hadoop-2.3.0-cdh5.1.0徹底分佈式集羣配置及HA配置（待）

1、安裝前準備：
操做系統：CentOS 6.5 64位操做系統
環境：jdk1.7.0_45以上，本次採用jdk-7u55-linux-x64.tar.gz
master01 10.10.2.57 namenode 節點
master02 10.10.2.58 namenode 節點
slave01:10.10.2.173 datanode 節點
slave02:10.10.2.59 datanode 節點
slave03: 10.10.2.60 datanode 節點
注：Hadoop2.0以上採用的是jdk環境是1.7,Linux自帶的jdk卸載掉，從新安裝
下載地址：http://www.oracle.com/technetwork/java/javase/downloads/index.html
軟件版本：hadoop-2.3.0-cdh5.1.0.tar.gz, zookeeper-3.4.5-cdh5.1.0.tar.gz
下載地址：http://archive.cloudera.com/cdh5/cdh/5/
開始安裝：
2、jdk安裝
一、檢查是否自帶jdk
rpm -qa | grep jdk
java-1.6.0-openjdk-1.6.0.0-1.45.1.11.1.el6.i686 
二、卸載自帶jdk
yum -y remove java-1.6.0-openjdk-1.6.0.0-1.45.1.11.1.el6.i686
三、安裝jdk-7u55-linux-x64.tar.gz
在usr/目錄下建立文件夾java,在java文件夾下運行tar –zxvf jdk-7u55-linux-x64.tar.gz
解壓到java目錄下
[root@master01 java]# ls
jdk1.7.0_55
3、配置環境變量
遠行vi /etc/profile
# /etc/profile
# System wide environment and startup programs, for login setup
# Functions and aliases go in /etc/bashrc
export JAVA_HOME=/usr/java/jdk1.7.0_55
export JRE_HOME=/usr/java/jdk1.7.0_55/jre
export CLASSPATH=/usr/java/jdk1.7.0_55/lib
export PATH=$JAVA_HOME/bin: $PATH
保存修改，運行source /etc/profile 從新加載環境變量
運行java -version
[root@master01 java]# java -version
java version "1.7.0_55"
Java(TM) SE Runtime Environment (build 1.7.0_55-b13)
Java HotSpot(TM) 64-Bit Server VM (build 24.55-b03, mixed mode)
Jdk配置成功
4、系統配置
預先準備5臺機器，並配置IP
關閉防火牆
chkconfig iptables off(永久性關閉)
配置主機名和hosts文件
[root@master01 java]# vi /etc/hosts
127.0.0.1   localhost localhost.localdomain localhost4 localhost4.localdomain4
::1         localhost localhost.localdomain localhost6 localhost6.localdomain6
10.10.2.57 master01
10.10.2.58 master02
10.10.2.173 slave01
10.10.2.59 slave02
10.10.2.60 slave03
按照不一樣機器IP配置不一樣的主機名
三、SSH無密碼驗證配置
由於Hadoop運行過程須要遠程管理Hadoop的守護進程，NameNode節點須要經過SSH（Secure Shell）連接各個DataNode節點，中止或啓動他們的進程，因此SSH必須是沒有密碼的，因此咱們要把NameNode節點和DataNode節點配製成無祕密通訊，同理DataNode也須要配置無密碼連接NameNode節點。
在每一臺機器上配置：
vi /etc/ssh/sshd_config打開
RSAAuthentication yes # 啓用 RSA 認證，PubkeyAuthentication yes # 啓用公鑰私鑰配對認證方式
Master01:運行：ssh-keygen –t rsa –P ''  不輸入密碼直接enter
默認存放在 ／root／.ssh目錄下,
cat ~/.ssh/id_rsa.pub >> ~/.ssh/authorized_keys
[root@master01 .ssh]# ls
authorized_keys  id_rsa  id_rsa.pub  known_hosts
slave01執行相同的操做，而後將master01 ／root／.ssh/目錄下的id_rsa.pub放到 slave01 相同目錄下的authorized_keys這樣slave01就持有了master01的公鑰 而後直接ssh slave01測試是否能夠無密碼鏈接到slave01上，而後將slave01 上的id_rsa.pub 追加到master01的authorized_keys中，測試ssh master01 是否能夠直接連上slave01.
