本篇内容介绍了“hadoop2.7.3+HA+YARN+zookeeper高可用集群如何部署”的有关知识，在实际案例的操作过程中，不少人都会遇到这样的困境，接下来就让小编带领大家学习一下如何处理这些情况吧！希望大家仔细阅读，能够学有所成！
一、安装版本：
| JDK | 1.8.0_111-b14 |
| hadoop | hadoop-2.7.3 |
| zookeeper | zookeeper-3.5.2 |
二、安装步骤：
JDK的安装和集群的依赖环境配置不再叙述
1、hadoop配置
hadoop配置主要涉及hdfs-site.xml，core-site.xml，mapred-site.xml，yarn-site.xml四个文件。以下详细介绍每个文件的配置。
core-site.xml的配置
<configuration>
<property>
<name>fs.defaultFS</name>
<value>hdfs://cluster1</value>
<description>HDFS namenode的逻辑名称，也就是namenode HA,此值要对应hdfs-site.xml里的dfs.nameservices</description>
</property>
<property>
<name>hadoop.tmp.dir</name>
<value>/usr/hadoop/tmp</value>
<description>hdfs中namenode和datanode的数据默认放置路径，也可以在hdfs-site.xml中分别指定</description>
</property>
<property>
<name>ha.zookeeper.quorum</name>
<value>master:2181,salve1:2181,salve2:2181</value>
<description>zookeeper集群的地址和端口，zookeeper集群的节点数必须为奇数</description>
</property>
</configuration>
hdfs-site.xml的配置（重点配置）
<configuration>
<property>
<name>dfs.name.dir</name>
<value>/usr/hadoop/hdfs/name</value>
<description>namenode的数据放置目录</description>
</property>
<property>
<name>dfs.data.dir</name>
<value>/usr/hadoop/hdfs/data</value>
<description>datanode的数据放置目录</description>
</property>
<property>
<name>dfs.replication</name>
<value>4</value>
<description>数据块的备份数，默认是3</description>
</property>
<property>
<name>dfs.nameservices</name>
<value>cluster1</value>
<description>HDFS namenode的逻辑名称，也就是namenode HA</description>
</property>
<property>
<name>dfs.ha.namenodes.cluster1</name>
<value>ns1,ns2</value>
<description>nameservices对应的namenode逻辑名</description>
</property>
<property>
<name>dfs.namenode.rpc-address.cluster1.ns1</name>
<value>master:9000</value>
<description>指定namenode(ns1)的rpc地址和端口</description>
</property>
<property>
<name>dfs.namenode.http-address.cluster1.ns1</name>
<value>master:50070</value>
<description>指定namenode(ns1)的web地址和端口</description>
</property>
<property>
<name>dfs.namenode.rpc-address.cluster1.ns2</name>
<value>salve1:9000</value>
<description>指定namenode(ns2)的rpc地址和端口</description>
</property>
<property>
<name>dfs.namenode.http-address.cluster1.ns2</name>
<value>salve1:50070</value>
<description>指定namenode(ns2)的web地址和端口</description>
</property>
<property>
<name>dfs.namenode.shared.edits.dir</name>
<value>qjournal://master:8485;salve1:8485;salve2:8485/cluster1 </value>
<description>这是NameNode读写JNs组的uri，active NN 将 edit log 写入这些JournalNode，而 standby NameNode 读取这些 edit log，并作用在内存中的目录树中</description>
</property>
<property>
<name>dfs.journalnode.edits.dir</name>
<value>/usr/hadoop/journal</value>
<description>ournalNode 所在节点上的一个目录，用于存放 editlog 和其他状态信息。</description>
</property>
<property>
<name>dfs.ha.automatic-failover.enabled</name>
<value>true</value>
<description>启动自动failover。自动failover依赖于zookeeper集群和ZKFailoverController（ZKFC），后者是一个zookeeper客户端，用来监控NN的状态信息。每个运行NN的节点必须要运行一个zkfc</description>
</property>
<property>
<name>dfs.client.failover.proxy.provider.cluster1</name>
<value>org.apache.hadoop.hdfs.server.namenode.ha.ConfiguredFailoverProxyProvider</value>
