Hadoop3.1.1

下载

http://archive.apache.org/dist/hadoop/common/hadoop-3.1.1/

上传至服务器/opt/software

解压

[root@server1 servers]# tar -zxvf hadoop-3.1.1.tar.gz -C /opt/servers

 

配置环境变量

[root@server1 ~]# vim /etc/profile

添加环境变量

#HADOOP_HOME
export HADOOP_HOME=/opt/servers/hadoop-3.1.1
export PATH=$PATH:$HADOOP_HOME/bin:$HADOOP_HOME/sbin
source /etc/profile

编辑

hadoop-env.sh

export JAVA_HOME=/opt/module/jdk1.8.0_231

 伪分布式运行模式

core-site.xml

<configuration>
    <!-- hdfs://server1:8020 中server1是主机名 -->
    <property>
        <name>fs.default.name</name>
        <value>hdfs://server1:8020</value>
    </property>
    
    <!-- 临时文件存储目录 -->
    <property>
        <name>hadoop.tmp.dir</name>
        <value>/opt/servers/hadoop-3.1.1/datas/tmp</value>
    </property>
    
    <!-- 缓冲区大小 -->
    <property>
        <name>io.file.buffer.size</name>
        <value>8129</value>
    </property>
    <!-- 开启HDFS垃圾桶机制，删除掉的数据可以从垃圾桶中回收 单位为分钟-->
    <property>
        <name>fs.trash.interval</name>
        <value>10080</value>
    </property>
</configuration>

 hdfs-site.xml

<configuration>
    <property>
        <name>dfs.replication</name>
        <value>1</value>
    </property>
    <property>
        <name>dfs.namenode.http-address</name>
        <value>server1:50070</value>
    </property>
</configuration>

启动集群

格式化NameNode（第一次启动时格式化，以后就不要总格式化）

bin/hdfs namenode -format

启动NameNode

[root@server1 hadoop-3.1.1]# sbin/hadoop-daemon.sh start namenode

启动DataNode

[root@server1 hadoop-3.1.1]# sbin/hadoop-daemon.sh start datanode

查看是否启动成功

[root@server1 hadoop-3.1.1]# jps
8001 Jps
7731 NameNode
7855 DataNode

web端查看HDFS文件系统

http://192.168.238.128:50070

 

 

 

启动YARN并运行MapReduce程序

配置yarn-env.sh

 

配置yarn-site.xml

<configuration>

<!-- Site specific YARN configuration properties -->
<!--Reducer获取数据的方式-->
    <property>
        <name>yarn.nodemanager.aux-services</name>
        <value>mapreduce_shuffle</value>
    </property>
<!--指定YARN的ResourceManager的地址-->
    <property>
        <name>yarn.resourcemanager.hostname</name>
        <value>server1</value>
    </property>

</configuration>

 

配置mapred-site.xml

<configuration>

<!--指定MR运行在YARN上-->
    <property>
        <name>mapreduce.framework.name</name>
        <value>yarn</value>
    </property>
</configuration>

启动集群（启动前必须保证NameNode和DataNode已经启动）

启动ResourceManager

yarn-daemon.sh start resourcemanager

启动NodeManager

yarn-daemon.sh start nodemanager

查看启动情况

[root@server1 hadoop-3.1.1]# jps
7731 NameNode
8660 Jps
8566 NodeManager
8268 ResourceManager
7855 DataNode

YARN的浏览器页面查看

http://192.168.238.128:8088

 

 

 

 

集群配置 

  server1 server2 server3
HDFS

NameNode

DataNode

 DataNode

SecondaryNameNode

DataNode
YARN NodeManager

ResourceManager

NodeManager

 NodeManager

 

 

配置core-site.xml

<configuration>
    <!--指定HDFS中NameNode的地址-->
    <property>
        <name>fs.default.name</name>
        <value>hdfs://server1:8020</value>
    </property>
    
    <!-- 临时文件存储目录 -->
    <property>
        <name>hadoop.tmp.dir</name>
        <value>/opt/servers/hadoop-3.1.1/datas/tmp</value>
    </property>
    
    <!-- 缓冲区大小 -->
    <property>
        <name>io.file.buffer.size</name>
        <value>8129</value>
    </property>
    <!-- 开启HDFS垃圾桶机制，删除掉的数据可以从垃圾桶中回收 单位为分钟-->
    <property>
        <name>fs.trash.interval</name>
        <value>10080</value>
    </property>
</configuration>