[root@master01 ~]# ssh slave01
Last login: Tue Aug 19 14:28:15 2014 from master01
[root@slave01 ~]# 
Master01-master02
Master01-slave01
Master01-slave02
Master01-slave03
Master02-slave01
Master02-slave02
Master02-slave03
執行相同的操做。
 
5、安裝Hadoop
創建文件目錄 /usr/local/cloud 建立文件夾data，存放數據、日誌文件，haooop原文件，zookeeper原文件
[root@slave01 cloud]# ls
data  hadoop  tar  zookeeper
5.一、配置hadoop-env.sh
進入到/usr/local/cloud/hadoop/etc/hadoop目錄下
配置vi hadoop-env.sh hadoop運行環境加載
export JAVA_HOME=/usr/java/jdk1.7.0_55
5.二、配置core-site.xml
<!—hadoop.tmp.dir:hadoop不少路徑都依賴他，namenode節點該目錄不能夠刪除，不然須要從新格式化-->
<property>
    <name>hadoop.tmp.dir</name>
    <value>/usr/local/cloud/data/hadoop/tmp</value>
</property>
<!—這個配置文件描述了集羣的namenode節點的url,這裏採用HA表明默認邏輯名，集羣中的每一個datanode節點都須要知道namenode的地址，數據才能夠被使用-->
<property>
    <name>fs.defaultFS</name>
    <value>hdfs://zzg</value>
</property>
<!-- zookeeper集羣的地址和端口,最好保持基數個至少3臺-->
 <property>
    <name>ha.zookeeper.quorum</name>
    <value>master01:2181,slave01:2181,slave02:2181</value>
</property>
 
(2)hdfs-site.xml配置
<!—hadoop namenode數據的存儲目錄，只是針對與namenode，包含了namenode的系統信息元數據信息-->
<property>
    <name>dfs.namenode.name.dir</name>
    <value>/usr/local/cloud/data/hadoop/dfs/nn</value>
</property>
<!—datanode 要存儲到數據到本地的路徑，沒必要每一臺機器都同樣，可是爲了方便管理最好仍是同樣-->
<property>
    <name>dfs.datanode.data.dir</name>
    <value>/usr/local/cloud/data/hadoop/dfs/dn</value>
</property>
<!—系統中文件備份數量，系統默認是3分-->
<property>
    <name>dfs.replication</name>
    <value>3</value>
</property>
<!-- dfs.webhdfs.enabled 置爲true，不然一些命令沒法使用如：webhdfs的LISTSTATUS -->
<property>
    <name>dfs.webhdfs.enabled</name>
    <value>true</value>
</property>
<!—可選，關閉權限帶來一些沒必要要的麻煩-->
<property>
     <name>dfs.permissions</name>
     <value>false</value>
</property>
<!—可選，關閉權限帶來一些沒必要要的麻煩-->
<property>
     <name>dfs.permissions.enabled</name>
     <value>false</value>
</property>
<!—HA配置-->
<!—設置集羣的邏輯名-->
<property>
    <name>dfs.nameservices</name>
    <value>zzg</value>
</property>
<!—hdfs聯邦集羣中的namenode節點邏輯名-->
<property>
    <name>dfs.ha.namenodes.zzg</name>
    <value>nn1,nn2</value>
</property>
<!—hdfs namenode邏輯名中RPC配置，rpc 簡單理解爲序列化文件上傳輸出文件要用到-->
<property>
    <name>dfs.namenode.rpc-address.zzg.nn1</name>
    <value>master01:9000</value>
</property>
<property>
    <name>dfs.namenode.rpc-address.zzg.nn2</name>
    <value>master02:9000</value>
</property>
<!—配置hadoop頁面訪問端口端口-->
<property>
    <name>dfs.namenode.http-address.zzg.nn1</name>
    <value>master01:50070</value>
</property>
<property>
    <name>dfs.namenode.http-address.zzg.nn2</name>
    <value>master02:50070</value>
</property>
<!—創建與namenode的通訊-->
<property>
    <name>dfs.namenode.servicerpc-address.zzg.nn1</name>
    <value>master01:53310</value>
</property>
<property>
    <name>dfs.namenode.servicerpc-address.zzg.nn2</name>
    <value>master02:53310</value>
</property>
<!—journalnode 共享文件集羣-->
<property>
    <name>dfs.namenode.shared.edits.dir</name>
    <value>qjournal://master01:8485;slave01:8485;slave02:8485/zzg</value>
</property>
 <!—journalnode對namenode的進行共享設置-->
<property>
    <name>dfs.journalnode.edits.dir</name>
    <value>/usr/local/cloud/data/hadoop/ha/journal</value>
</property>
<!—設置故障處理類-->
<property>
    <name>dfs.client.failover.proxy.provider.zzg</name>
    <value>org.apache.hadoop.hdfs.server.namenode.ha.ConfiguredFailoverProxyProvider</value>
</property>
<!—開啓自動切換-->
<property>
    <name>dfs.ha.automatic-failover.enabled</name>
