Java之美[从菜鸟到高手演练]之Linux下Hadoop的完全分布式安装，javahadoop

文章由LinuxBoy分享于2019-03-27 07:03:56热评（484）

Java之美[从菜鸟到高手演练]之Linux下Hadoop的完全分布式安装，javahadoop

作者：二青

邮箱：xtfggef@gmail.com 微博：http://weibo.com/xtfggef

本来是想安装一个单节点的环境就好了，后来按装完了总觉得不够过瘾，于是今天继续研究一下，来一个完全分布式的集群安装。用到的软件和上一篇单节点安装Hadoop一样，如下：

Ubuntu 14.10 64 Bit Server Edition
Hadoop2.6.0
JDK 1.7.0_71
ssh
rsync

准备环境

依然是VirtualBox + Ubuntu 14.10 64 Bit，只不过这次是3个节点，话不多说，下面开始配置准备，基础环境就不再赘述了，包括安装JDK，ssh，rsync等，可以参考上一篇。

master 192.168.1.118 nameNode
slave1 192.168.1.189 dataNode1
slave2 192.168.1.116 dataNode2

修改每个机器的hosts文件，在/etc/hosts文件末尾添加如下配置：

192.168.1.118   master
192.168.1.189   slave1
192.168.1.116   slave2

2015年1月15日补充：

1. 修改每个机器的hostname，在/etc/hostsname下，将master机器的hostname改为master，以此类推。

2. 赋予当前用户管理员权限。

3. 将IP地址改成静态IP，通过修改/etc/network/interfaces文件，添加如下配置：

auto eth0
iface eth0 inet static
address 192.168.1.118
netmask 255.255.255.0
gateway 192.168.1.1

修改完需重启才能生效。

配置namenode对datanode的无密钥访问

直接在namenode控制台执行如下两行命令：

$ ssh-keygen -t dsa -P '' -f ~/.ssh/id_dsa
$ cat ~/.ssh/id_dsa.pub >> ~/.ssh/authorized_keys

进入namenode的用户根目录，再进入.ssh目录查看生成的文件：authorized_keys, id_dsa, id_dsa.pub

将authorized_keys文件分发到个datanode节点上：

验证：

ssh 192.168.1.189

ssh 192.168.1.116

ssh slave1

ssh slave2

如果不需要密码直接进入则OK，否则重新来配。

安装Hadoop

1. 从官网下载hadoop 2.6.0 tar.gz文件，然后解压到用户目录：tar -zxvf hadoop-2.6.0.tar.gz.

2. 在解压后的hadoop-2.6.0文件夹里创建tmp文件夹。

3. 配置环境变量

添加如下配置信息到/etc/profile文件末尾（每台机器都要配置）。

# set hadoop path
export HADOOP_HOME=/home/adam/hadoop-2.6.0
export PATH=$PATH:$HADOOP_HOME/bin

执行. /etc/profile或者source /etc/profile使配置生效，然后执行hadoop version查看hadoop版本并且验证环境变量是否配置成功。

4. 配置hadoop，进入目录/home/adam/hadoop-2.6.0/etc/hadoop

a>. 编辑core-site.xml

<configuration>
    <property>
        <name>hadoop.tmp.dir</name>
        <value>/home/adam/hadoop-2.6.0/tmp</value>
        <description>Abase for other temporary directories.</description>
    </property>
    <property>
        <name>fs.defaultFS</name>
        <value>hdfs://master:9000</value>
    </property>
    <property>
        <name>io.file.buffer.size</name>
        <value>4096</value>
    </property>
</configuration>

b>. 在hadoop-env.sh和yarn-env.sh里配置JAVA_HOME环境变量如下

3. 编辑hdfs-site.xml

<configuration>
    <property>
    	<name>dfs.nameservices</name>
        <value>hadoop-cluster</value>
    </property>
    <property>
        <name>dfs.namenode.secondary.http-address</name>
        <value>master:50090</value>
    </property>
    <property>
        <name>dfs.namenode.name.dir</name>
        <value>file:///home/adam/hadoop-2.6.0/dfs/name</value>
    </property>
    <property>
        <name>dfs.datanode.data.dir</name>
        <value>file:///home/adam/hadoop-2.6.0/dfs/data</value>
    </property>
    <property>
        <name>dfs.replication</name>
        <value>1</value>
    </property>
    <property>
        <name>dfs.webhdfs.enabled</name>
        <value>true</value>
    </property>
</configuration>