配置hadoop-env.sh

export JAVA_HOME=/opt/module/jdk1.8.0_231

配置hdfs-site.xml

<configuration>
    <property>
        <name>dfs.replication</name>
        <value>3</value>
    </property>
    <property>
        <name>dfs.namenode.http-address</name>
        <value>server1:50070</value>
    </property>
    <!--指定Hadoop辅助名称节点主机配置-->
    <property>
        <name>dfs.namenode.secondary.http-address</name>
        <value>server3:50090</value>
    </property>
</configuration>

配置yarn-site.xm

<configuration>

<!-- Site specific YARN configuration properties -->
<!--Reducer获取数据的方式-->
    <property>
        <name>yarn.nodemanager.aux-services</name>
        <value>mapreduce_shuffle</value>
    </property>
<!--指定YARN的ResourceManager的地址-->
    <property>
        <name>yarn.resourcemanager.hostname</name>
        <value>server2</value>
    </property>

</configuration>

配置mapred-site.xml

<configuration>

<!--指定MR运行在YARN上-->
    <property>
        <name>mapreduce.framework.name</name>
        <value>yarn</value>
    </property>
    <!-- 历史服务器 -->
    <property>
        <name>mapreduce.jobhistory.address</name>
        <value>server2:10020</value>
    </property>
    <property>
        <name>mapreduce.jobhistory.webapp.address</name>
        <value>server2:19888</value>
    </property>
</configuration>

 

 

编辑

vim /opt/servers/hadoop-3.1.1/etc/hadoop/workers

删除locahost

添加

server1
server2
server3

归档拷贝（在2跟3上执行；可使用集群分发脚本，后文有说明）

[root@server3 servers]# rsync -av server1:/opt/servers/hadoop-3.1.1 /opt/servers

如果不能使用rsync 先安装

[root@server3 servers]# yum install rsync -y

 

格式化集群

[hadoop@server1 ~]# hdfs namenode -format

启动

namenode节点

[hadoop@server1 root]$ start-dfs.sh

yarn节点

[hadoop@server2 root]$ start-yarn.sh
[hadoop@server2 root]$ mr-jobhistory-daemon.sh start historyserver

 关闭

[hadoop@server2 root]$ mr-jobhistory-daemon.sh stop historyserver
[hadoop@server2 root]$ stop-yarn.sh
[hadoop@server1 root]$ stop-dfs.sh

 

 

xsync集群分发脚本（循环复制文件到所有节点的相同目录下）

在/home/hadoop目录下创建bin目录，并在bin目录下xsync创建文件，

[hadoop@server1 ~]$ vim xsync

文件内容如下：

#!/bin/bash
pcount=$#
if((pcount==0)); then
echo no args;
exit;
fi
p1=$1
fname=`basename $p1`
echo fname=$fname
pdir=`cd -P $(dirname $p1); pwd`
echo pdir=$pdir
user=`whoami`
for((host=2; host<4; host++)); do
echo ------------------- server$host --------------
rsync -rvl $pdir/$fname $user@server$host:$pdir
done

（如果后面执行错误 ）

vim xsync进入后， 在底部模式下， 执行:set fileformat=unix后执行:wq保存修改。 然后就可以执行./xsync运行脚本了

复制到所有用户环境变量中

[hadoop@server1 ~]$ sudo cp xsync /bin

使用示例

[hadoop@server1 servers]$ xsync hadoop-3.1.1
fname=hadoop-3.1.1
pdir=/opt/servers
------------------- server1 --------------
sending incremental file list