    <value>true</value>
</property>
<property>
        <name>ha.zookeeper.quorum</name>
        <value>master01:2181,slave01:2181,slave02:2181</value>
</property>
<!—使用ssh方式進行故障切換-->
<property>
    <name>dfs.ha.fencing.methods</name>
    <value>sshfence</value>
</property>
<!—ssh通訊密碼通訊位置-->
<property>
    <name>dfs.ha.fencing.ssh.private-key-files</name>
    <value>/root/.ssh/id_rsa</value>
</property>
5.3 配置maped-site.xml
<property>
                <name>mapreduce.framework.name</name>
                <value>yarn</value>
</property>
5.4配置yarn HA 
配置yarn-en.sh java環境
# some Java parameters
  export JAVA_HOME=/usr/java/jdk1.7.0_55
5.5配置yarn-site.xml
        <!—rm失聯後從新連接的時間-->
        <property>
                <name>yarn.resourcemanager.connect.retry-interval.ms</name>
                <value>2000</value>
        </property>
        <!—開啓resource manager HA,默認爲false-->
         <property>
                <name>yarn.resourcemanager.ha.enabled</name>
                <value>true</value>
        </property>
        <!—開啓故障自動切換-->
        <property>
                <name>yarn.resourcemanager.ha.automatic-failover.enabled</name>
                <value>true</value>
        </property>
        <!—配置resource manager -->
        <property>
                <name>yarn.resourcemanager.ha.rm-ids</name>
                <value>rm1,rm2</value>
        </property>
        <!—在master01上配置rm1,在master02上配置rm2,-->
        <property>
                <name>yarn.resourcemanager.ha.id</name>
                <value>rm1</value>
               <description>If we want to launch more than one RM in single node, we need this configuration</description>
         </property>
        <!—開啓自動恢復功能-->
         <property>
                <name>yarn.resourcemanager.recovery.enabled</name>
                 <value>true</value>
        </property>
        <!—配置與zookeeper的鏈接地址-->
        <property>
                <name>yarn.resourcemanager.zk-state-store.address</name>
                <value>localhost:2181</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>localhost:2181</value>
        </property>
        <property>
                <name>yarn.resourcemanager.cluster-id</name>
                <value>yarn-cluster</value>
        </property>
        <!—schelduler失聯等待鏈接時間-->
         <property>
                <name>yarn.app.mapreduce.am.scheduler.connection.wait.interval-ms</name>
                <value>5000</value>
        </property>
        <!—配置rm1-->
        <property>
                <name>yarn.resourcemanager.address.rm1</name>
                <value>master01:23140</value>
        </property>
        <property>
                <name>yarn.resourcemanager.scheduler.address.rm1</name>
                <value>master01:23130</value>
        </property>
        <property>
                <name>yarn.resourcemanager.webapp.address.rm1</name>
                <value>master01:23188</value>
        </property>
        <property>
                <name>yarn.resourcemanager.resource-tracker.address.rm1</name>
                <value>master01:23125</value>
        </property>
         <property>
                <name>yarn.resourcemanager.admin.address.rm1</name>
                <value>master01:23141</value>
        </property>
        <property>
                <name>yarn.resourcemanager.ha.admin.address.rm1</name>
                <value>master01:23142</value>
        </property>
        <!—配置rm2-->
         <property>