4. 编辑mapred-site.xml

<configuration>
    <property>
        <name>mapreduce.framework.name</name>
        <value>yarn</value>
    </property>
    <property>
        <name>mapreduce.jobtracker.http.address</name>
        <value>master:50030</value>
    </property>
    <property>
        <name>mapreduce.jobhistory.address</name>
        <value>master:10020</value>
    </property>
    <property>
        <name>mapreduce.jobhistory.webapp.address</name>
        <value>master:19888</value>
    </property>
</configuration>

5. 编辑yarn-site.xml

<configuration>

<!-- Site specific YARN configuration properties -->
    <property>
        <name>yarn.nodemanager.aux-services</name>
        <value>mapreduce_shuffle</value>
    </property>
    <property>
        <name>yarn.resourcemanager.address</name>
        <value>master:8032</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.admin.address</name>
        <value>master:8033</value>
    </property>
    <property>
        <name>yarn.resourcemanager.webapp.address</name>
        <value>master:8088</value>
    </property>
</configuration>

6. 编辑slaves文件添加如下两行：

slave1

slave2

7. 将hadoop文件夹复制到另个slave结点上

启动Hadoop

1. 格式化namenode

adam@ubuntu:~/hadoop-2.6.0/bin$ ./hdfs namenode -format
15/01/14 19:29:58 INFO namenode.NameNode: STARTUP_MSG:
/************************************************************
STARTUP_MSG: Starting NameNode
STARTUP_MSG:   host = ubuntu/60.191.124.254
STARTUP_MSG:   args = [-format]
STARTUP_MSG:   version = 2.6.0
STARTUP_MSG:   classpath = /home/adam/hadoop-2.6.0/etc/hadoop:/home/adam/hadoop-2.6.0/share/hadoop/common/lib/slf4j-log4j12-1.7.5.jar:/home/adam/hadoop-2.6.0/share/hadoop/common/lib/jsr305-1.3.9.jar:/home/adam/h ...
jar:/home/adam/hadoop-2.6.0/share/hadoop/mapreduce/hadoop-mapreduce-client-app-2.6.0.jar:/home/adam/hadoop-2.6.0/share/hadoop/mapreduce/hadoop-mapreduce-client-core-2.6.0.jar:/home/adam/hadoop-2.6.0/share/hadoop/mapreduce/hadoop-mapreduce-client-shuffle-2.6.0.jar:/home/adam/hadoop-2.6.0/contrib/capacity-scheduler/*.jar
STARTUP_MSG:   build = https://git-wip-us.apache.org/repos/asf/hadoop.git -r e3496499ecb8d220fba99dc5ed4c99c8f9e33bb1; compiled by 'jenkins' on 2014-11-13T21:10Z
STARTUP_MSG:   java = 1.7.0_71
************************************************************/
15/01/14 19:29:58 INFO namenode.NameNode: registered UNIX signal handlers for [TERM, HUP, INT]
15/01/14 19:29:58 INFO namenode.NameNode: createNameNode [-format]
Formatting using clusterid: CID-3f81e813-604e-4d60-93b1-9794d7c7c079
15/01/14 19:30:10 INFO namenode.FSNamesystem: No KeyProvider found.
15/01/14 19:30:10 INFO namenode.FSNamesystem: fsLock is fair:true
15/01/14 19:30:10 INFO blockmanagement.DatanodeManager: dfs.block.invalidate.limit=1000
15/01/14 19:30:10 INFO blockmanagement.DatanodeManager: dfs.namenode.datanode.registration.ip-hostname-check=true
15/01/14 19:30:10 INFO blockmanagement.BlockManager: dfs.namenode.startup.delay.block.deletion.sec is set to 000:00:00:00.000
15/01/14 19:30:10 INFO blockmanagement.BlockManager: The block deletion will start around 2015 Jan 14 19:30:10
15/01/14 19:30:10 INFO util.GSet: Computing capacity for map BlocksMap
15/01/14 19:30:10 INFO util.GSet: VM type       = 64-bit
15/01/14 19:30:10 INFO util.GSet: 2.0% max memory 966.7 MB = 19.3 MB
15/01/14 19:30:10 INFO util.GSet: capacity      = 2^21 = 2097152 entries
15/01/14 19:30:10 INFO blockmanagement.BlockManager: dfs.block.access.token.enable=false
15/01/14 19:30:10 INFO blockmanagement.BlockManager: defaultReplication         = 1
15/01/14 19:30:10 INFO blockmanagement.BlockManager: maxReplication             = 512
