c6e7f2410377b3d53d3d5f8
Compiled by jdu on --10T03:32Z
Compiled with protoc 2.5.
From source with checksum 9942ca5c745417c14e318835f420733
This command was run using /export/servers/hadoop-2.8./share/hadoop/common/hadoop-common-2.8..jar
[root@jiang01 servers]#

查看hadoop版本

启动zk

[root@jiang01 servers]#
[root@jiang01 servers]# xcall.sh jps -l
============= jiang01 : jps -l ============
 org.apache.zookeeper.server.quorum.QuorumPeerMain
 sun.tools.jps.Jps
命令执行成功
============= jiang02 : jps -l ============
 sun.tools.jps.Jps
 org.apache.zookeeper.server.quorum.QuorumPeerMain
命令执行成功
============= jiang03 : jps -l ============
 org.apache.zookeeper.server.quorum.QuorumPeerMain
 sun.tools.jps.Jps
命令执行成功
[root@jiang01 servers]# xcall.sh zkServer.sh status
============= jiang01 : zkServer.sh status ============
ZooKeeper JMX enabled by default
Using config: /export/servers/zookeeper-3.4./bin/../conf/zoo.cfg
Mode: follower
命令执行成功
============= jiang02 : zkServer.sh status ============
ZooKeeper JMX enabled by default
Using config: /export/servers/zookeeper-3.4./bin/../conf/zoo.cfg
Mode: leader
命令执行成功
============= jiang03 : zkServer.sh status ============
ZooKeeper JMX enabled by default
Using config: /export/servers/zookeeper-3.4./bin/../conf/zoo.cfg
Mode: follower
命令执行成功
[root@jiang01 servers]#

启动zk

在你配置的各个journalnode节点启动该进程

[root@jiang01 servers]#
[root@jiang01 servers]# xcall.sh hadoop-daemon.sh start journalnode
============= jiang01 : hadoop-daemon.sh start journalnode ============
starting journalnode, logging to /export/servers/hadoop-2.8./logs/hadoop-root-journalnode-jiang01.out
命令执行成功
============= jiang02 : hadoop-daemon.sh start journalnode ============
starting journalnode, logging to /export/servers/hadoop-2.8./logs/hadoop-root-journalnode-jiang02.out
命令执行成功
============= jiang03 : hadoop-daemon.sh start journalnode ============
starting journalnode, logging to /export/servers/hadoop-2.8./logs/hadoop-root-journalnode-jiang03.out
命令执行成功
[root@jiang01 servers]#

启动journalnode

先选取一个namenode（jiang01）节点进行格式化

[root@jiang01 servers]# hadoop namenode -format

格式化zkfc，只能在nameonde节点进行

主节点上面启动 dfs文件系统：

[root@jiang01 dfs]# start-dfs.sh

jiang002启动yarm

[root@jiang02 mapreduce]# start-yarn.sh
starting yarn daemons
starting resourcemanager, logging to /export/servers/hadoop-2.8./logs/yarn-root-resourcemanager-jiang02.out
jiang03: starting nodemanager, logging to /export/servers/hadoop-2.8./logs/yarn-root-nodemanager-jiang03.out
jiang01: starting nodemanager, logging to /export/servers/hadoop-2.8./logs/yarn-root-nodemanager-jiang01.out
jiang02: starting nodemanager, logging to /export/servers/hadoop-2.8./logs/yarn-root-nodemanager-jiang02.out
[root@jiang02 mapreduce]# 

jiang03启动：resourcemanager

[root@jiang03 hadoopDatas]#  yarn-daemon.sh start resourcemanager
starting resourcemanager, logging to /export/servers/hadoop-2.8./logs/yarn-root-resourcemanager-jiang03.out

hadoop wordcount程序启动：

1  cd /export/servers/hadoop-2.8.5/share/hadoop/mapreduce/

2 生成数据文件：

touch word.txt
echo "hello world" >> word.txt
echo "hello hadoop" >> word.txt
echo "hello hive" >> word.txt

3 创建hadoop 文件目录

hdfs dfs -mkdir -p /work/data/input

4 向hadoop上传数据文件

hdfs dfs -put ./word.txt /work/data/input

5 计算例子

hadoop jar hadoop-mapreduce-examples-2.8..jar wordcount /work/data/input /work/data/output

6 查看结果：

[root@jiang01 mapreduce]# hadoop jar hadoop-mapreduce-examples-2.8..jar wordcount /work/data/input /work/data/output
// :: INFO input.FileInputFormat: Total input files to process :
// :: INFO mapreduce.JobSubmitter: number of splits:
// :: INFO mapreduce.JobSubmitter: Submitting tokens for job: job_1570635804389_0001
// :: INFO impl.YarnClientImpl: Submitted application application_1570635804389_0001
// :: INFO mapreduce.Job: The url to track the job: http://jiang02:8088/proxy/application_1570635804389_0001/
// :: INFO mapreduce.Job: Running job: job_1570635804389_0001
// :: INFO mapreduce.Job: Job job_1570635804389_0001 running in uber mode : false
// :: INFO mapreduce.Job:  map % reduce %
// :: INFO mapreduce.Job:  map % reduce %
// :: INFO mapreduce.Job:  map % reduce %
// :: INFO mapreduce.Job: Job job_1570635804389_0001 completed successfully
// :: INFO mapreduce.Job: Counters:
        File System Counters
                FILE: Number of bytes read=
                FILE: Number of bytes written=
                FILE: Number of read operations=
                FILE: Number of large read operations=
                FILE: Number of write operations=
                HDFS: Number of bytes read=
                HDFS: Number of bytes written=
                HDFS: Number of read operations=
                HDFS: Number of large read operations=
                HDFS: Number of write operations=
        Job Counters
                Launched map tasks=
                Launched reduce tasks=
                Data-local map tasks=
                Total time spent by all maps in occupied slots (ms)=
                Total time spent by all reduces in occupied slots (ms)=
                Total time spent by all map tasks (ms)=
                Total time spent by all reduce tasks (ms)=
                Total vcore-milliseconds taken by all map tasks=
                Total vcore-milliseconds taken by all reduce tasks=
                Total megabyte-milliseconds taken by all map tasks=
                Total megabyte-milliseconds taken by all reduce tasks=
        Map-Reduce Framework
                Map input records=
                Map output records=
                Map output bytes=
                Map output materialized bytes=
                Input split bytes=
                Combine input records=
                Combine output records=
                Reduce input groups=
                Reduce shuffle bytes=
                Reduce input records=
                Reduce output records=
                Spilled Records=
                Shuffled Maps =
                Failed Shuffles=
                Merged Map outputs=
                GC time elapsed (ms)=
                CPU time spent (ms)=
                Physical memory (bytes) snapshot=
                Virtual memory (bytes) snapshot=
                Total committed heap usage (bytes)=
        Shuffle Errors
                BAD_ID=
                CONNECTION=
                IO_ERROR=
                WRONG_LENGTH=
                WRONG_MAP=
                WRONG_REDUCE=
        File Input Format Counters
                Bytes Read=
        File Output Format Counters
                Bytes Written=