搭建部署Hadoop 之 HDFS

HDFS  Hadoop 分布式文件系统

分布式文件系统

分布式文件系统可以有效解决数据的存储和管理难题

– 将固定于某个地点的某个文件系统,扩展到任意多个地点/多个文件系统

– 众多的节点组成一个文件系统网络

– 每个节点可以分布在不同的地点,通过网络进行节点间的通信和数据传输

– 人们在使用分布式文件系统时,无需关心数据是存储在哪个节点上、或者是从哪个节点从获取的,只需要像使用本地文件系统一样管理和存储文件系统中的数据

HDFS 角色及概念

? 是Hadoop体系中数据存储管理的基础。它是一个高度容错的系统,用于在低成本的通用硬件上运行。

? 角色和概念

– Client

– Namenode

– Secondarynode

– Datanode

? NameNode

– Master节点,管理HDFS的名称空间和数据块映射信息,配置副本策略,处理所有客户端请求。

? Secondary NameNode

– 定期合并 fsimage 和fsedits,推送给NameNode

– 紧急情况下,可辅助恢复NameNode,

? 但Secondary NameNode并非NameNode的热备。

? DataNode

– 数据存储节点,存储实际的数据

– 汇报存储信息给NameNode。

? Client

– 切分文件

– 访问HDFS

– 与NameNode交互,获取文件位置信息

– 与DataNode交互,读取和写入数据。

? Block

– 每块缺省64MB大小

– 每块可以多个副本

搭建部署 HDFS 分布式文件系统

实验环境准备：

# vim /etc/hosts

.. ..

192.168.4.1master

192.168.4.2node1

192.168.4.3node2

192.168.4.4node3

# sed -ri  "/Host */aStrictHostKeyChecking no" /etc/ssh/ssh_config

# ssh-keygen

# for i in {1..4}

> do

> ssh-copy-id 192.168.4.${i}

> done

# for i in {1..4}        //同步本地域名

> do

> rsync -a /etc/hosts 192.168.4.${i}:/etc/hosts

> done

# rm -rf /etc/yum.repos.d/*

# vim /etc/yum.repos.d/yum.repo   //配置网络yum

[yum]

name=yum

baseurl=http://192.168.4.254/rhel7

gpgcheck=0

# for i in {2..4}

> do

> ssh 192.168.4.${i} "rm -rf /etc/yum.repos.d/*"

> rsync -a /etc/yum.repos.d/yum.repo 192.168.4.${i}:/etc/yum.repos.d/

> done

# for i in {1..4}

> do

> ssh 192.168.4.${i} 'sed -ri "s/^(SELINUX=).*/\1disabled/" /etc/selinux/config ; yum -y remove firewalld'

> done

//所有机器重启

搭建完全分布式

系统规划：

主机                                            角色                                                            软件

192.168.4.1    master             NameNode  SecondaryNameNode        HDFS

192.168.4.2     node1             DataNode                                                    HDFS

192.168.4.3     node2             DataNode                                                    HDFS

192.168.4.4     node3             DataNode                                                    HDFS

在所有系统上安装java 环境和调试工具jtarps

# for i in {1..4}

> do

> ssh 192.168.4.${i} "yum -y install java-1.8.0-openjdk-devel.x86_64"

> done

# which java

/usr/bin/java

# readlink -f /usr/bin/java

/usr/lib/jvm/java-1.8.0-openjdk-1.8.0.65-3.b17.el7.x86_64/jre/bin/java

安装 hadoop

# tar -xf hadoop-2.7.3.tar.gz

# mv hadoop-2.7.3 /usr/local/hadoop

修改配置

# cd /usr/local/hadoop/

# sed -ri "s;(export JAVA_HOME=).*;\1/usr/lib/jvm/java-1.8.0-openjdk-1.8.0.65-3.b17.el7.x86_64/jre;" etc/hadoop/hadoop-env.sh

# sed -ri "s;(export HADOOP_CONF_DIR=).*;\1/usr/local/hadoop/etc/hadoop;" etc/hadoop/hadoop-env.sh

# sed -n "25p;33p" etc/hadoop/hadoop-env.sh

export JAVA_HOME=/usr/lib/jvm/java-1.8.0-openjdk-1.8.0.65-3.b17.el7.x86_64/jre

export HADOOP_CONF_DIR=/usr/local/hadoop/etc/hadoop

//配置参数说明 网站http://hadoop.apache.org/docs/r2.7.5/hadoop-project-dist/hadoop-common/core-default.xml

# vim etc/hadoop/core-site.xml

.. ..