15/01/14 19:30:10 INFO blockmanagement.BlockManager: minReplication             = 1
15/01/14 19:30:10 INFO blockmanagement.BlockManager: maxReplicationStreams      = 2
15/01/14 19:30:10 INFO blockmanagement.BlockManager: shouldCheckForEnoughRacks  = false
15/01/14 19:30:10 INFO blockmanagement.BlockManager: replicationRecheckInterval = 3000
15/01/14 19:30:10 INFO blockmanagement.BlockManager: encryptDataTransfer        = false
15/01/14 19:30:10 INFO blockmanagement.BlockManager: maxNumBlocksToLog          = 1000
15/01/14 19:30:10 INFO namenode.FSNamesystem: fsOwner             = adam (auth:SIMPLE)
15/01/14 19:30:10 INFO namenode.FSNamesystem: supergroup          = supergroup
15/01/14 19:30:10 INFO namenode.FSNamesystem: isPermissionEnabled = true
15/01/14 19:30:10 INFO namenode.FSNamesystem: Determined nameservice ID: hadoop-cluster
15/01/14 19:30:10 INFO namenode.FSNamesystem: HA Enabled: false
15/01/14 19:30:10 INFO namenode.FSNamesystem: Append Enabled: true
15/01/14 19:30:16 INFO util.GSet: Computing capacity for map INodeMap
15/01/14 19:30:16 INFO util.GSet: VM type       = 64-bit
15/01/14 19:30:16 INFO util.GSet: 1.0% max memory 966.7 MB = 9.7 MB
15/01/14 19:30:16 INFO util.GSet: capacity      = 2^20 = 1048576 entries
15/01/14 19:30:16 INFO namenode.NameNode: Caching file names occuring more than 10 times
15/01/14 19:30:16 INFO util.GSet: Computing capacity for map cachedBlocks
15/01/14 19:30:16 INFO util.GSet: VM type       = 64-bit
15/01/14 19:30:16 INFO util.GSet: 0.25% max memory 966.7 MB = 2.4 MB
15/01/14 19:30:16 INFO util.GSet: capacity      = 2^18 = 262144 entries
15/01/14 19:30:16 INFO namenode.FSNamesystem: dfs.namenode.safemode.threshold-pct = 0.9990000128746033
15/01/14 19:30:16 INFO namenode.FSNamesystem: dfs.namenode.safemode.min.datanodes = 0
15/01/14 19:30:16 INFO namenode.FSNamesystem: dfs.namenode.safemode.extension     = 30000
15/01/14 19:30:16 INFO namenode.FSNamesystem: Retry cache on namenode is enabled
15/01/14 19:30:16 INFO namenode.FSNamesystem: Retry cache will use 0.03 of total heap and retry cache entry expiry time is 600000 millis
15/01/14 19:30:16 INFO util.GSet: Computing capacity for map NameNodeRetryCache
15/01/14 19:30:16 INFO util.GSet: VM type       = 64-bit
15/01/14 19:30:16 INFO util.GSet: 0.029999999329447746% max memory 966.7 MB = 297.0 KB
15/01/14 19:30:16 INFO util.GSet: capacity      = 2^15 = 32768 entries
15/01/14 19:30:16 INFO namenode.NNConf: ACLs enabled? false
15/01/14 19:30:16 INFO namenode.NNConf: XAttrs enabled? true
15/01/14 19:30:16 INFO namenode.NNConf: Maximum size of an xattr: 16384
15/01/14 19:30:16 INFO namenode.FSImage: Allocated new BlockPoolId: BP-1507698623-60.191.124.254-1421235016468
15/01/14 19:30:16 INFO common.Storage: Storage directory /home/adam/hadoop-2.6.0/dfs/name has been successfully formatted.
15/01/14 19:30:17 INFO namenode.NNStorageRetentionManager: Going to retain 1 images with txid >= 0
15/01/14 19:30:17 INFO util.ExitUtil: Exiting with status 0
15/01/14 19:30:17 INFO namenode.NameNode: SHUTDOWN_MSG:
/************************************************************
SHUTDOWN_MSG: Shutting down NameNode at ubuntu/60.191.124.254
************************************************************/

2. 启动Hadoop

hadoop/sbin start-all.sh或者start-dfs.sh & start-yard.sh

3. 验证安装

启动Job History Server：

root@master:~/hadoop/sbin# ./mr-jobhistory-daemon.sh start historyserver

这样一个完全的分布式hadoop集群就装好了，步骤也不多，有兴趣的同学可以试一试，有什么问题欢迎联系我：

微博：http://weibo.com/xtfggef

邮箱：xtfggef@gmail.com

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Java之美[从菜鸟到高手演练]之Linux下Hadoop的完全分布式安装，javahadoop