hadoop 2.7.2 + zookeeper 高可用集群部署
一.環(huán)境說明
虛擬機:vmware 11
操作系統(tǒng):Ubuntu 16.04
Hadoop版本:2.7.2
Zookeeper版本:3.4.9
二.節(jié)點部署說明
三.Hosts增加配置
sudo gedit /etc/hosts
wxzz-pc、wxzz-pc0、wxzz-pc1、wxzz-pc2均配置如下:
127.0.0.1 localhost 192.168.72.132 wxzz-pc 192.168.72.138 wxzz-pc0 192.168.72.135 wxzz-pc1 192.168.72.136 wxzz-pc2?四.zookeeper上配置
Zoo.cfg配置文件內(nèi)容如下:
tickTime=2000 initLimit=10 syncLimit=5 dataDir=/opt/zookeeper-3.4.9/tmp/dataDir dataLogDir=/opt/zookeeper-3.4.9/tmp/logs/ clientPort=2181 server.1=wxzz-pc:2182:2183 server.2=wxzz-pc0:2182:2183 server.3=wxzz-pc1:2182:2183?在/opt/zookeeper-3.4.9/tmp/dataDir下新建”myid”文件,wxzz-pc、wxzz-pc0、wxzz-pc1三臺虛擬機中myid文件分別對應(yīng)的內(nèi)容為:1、2、3,也就是server.X=wxzz-pc:2182:2183,對應(yīng)X的數(shù)值。
五.Hadoop配置
1.core-site.xml 配置
<configuration><property><name>fs.defaultFS</name><value>hdfs://myhadoop:8020</value></property><property><name>hadoop.tmp.dir</name><value>/opt/hadoop-2.7.2/tmp/hadoop-${user.name}</value></property><property><name>ha.zookeeper.quorum</name><value>wxzz-pc:2181,wxzz-pc0:2181,wxzz-pc1:2181</value></property> </configuration>2. hdfs-site.xml 配置
<configuration><property><name>dfs.replication</name><value>2</value></property><property> <name>dfs.block.size</name> <value>10485760</value> </property><property><name>hadoop.tmp.dir</name><value>/opt/hadoop-2.7.2/tmp/hadoop-${user.name}</value></property><property><name>dfs.namenode.name.dir</name><value>${hadoop.tmp.dir}/dfs/name</value></property><property><name>dfs.datanode.data.dir</name><value>${hadoop.tmp.dir}/dfs/data</value></property><property> <name>dfs.permissions</name> <value>false</value> </property> <property> <name>dfs.permissions.enabled</name> <value>false</value> </property> <property> <name>dfs.webhdfs.enabled</name> <value>true</value> </property><property><name>dfs.nameservices</name><value>myhadoop</value></property><property><name>dfs.ha.namenodes.myhadoop</name><value>nn1,nn2</value></property><property><name>dfs.namenode.rpc-address.myhadoop.nn1</name><value>wxzz-pc:8020</value></property><property><name>dfs.namenode.http-address.myhadoop.nn1</name><value>wxzz-pc:50070</value></property><property><name>dfs.namenode.rpc-address.myhadoop.nn2</name><value>wxzz-pc0:8020</value></property><property><name>dfs.namenode.http-address.myhadoop.nn2</name><value>wxzz-pc0:50070</value></property><property><name>dfs.namenode.servicerpc-address.myhadoop.nn1</name><value>wxzz-pc:53310</value></property><property><name>dfs.namenode.servicerpc-address.cluster1.nn2</name><value>wxzz-pc0:53310</value></property><property><name>dfs.ha.automatic-failover.enabled.cluster1</name><value>true</value></property><property><name>dfs.namenode.shared.edits.dir</name><value>qjournal://wxzz-pc:8485;wxzz-pc0:8485;wxzz-pc1:8485/myhadoop</value></property><property><name>dfs.client.failover.proxy.provider.myhadoop</name> <value>org.apache.hadoop.hdfs.server.namenode.ha.ConfiguredFailoverProxyProvider</value></property><property><name