<description>配置HDFS客户端连接到Active NameNode的一个java类</description>
</property>
<property>
<name>dfs.ha.fencing.methods</name>
<value>sshfence</value>
<description>解决HA集群脑裂问题（即出现两个 master 同时对外提供服务，导致系统处于不一致状态）。在 HDFS HA中，JournalNode 只允许一个 NameNode 写数据，不会出现两个 active NameNode 的问题，
但是，当主备切换时，之前的 active NameNode 可能仍在处理客户端的 RPC 请求，为此，需要增加隔离机制（fencing）将之前的 active NameNode 杀死。常用的fence方法是sshfence，要指定ssh通讯使用的密钥dfs.ha.fencing.ssh.private-key-files和连接超时时间</description>
</property>
<property>
<name>dfs.ha.fencing.ssh.private-key-files</name>
<value>/home/hadoop/.ssh/id_rsa</value>
<description>ssh通讯使用的密钥</description>
</property>
<property>
<name>dfs.ha.fencing.ssh.connect-timeout</name>
<value>30000</value>
<description>连接超时时间</description>
</property>
</configuration>
mapred-site.xml的配置
<configuration>
<property>
<name>mapreduce.framework.name</name>
<value>yarn</value>
<description>指定运行mapreduce的环境是yarn，与hadoop1截然不同的地方</description>
</property>
<property>
<name>mapreduce.jobhistory.address</name>
<value>master:10020</value>
<description>MR JobHistory Server管理的日志的存放位置</description>
</property>
<property>
<name>mapreduce.jobhistory.webapp.address</name>
<value>master:19888</value>
<description>查看历史服务器已经运行完的Mapreduce作业记录的web地址，需要启动该服务才行</description>
</property>
<property>
<name>mapreduce.jobhistory.done-dir</name>
<value>/data/hadoop/done</value>
<description>MR JobHistory Server管理的日志的存放位置,默认:/mr-history/done</description>
</property>
<property>
<name>mapreduce.jobhistory.intermediate-done-dir</name>
<value>hdfs://mycluster-pha/mapred/tmp</value>
<description>MapReduce作业产生的日志存放位置，默认值:/mr-history/tmp</description>
</property>
</configuration>
yarn-site.xml的配置
<configuration>
<property>
<name>yarn.nodemanager.aux-services</name>
<value>mapreduce_shuffle</value>
<description>默认</description>
</property>
<property>
<name>yarn.nodemanager.auxservices.mapreduce.shuffle.class</name>
<value>org.apache.hadoop.mapred.ShuffleHandler</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>
<property>
<name>yarn.nodemanager.resource.memory-mb</name>
<value>1024</value>
<description>该值配置小于1024时，NM是无法启动的！会报错：
NodeManager from slavenode2 doesn't satisfy minimum allocations, Sending SHUTDOWN signal to the NodeManager.</description>
</property>
</configuration>
2.zookeeper配置
zookeeper的配置主要是zoo.cfg和myid两个文件
conf/zoo.cfg配置：先将zoo_sample.cfg改成zoo.cfg
cp zoo_sample.cfg zoo.cfg
vi zoo.cfg
dataDir：数据的放置路径
dataLogDir：log的放置路径
initLimit=10
syncLimit=5
clientPort=2181
tickTime=2000
dataDir=/usr/zookeeper/tmp/data
dataLogDir=/usr/zookeeper/tmp/log
server.1=master:2888:3888
server.2=slave1:2888:3888
server.3=slave2:2888:3888
在[master,slave1,slave2]节点的dataDir目录新建文件myid
vi myid
master节点编辑：1
slave1节点编辑：2
slave2节点编辑：3
如下：
[hadoop@master data]$ vi myid
1
三、启动集群
1.zookeeper集群启动
1.启动zookeeper集群，在三个节点全部启动
bin/zkServer.sh start
2.查看集群zookeeper状态：zkServer.sh status，一个learer两个follower。
[hadoop@master hadoop-2.7.3]$ zkServer.sh status
ZooKeeper JMX enabled by default
Using config: /usr/local/zookeeper-3.5.2-alpha/bin/../conf/zoo.cfg
Client port found: 2181. Client address: localhost.
