一.環境說明html
虛擬機:vmware 11node
操做系統:Ubuntu 16.04git
Hadoop版本:2.7.2github
Zookeeper版本:3.4.9web
二.節點部署說明apache
三.Hosts增長配置bootstrap
sudo gedit /etc/hosts網絡
wxzz-pc、wxzz-pc0、wxzz-pc一、wxzz-pc2均配置以下:app
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上配置框架
Zoo.cfg配置文件內容以下:
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文件分別對應的內容爲:一、二、3,也就是server.X=wxzz-pc:2182:2183,對應X的數值。
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.服務啓動
1.在各個Journal Node節點上,輸入如下命令啓動Journal Node
sbin/hadoop-daemon.sh start journalnode
2.在[nn1]上,進行格式化,並啓動
bin/hdfs namenode -format
sbin/hadoop-daemon.sh start namenode
3.在[nn2]上,同步[nn1]的元數據信息,並啓動
bin/hdfs namenode -bootstrapStandby
sbin/hadoop-daemon.sh start namenode
通過以上3步,[nn1]和[nn2]均處在standby狀態
4.[nn1]節點上,將其轉換爲active狀態
bin/hdfs haadmin –transitionToActive --forcemanual nn1
5.在[nn1]上,啓動全部datanode
sbin/hadoop-daemons.sh start datanode
6.在[nn1]上,啓動yarn
sbin/start-yarn.sh
若是要關閉集羣,在[nn1]上輸入sbin/stop-all.sh便可。之後每次啓動的時候,須要按照上面的步驟啓動,不過不須要執行2 的格式化操做。
七.運行效果
管理界面:
命令行效果:
2.[開源]C#跨平臺物聯網通信框架ServerSuperIO(SSIO)介紹
2.應用SuperIO(SIO)和開源跨平臺物聯網框架ServerSuperIO(SSIO)構建系統的總體方案
3.C#工業物聯網和集成系統解決方案的技術路線(數據源、數據採集、數據上傳與接收、ActiveMQ、Mongodb、WebApi、手機App)
5.ServerSuperIO開源地址:https://github.com/wxzz/ServerSuperIO
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