>dfs.journalnode.edits.dir</name><value>/opt/hadoop-2.7.2/journal</value></property><property><name>dfs.ha.fencing.methods</name><value>sshfence</value></property><property><name>dfs.ha.fencing.ssh.private-key-files</name><value>/opt/hadoop-2.7.2/.ssh/id_rsa</value></property><property><name>dfs.ha.fencing.ssh.connect-timeout</name><value>1000</value></property><property><name>dfs.namenode.handler.count</name><value>10</value></property><property><name>dfs.ha.automatic-failover.enabled.myhadoop</name><value>true</value></property> </configuration>3. mapred-site.xml 配置
<configuration><property><name>mapreduce.framework.name</name><value>yarn</value></property><property><name>mapreduce.jobhistory.address</name><value>0.0.0.0:10020</value></property><property><name>mapreduce.jobhistory.webapp.address</name><value>0.0.0.0:19888</value></property> </configuration>4.yarn-site.xml 配置
<configuration><property><name>yarn.resourcemanager.ha.enabled</name><value>true</value></property><property><name>yarn.resourcemanager.cluster-id</name><value>rm-id</value></property><property><name>yarn.resourcemanager.ha.rm-ids</name><value>rm1,rm2</value></property><property><name>yarn.resourcemanager.hostname.rm1</name><value>wxzz-pc</value></property><property><name>yarn.resourcemanager.hostname.rm2</name><value>wxzz-pc0</value></property><property><name>yarn.resourcemanager.zk-address</name><value>wxzz-pc:2181,wxzz-pc0:2181,wxzz-pc1:2181</value></property><property><name>yarn.nodemanager.aux-services</name><value>mapreduce_shuffle</value></property> </configuration>六.服務(wù)啟動
1.在各個Journal Node節(jié)點上,輸入以下命令啟動Journal Node
? ? ? ? ?sbin/hadoop-daemon.sh start journalnode
2.在[nn1]上,進行格式化,并啟動
? ? ? ? ?bin/hdfs namenode -format
? ? ? ? ?sbin/hadoop-daemon.sh start namenode
3.在[nn2]上,同步[nn1]的元數(shù)據(jù)信息,并啟動
? ? ? ? ?bin/hdfs namenode -bootstrapStandby
? ? ? ? ?sbin/hadoop-daemon.sh start namenode
? ?經(jīng)過以上3步,[nn1]和[nn2]均處在standby狀態(tài)
4.[nn1]節(jié)點上,將其轉(zhuǎn)換為active狀態(tài)
? ? ? ? ?bin/hdfs haadmin –transitionToActive --forcemanual nn1
5.在[nn1]上,啟動所有datanode
? ? ? ? ?sbin/hadoop-daemons.sh start datanode
6.在[nn1]上,啟動yarn
? ? ? ? ?sbin/start-yarn.sh
如果要關(guān)閉集群,在[nn1]上輸入sbin/stop-all.sh即可。以后每次啟動的時候,需要按照上面的步驟啟動,不過不需要執(zhí)行2 的格式化操作。
七.運行效果
管理界面:
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命令行效果:
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1.[連載]《C#通訊(串口和網(wǎng)絡(luò))框架的設(shè)計與實現(xiàn)》
2.[開源]C#跨平臺物聯(lián)網(wǎng)通訊框架ServerSuperIO(SSIO)介紹
2.應(yīng)用SuperIO(SIO)和開源跨平臺物聯(lián)網(wǎng)框架ServerSuperIO(SSIO)構(gòu)建系統(tǒng)的整體方案
3.C#工業(yè)物聯(lián)網(wǎng)和集成系統(tǒng)解決方案的技術(shù)路線(數(shù)據(jù)源、數(shù)據(jù)采集、數(shù)據(jù)上傳與接收、ActiveMQ、Mongodb、WebApi、手機App)
5.ServerSuperIO開源地址:https://github.com/wxzz/ServerSuperIO
物聯(lián)網(wǎng)&集成技術(shù)(.NET) QQ群:54256083?
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轉(zhuǎn)載于:https://www.cnblogs.com/lsjwq/p/6145386.html
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