Mode: follower
[hadoop@slave1 root]$ zkServer.sh status
ZooKeeper JMX enabled by default
Using config: /usr/local/zookeeper-3.5.2-alpha/bin/../conf/zoo.cfg
Client port found: 2181. Client address: localhost.
Mode: leader
[hadoop@slave2 root]$ zkServer.sh status
ZooKeeper JMX enabled by default
Using config: /usr/local/zookeeper-3.5.2-alpha/bin/../conf/zoo.cfg
Client port found: 2181. Client address: localhost.
Mode: follower
3.验证zookeeper（非必须）： 执行zkCli.sh
[hadoop@slave1 root]$ zkCli.sh
Connecting to localhost:2181
2016-12-18 02:05:03,115 [myid:] - INFO [main:Environment@109] - Client environment:zookeeper.version=3.5.2-alpha-1750793, built on 06/30/2016 13:15 GMT
2016-12-18 02:05:03,118 [myid:] - INFO [main:Environment@109] - Client environment:host.name=salve1
2016-12-18 02:05:03,118 [myid:] - INFO [main:Environment@109] - Client environment:java.version=1.8.0_111
2016-12-18 02:05:03,120 [myid:] - INFO [main:Environment@109] - Client environment:java.vendor=Oracle Corporation
2016-12-18 02:05:03,120 [myid:] - INFO [main:Environment@109] - Client environment:java.home=/usr/local/jdk1.8.0_111/jre
2016-12-18 02:05:03,120 [myid:] - INFO [main:Environment@109] - Client environment:java.class.path=/usr/local/zookeeper-3.5.2-alpha/bin/../build/classes:/usr/local/zookeeper-3.5.2-alpha/bin/../build/lib/*.jar:/usr/local/zookeeper-3.5.2-alpha/bin/../lib/slf4j-log4j12-1.7.5.jar:/usr/local/zookeeper-3.5.2-alpha/bin/../lib/slf4j-api-1.7.5.jar:/usr/local/zookeeper-3.5.2-alpha/bin/../lib/servlet-api-2.5-20081211.jar:/usr/local/zookeeper-3.5.2-alpha/bin/../lib/netty-3.10.5.Final.jar:/usr/local/zookeeper-3.5.2-alpha/bin/../lib/log4j-1.2.17.jar:/usr/local/zookeeper-3.5.2-alpha/bin/../lib/jline-2.11.jar:/usr/local/zookeeper-3.5.2-alpha/bin/../lib/jetty-util-6.1.26.jar:/usr/local/zookeeper-3.5.2-alpha/bin/../lib/jetty-6.1.26.jar:/usr/local/zookeeper-3.5.2-alpha/bin/../lib/javacc.jar:/usr/local/zookeeper-3.5.2-alpha/bin/../lib/jackson-mapper-asl-1.9.11.jar:/usr/local/zookeeper-3.5.2-alpha/bin/../lib/jackson-core-asl-1.9.11.jar:/usr/local/zookeeper-3.5.2-alpha/bin/../lib/commons-cli-1.2.jar:/usr/local/zookeeper-3.5.2-alpha/bin/../zookeeper-3.5.2-alpha.jar:/usr/local/zookeeper-3.5.2-alpha/bin/../src/java/lib/*.jar:/usr/local/zookeeper-3.5.2-alpha/bin/../conf:.:/usr/local/jdk1.8.0_111/lib/dt.jar:/usr/local/jdk1.8.0_111/lib/tools.jar:/usr/local/zookeeper-3.5.2-alpha/bin:/usr/local/hadoop-2.7.3/bin
2016-12-18 02:05:03,120 [myid:] - INFO [main:Environment@109] - Client environment:java.library.path=/usr/java/packages/lib/amd64:/usr/lib64:/lib64:/lib:/usr/lib
2016-12-18 02:05:03,121 [myid:] - INFO [main:Environment@109] - Client environment:java.io.tmpdir=/tmp
2016-12-18 02:05:03,121 [myid:] - INFO [main:Environment@109] - Client environment:java.compiler=<NA>
2016-12-18 02:05:03,121 [myid:] - INFO [main:Environment@109] - Client environment:os.name=Linux
2016-12-18 02:05:03,121 [myid:] - INFO [main:Environment@109] - Client environment:os.arch=amd64