                <name>yarn.resourcemanager.address.rm2</name>
                <value>master02:23140</value>
        </property>
        <property>
                <name>yarn.resourcemanager.scheduler.address.rm2</name>
                <value>master02:23130</value>
        </property>
        <property>
                <name>yarn.resourcemanager.webapp.address.rm2</name>
                <value>master02:23188</value>
        </property>
        <property>
                <name>yarn.resourcemanager.resource-tracker.address.rm2</name>
                <value>master02:23125</value>
        </property>
        <property>
                <name>yarn.resourcemanager.admin.address.rm2</name>
                <value>master02:23141</value>
        </property>
        <property>
                <name>yarn.resourcemanager.ha.admin.address.rm2</name>
                <value>master02:23142</value>
        </property>
        <!—配置nodemanager-->
        <property>
                <description>Address where the localizer IPC is.</description>
                <name>yarn.nodemanager.localizer.address</name>
                <value>0.0.0.0:23344</value>
        </property>
        <!—nodemanager http訪問端口-->
         <property>
                <description>NM Webapp address.</description>
                <name>yarn.nodemanager.webapp.address</name>
                <value>0.0.0.0:23999</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>/usr/local/cloud/data/hadoop/yarn/local</value>
        </property>
        <property>
                <name>yarn.nodemanager.log-dirs</name>
                <value>/usr/local/cloud/data/logs/hadoop</value>
        </property>
        <property>
                <name>mapreduce.shuffle.port</name>
                <value>23080</value>
        </property>
        <!—故障處理類-->
         <property>
                <name>yarn.client.failover-proxy-provider</name>
                 <value>org.apache.hadoop.yarn.client.ConfiguredRMFailoverProxyProvider</value>
         </property>
6、配置zookeeper集羣
在zookeeper目錄下創建data目錄 和logs目錄，
配置zoo.cnf
dataDir=/usr/local/cloud/zookeeper/data
dataLogDir=/usr/local/cloud/zookeeper/logs
# the port at which the clients will connect
clientPort=2181
server.1=master01:2888:3888
server.2=master02:2888:3888
server.3=slave01:2888:3888
server.4=slave02:2888:3888
server.5=slave03:2888:3888
在data目錄下建立myid文件，並在對應的機器上填寫數字，如上配置master01 server01 的myid寫入1，
master02 中的data的myid寫入2，依次在其餘機子上執行相同操做。
在各個機器下zookeeper目錄下的bin目錄下執行zkServer.sh start命令
再運行zkServer.sh status若是出現leader 或fllower 則說明集羣配置正確。
 
到此各個配置文件配置完畢
7、啓動Hadoop集羣嚴格按照如下順序執行（第一次）
(1)各個節點啓動zookeeper，在zookeeper/bin/zkServer.sh start
(2) 在hadoop/bin/hdfs zkfc –formatZK 進行格式化建立命名空間
(3)在配置了journalnode的節點啓動，master01，slave01,slave02
   在hadoop/sbin/hadoop-daemon.sh  journalnode
（4）在主namenode節點執行格式化
./bin/hadoop namenode -format zzg
 主機器上啓動namenode
 hadoop/sbin/ hadoop-daemon.sh start namenode
(5)將主namenode節點格式化的目錄拷貝到從主namenode節點上
hadoop/bin/hdfs namenode –bootstrapStandby
hadoop/sbin/hadoop-daemon.sh start namenode
(6) 在兩個namenode節點都執行如下命令
./sbin/hadoop-daemon.sh start zkfc
(7) 在全部datanode節點都執行如下命令啓動datanode
./sbin/hadoop-daemon.sh start datanode
(8)在主namenode節點啓動yarn，運行yarn-start.sh命令
jps能夠看到
namenode節點
[root@master01 ~]# jps
38972 JournalNode
38758 NameNode
39166 DFSZKFailoverController
37473 QuorumPeerMain
39778 ResourceManager
42620 Jps
datanode節點
[root@slave01 ~]# jps
33440 DataNode
35277 Jps
32681 QuorumPeerMain
33568 JournalNode
34231 NodeManager