sent 689,281 bytes  received 2,592 bytes  461,248.67 bytes/sec
total size is 835,950,736  speedup is 1,208.24
------------------- server2 --------------
sending incremental file list
hadoop-3.1.1/datas/tmp/dfs/data/current/VERSION
hadoop-3.1.1/datas/tmp/dfs/data/current/BP-1402719487-192.168.238.128-1575364988262/scanner.cursor
hadoop-3.1.1/datas/tmp/dfs/data/current/BP-1402719487-192.168.238.128-1575364988262/current/VERSION
hadoop-3.1.1/datas/tmp/dfs/name/current/VERSION
hadoop-3.1.1/datas/tmp/dfs/name/current/edits_0000000000000000001-0000000000000000001
hadoop-3.1.1/datas/tmp/dfs/name/current/edits_0000000000000000002-0000000000000000002
hadoop-3.1.1/datas/tmp/dfs/name/current/edits_0000000000000000003-0000000000000000003
hadoop-3.1.1/datas/tmp/dfs/name/current/edits_0000000000000000004-0000000000000000005
hadoop-3.1.1/datas/tmp/dfs/name/current/edits_inprogress_0000000000000000006
hadoop-3.1.1/datas/tmp/dfs/name/current/fsimage_0000000000000000003
hadoop-3.1.1/datas/tmp/dfs/name/current/fsimage_0000000000000000003.md5
hadoop-3.1.1/datas/tmp/dfs/name/current/fsimage_0000000000000000005
hadoop-3.1.1/datas/tmp/dfs/name/current/fsimage_0000000000000000005.md5
hadoop-3.1.1/datas/tmp/dfs/name/current/seen_txid
hadoop-3.1.1/etc/hadoop/mapred-site.xml
hadoop-3.1.1/etc/hadoop/workers
hadoop-3.1.1/etc/hadoop/yarn-site.xml
hadoop-3.1.1/logs/SecurityAuth-hadoop.audit
hadoop-3.1.1/logs/hadoop-hadoop-datanode-server1.log
hadoop-3.1.1/logs/hadoop-hadoop-datanode-server1.out
hadoop-3.1.1/logs/hadoop-hadoop-datanode-server1.out.1
hadoop-3.1.1/logs/hadoop-hadoop-datanode-server1.out.2
hadoop-3.1.1/logs/hadoop-hadoop-datanode-server1.out.3
hadoop-3.1.1/logs/hadoop-hadoop-datanode-server1.out.4
hadoop-3.1.1/logs/hadoop-hadoop-datanode-server1.out.5
hadoop-3.1.1/logs/hadoop-hadoop-namenode-server1.log
hadoop-3.1.1/logs/hadoop-hadoop-namenode-server1.out
hadoop-3.1.1/logs/hadoop-hadoop-namenode-server1.out.1
hadoop-3.1.1/logs/hadoop-hadoop-namenode-server1.out.2
hadoop-3.1.1/logs/hadoop-hadoop-namenode-server1.out.3
hadoop-3.1.1/logs/hadoop-hadoop-namenode-server1.out.4
hadoop-3.1.1/logs/hadoop-hadoop-namenode-server1.out.5
hadoop-3.1.1/logs/hadoop-hadoop-nodemanager-server1.log
hadoop-3.1.1/logs/hadoop-hadoop-nodemanager-server1.out
hadoop-3.1.1/logs/hadoop-hadoop-nodemanager-server1.out.1
hadoop-3.1.1/logs/hadoop-hadoop-nodemanager-server1.out.2
hadoop-3.1.1/logs/hadoop-hadoop-nodemanager-server1.out.3
hadoop-3.1.1/logs/hadoop-hadoop-nodemanager-server1.out.4
hadoop-3.1.1/logs/hadoop-hadoop-nodemanager-server1.out.5
hadoop-3.1.1/logs/hadoop-hadoop-resourcemanager-server1.log
hadoop-3.1.1/logs/hadoop-hadoop-resourcemanager-server1.out
hadoop-3.1.1/logs/hadoop-hadoop-resourcemanager-server1.out.1
hadoop-3.1.1/logs/hadoop-hadoop-resourcemanager-server1.out.2
hadoop-3.1.1/logs/hadoop-hadoop-resourcemanager-server1.out.3
hadoop-3.1.1/logs/hadoop-hadoop-resourcemanager-server1.out.4
hadoop-3.1.1/logs/hadoop-hadoop-resourcemanager-server1.out.5