2016-12-18 02:05:03,121 [myid:] - INFO [main:Environment@109] - Client environment:os.version=3.10.0-327.22.2.el7.x86_64
2016-12-18 02:05:03,121 [myid:] - INFO [main:Environment@109] - Client environment:user.name=hadoop
2016-12-18 02:05:03,121 [myid:] - INFO [main:Environment@109] - Client environment:user.home=/home/hadoop
2016-12-18 02:05:03,121 [myid:] - INFO [main:Environment@109] - Client environment:user.dir=/tmp/hsperfdata_hadoop
2016-12-18 02:05:03,121 [myid:] - INFO [main:Environment@109] - Client environment:os.memory.free=52MB
2016-12-18 02:05:03,123 [myid:] - INFO [main:Environment@109] - Client environment:os.memory.max=228MB
2016-12-18 02:05:03,123 [myid:] - INFO [main:Environment@109] - Client environment:os.memory.total=57MB
2016-12-18 02:05:03,146 [myid:] - INFO [main:ZooKeeper@855] - Initiating client connection, connectString=localhost:2181 sessionTimeout=30000 watcher=org.apache.zookeeper.ZooKeeperMain$MyWatcher@593634ad
Welcome to ZooKeeper!
2016-12-18 02:05:03,171 [myid:localhost:2181] - INFO [main-SendThread(localhost:2181):ClientCnxn$SendThread@1113] - Opening socket connection to server localhost/127.0.0.1:2181. Will not attempt to authenticate using SASL (unknown error)
JLine support is enabled
2016-12-18 02:05:03,243 [myid:localhost:2181] - INFO [main-SendThread(localhost:2181):ClientCnxn$SendThread@948] - Socket connection established, initiating session, client: /127.0.0.1:56184, server: localhost/127.0.0.1:2181
2016-12-18 02:05:03,252 [myid:localhost:2181] - INFO [main-SendThread(localhost:2181):ClientCnxn$SendThread@1381] - Session establishment complete on server localhost/127.0.0.1:2181, sessionid = 0x200220f5fe30060, negotiated timeout = 30000
WATCHER::
WatchedEvent state:SyncConnected type:None path:null
[zk: localhost:2181(CONNECTED) 0]
2.hadoop集群启动
1.第一次配置启动
1.1在三个节点上启动Journalnode deamons，然后jps，出现JournalNode进程。
sbin/./hadoop-daemon.sh start journalnode
jps
JournalNode
1.2格式化master上的namenode（任意一个），然后启动该节点的namenode。
bin/hdfs namenode -format
sbin/hadoop-daemon.sh start namenode
1.3在另一个namenode节点slave1上同步master上的元数据信息
bin/hdfs namenode -bootstrapStandby
1.4停止hdfs上的所有服务
sbin/stop-dfs.sh
1.5初始化zkfc
bin/hdfs zkfc -formatZK
1.6启动hdfs
sbin/start-dfs.sh
1.7启动yarn
sbin/start-yarn.sh
2.非第一次配置启动
2.1直接启动hdfs和yarn即可，namenode、datanode、journalnode、DFSZKFailoverController都会自动启动。
sbin/start-dfs.sh
2.2启动yarn
sbin/start-yarn.sh
四、查看各节点的进程
4.1master
[hadoop@master hadoop-2.7.3]$ jps
26544 QuorumPeerMain
25509 JournalNode
25704 DFSZKFailoverController
26360 Jps
25306 DataNode
25195 NameNode
25886 ResourceManager
25999 NodeManager
4.2slave1
[hadoop@slave1 root]$ jps
2289 DFSZKFailoverController
9400 QuorumPeerMain
2601 Jps
2060 DataNode
2413 NodeManager
2159 JournalNode
1983 NameNode
4.3slave2
[hadoop@slave2 root]$ jps
11984 DataNode
12370 Jps
2514 QuorumPeerMain
12083 JournalNode
12188 NodeManager
“hadoop2.7.3+HA+YARN+zookeeper高可用集群如何部署”的内容就介绍到这里了，感谢大家的阅读。如果想了解更多行业相关的知识可以关注天达云网站，小编将为大家输出更多高质量的实用文章！