<configuration>

<property>

<name>fs.defaultFS</name>                    //默认的文件系统

<value>hdfs://master:9000</value>

</property>

<property>

<name>hadoop.tmp.dir</name>                //所有程序存放位置 hadoop根目录

<value>/var/hadoop</value>

</property>

</configuration>

//所有机器上创建 根目录

# for i in {1..4}

> do

> ssh 192.168.4.${i} "mkdir /var/hadoop"

> done

//配置参数说明 网站http://hadoop.apache.org/docs/r2.7.5/hadoop-project-dist/hadoop-hdfs/hdfs-default.xml

# vim etc/hadoop/hdfs-site.xml

<configuration>

<property>

<name>dfs.namenode.http-address</name>        //配置namenode 地址

<value>master:50070</value>

</property>

<property>

<name>dfs.namenode.secondary.http-address</name>        //配置 secondarynamenode 地址

<value>master:50090</value>

</property>

<property>

<name>dfs.replication</name>                //配置数据存储几份

<value>2</value>

</property>

</configuration>

# vim etc/hadoop/slaves         //配置去那些主机上寻找 DataNode

node1

node2

node3

配置完成以后,把 hadoop 的文件夹拷贝到所有机器

# for i in {2..4}

> do

> rsync -azSH --delete /usr/local/hadoop 192.168.4.${i}:/usr/local/ -e "ssh"

> done

//在 NameNode 下执行格式化 Hadoop

# ./bin/hdfs namenode -format

看见 successfully formatted.   说明 格式化成功了

//在没有报错的情况下 启动集群

# ./sbin/start-dfs.sh

启动以后分别在 namenode 和 datanode执行命令

# for i in master node{1..3}

> do

> echo $i

> ssh ${i} "jps"

> done

master

4562 SecondaryNameNode

4827 NameNode

5149 Jps

node1

3959 DataNode

4105 Jps

node2

3957 Jps

3803 DataNode

node3

3956 Jps

3803 DataNode

# ./bin/hdfs dfsadmin -report                //查看注册成功的节点

Configured Capacity: 160982630400 (149.93 GB)

Present Capacity: 150644051968 (140.30 GB)

DFS Remaining: 150644039680 (140.30 GB)

DFS Used: 12288 (12 KB)

DFS Used%: 0.00%

Under replicated blocks: 0

Blocks with corrupt replicas: 0

Missing blocks: 0

Missing blocks (with replication factor 1): 0

-------------------------------------------------

Live datanodes (3):

Name: 192.168.4.2:50010 (node1)

Hostname: node1

Decommission Status : Normal

Configured Capacity: 53660876800 (49.98 GB)

DFS Used: 4096 (4 KB)

Non DFS Used: 3446755328 (3.21 GB)

DFS Remaining: 50214117376 (46.77 GB)

DFS Used%: 0.00%

DFS Remaining%: 93.58%

Configured Cache Capacity: 0 (0 B)

Cache Used: 0 (0 B)

Cache Remaining: 0 (0 B)

Cache Used%: 100.00%

Cache Remaining%: 0.00%

Xceivers: 1

Last contact: Mon Jan 29 21:17:39 EST 2018

Name: 192.168.4.4:50010 (node3)

Hostname: node3

Decommission Status : Normal

Configured Capacity: 53660876800 (49.98 GB)

DFS Used: 4096 (4 KB)

Non DFS Used: 3445944320 (3.21 GB)

DFS Remaining: 50214928384 (46.77 GB)

DFS Used%: 0.00%

DFS Remaining%: 93.58%

Configured Cache Capacity: 0 (0 B)

Cache Used: 0 (0 B)

Cache Remaining: 0 (0 B)

Cache Used%: 100.00%

Cache Remaining%: 0.00%

Xceivers: 1

Last contact: Mon Jan 29 21:17:39 EST 2018

Name: 192.168.4.3:50010 (node2)

Hostname: node2

Decommission Status : Normal

Configured Capacity: 53660876800 (49.98 GB)

DFS Used: 4096 (4 KB)

Non DFS Used: 3445878784 (3.21 GB)

DFS Remaining: 50214993920 (46.77 GB)

DFS Used%: 0.00%

DFS Remaining%: 93.58%

Configured Cache Capacity: 0 (0 B)

Cache Used: 0 (0 B)

Cache Remaining: 0 (0 B)

Cache Used%: 100.00%

Cache Remaining%: 0.00%

Xceivers: 1

Last contact: Mon Jan 29 21:17:39 EST 2018

HDFS 基本使用

HDFS 基本命令 几乎和shell命令相同

# ./bin/hadoop fs -ls hdfs://master:9000/

# ./bin/hadoop fs -mkdir /test

# ./bin/hadoop fs -ls /

Found 1 items

drwxr-xr-x   - root supergroup          0 2018-01-29 21:35 /test

# ./bin/hadoop fs -rmdir /test

# ./bin/hadoop fs -mkdir /input

# ./bin/hadoop fs -put *.txt /input                    //上传文件

# ./bin/hadoop fs -ls /input

Found 3 items

-rw-r--r--   2 root supergroup      84854 2018-01-29 21:37 /input/LICENSE.txt

-rw-r--r--   2 root supergroup      14978 2018-01-29 21:37 /input/NOTICE.txt

-rw-r--r--   2 root supergroup       1366 2018-01-29 21:37 /input/README.txt

# ./bin/hadoop fs -get /input/README.txt /root/            //下载文件

# ls /root/README.txt

/root/README.txt

原文地址：http://blog.51cto.com/13558754/2066708