sent 715,375 bytes  received 39,908 bytes  1,510,566.00 bytes/sec
total size is 835,950,736  speedup is 1,106.80
------------------- server3 --------------
sending incremental file list
hadoop-3.1.1/datas/tmp/dfs/data/current/VERSION
hadoop-3.1.1/datas/tmp/dfs/data/current/BP-1402719487-192.168.238.128-1575364988262/scanner.cursor
hadoop-3.1.1/datas/tmp/dfs/data/current/BP-1402719487-192.168.238.128-1575364988262/current/VERSION
hadoop-3.1.1/datas/tmp/dfs/name/current/VERSION
hadoop-3.1.1/datas/tmp/dfs/name/current/edits_0000000000000000001-0000000000000000001
hadoop-3.1.1/datas/tmp/dfs/name/current/edits_0000000000000000002-0000000000000000002
hadoop-3.1.1/datas/tmp/dfs/name/current/edits_0000000000000000003-0000000000000000003
hadoop-3.1.1/datas/tmp/dfs/name/current/edits_0000000000000000004-0000000000000000005
hadoop-3.1.1/datas/tmp/dfs/name/current/edits_inprogress_0000000000000000006
hadoop-3.1.1/datas/tmp/dfs/name/current/fsimage_0000000000000000003
hadoop-3.1.1/datas/tmp/dfs/name/current/fsimage_0000000000000000003.md5
hadoop-3.1.1/datas/tmp/dfs/name/current/fsimage_0000000000000000005
hadoop-3.1.1/datas/tmp/dfs/name/current/fsimage_0000000000000000005.md5
hadoop-3.1.1/datas/tmp/dfs/name/current/seen_txid
hadoop-3.1.1/etc/hadoop/mapred-site.xml
hadoop-3.1.1/etc/hadoop/workers
hadoop-3.1.1/etc/hadoop/yarn-site.xml
hadoop-3.1.1/logs/SecurityAuth-hadoop.audit
hadoop-3.1.1/logs/hadoop-hadoop-datanode-server1.log
hadoop-3.1.1/logs/hadoop-hadoop-datanode-server1.out
hadoop-3.1.1/logs/hadoop-hadoop-datanode-server1.out.1
hadoop-3.1.1/logs/hadoop-hadoop-datanode-server1.out.2
hadoop-3.1.1/logs/hadoop-hadoop-datanode-server1.out.3
hadoop-3.1.1/logs/hadoop-hadoop-datanode-server1.out.4
hadoop-3.1.1/logs/hadoop-hadoop-datanode-server1.out.5
hadoop-3.1.1/logs/hadoop-hadoop-namenode-server1.log
hadoop-3.1.1/logs/hadoop-hadoop-namenode-server1.out
hadoop-3.1.1/logs/hadoop-hadoop-namenode-server1.out.1
hadoop-3.1.1/logs/hadoop-hadoop-namenode-server1.out.2
hadoop-3.1.1/logs/hadoop-hadoop-namenode-server1.out.3
hadoop-3.1.1/logs/hadoop-hadoop-namenode-server1.out.4
hadoop-3.1.1/logs/hadoop-hadoop-namenode-server1.out.5
hadoop-3.1.1/logs/hadoop-hadoop-nodemanager-server1.log
hadoop-3.1.1/logs/hadoop-hadoop-nodemanager-server1.out
hadoop-3.1.1/logs/hadoop-hadoop-nodemanager-server1.out.1
hadoop-3.1.1/logs/hadoop-hadoop-nodemanager-server1.out.2
hadoop-3.1.1/logs/hadoop-hadoop-nodemanager-server1.out.3
hadoop-3.1.1/logs/hadoop-hadoop-nodemanager-server1.out.4
hadoop-3.1.1/logs/hadoop-hadoop-nodemanager-server1.out.5
hadoop-3.1.1/logs/hadoop-hadoop-resourcemanager-server1.log
hadoop-3.1.1/logs/hadoop-hadoop-resourcemanager-server1.out
hadoop-3.1.1/logs/hadoop-hadoop-resourcemanager-server1.out.1
hadoop-3.1.1/logs/hadoop-hadoop-resourcemanager-server1.out.2
hadoop-3.1.1/logs/hadoop-hadoop-resourcemanager-server1.out.3
hadoop-3.1.1/logs/hadoop-hadoop-resourcemanager-server1.out.4
hadoop-3.1.1/logs/hadoop-hadoop-resourcemanager-server1.out.5

sent 715,375 bytes  received 39,908 bytes  503,522.00 bytes/sec
total size is 835,950,736  speedup is 1,106.80

 

posted @ 2019-11-29 16:41  丹尼伯夷  阅读(494)  评论(0)  编辑  收藏  举报