Linux -- 之HDFS實現自動切換HA(全新HDFS)php
1.7及以上 https://blog.csdn.net/meiLin_Ya/article/details/80650945html
系統防火牆關閉java
hadoop01(nn1)--> hadoop01(nn1) 須要免密碼node
hadoop01(nn1)--> hadoop02(nn2) 須要免密碼web
hadoop01(nn1)--> hadoop03(dn) 須要免密碼數據庫
hadoop02(nn2)--> hadoop01(nn1) 須要免密碼apache
hadoop02(nn2)--> hadoop02(nn2) 須要免密碼bootstrap
hadoop02(nn2)--> hadoop03(dn) 須要免密碼app
若是多節點之間所有免密碼更好(生產環境不建議) 默認環境ssh
已有可用zk集羣 https://blog.csdn.net/meiLin_Ya/article/details/80654268
首先咱們要將全部的hadoop刪除乾淨。如/temp /hadoopdata 等等,而後將hadoop的壓縮包導入。你的集羣中的每一個節點也是,都要刪除的。
刪除後解壓hadoop:
tar zxvf hadoop-2.6.0.tar.gz
修改core-site.xml
<configuration> <property> <name>fs.defaultFS</name> <value>hdfs://beiwang</value> </property> <property> <name>hadoop.tmp.dir</name> <value>/home/hadoopdata/tmp</value> </property> <property> <name>io.file.buffer.size</name> <value>4096</value> </property> </configuration>
注意:中文註釋不要帶
<configuration> <!-- 指定hdfs的nameservice爲beiwang,就是那個代理程序,詢問zk集羣哪一個namenode還活着 --> <property> <name>dfs.nameservices</name> <value>beiwang</value> </property> <!—指定hdfs的兩個NameNode都是什麼名字(等會兒下面會配置他們所對應的機器的信息)--> <property> <name>dfs.ha.namenodes.beiwang</name> <value>nn1,nn2</value> </property> <!—NameNode1的rpc通信地址--> <property> <name>dfs.namenode.rpc-address.beiwang.nn1</name> <value> hadoop01:8020</value> </property> <!—NameNode2的rpc通信地址--> <property> <name>dfs.namenode.rpc-address.beiwang.nn2</name> <value> hadoop02:8020</value> </property> <!—NameNode1的web界面地址--> <property> <name>dfs.namenode.http-address.beiwang.nn1</name> <value> hadoop01:50070</value> </property> <!—NameNode2的web界面地址--> <property> <name>dfs.namenode.http-address.beiwang.nn2</name> <value> hadoop02:50070</value> </property> ######若是給一個有數據的HDFS添加HA,此處無需更改,保持原有地址便可##### <!---namenode存放元數據信息的Linux本地地址,這個目錄不須要咱們本身建立-> <property> <name>dfs.namenode.name.dir</name> <value>file:///home/hdfs/name</value> </property> <!—datanode存放用戶提交的大文件的本地Linux地址,這個目錄不須要咱們本身建立--> <property> <name>dfs.datanode.data.dir</name> <value>file:///home/hdfs/data</value> </property> ########################################################### <!—QJM存放共享數據的方式--> <property> <name>dfs.namenode.shared.edits.dir</name> <value>qjournal:// hadoop01:8485; hadoop02:8485; hadoop03:8485/beiwang</value> </property> <!—單個QJM進程(角色)存放本地edits文件的Linux地址--> <property> <name>dfs.journalnode.edits.dir</name> <value>/home/bigdata/hadoop/journal1</value> </property> <!—開啓hdfs的namenode死亡後自動切換--> <property> <name>dfs.ha.automatic-failover.enabled</name> <value>true</value> </property> <!-- 指定zookeeper集羣地址,輔助兩個namenode進行失敗切換 --> <property> <name>ha.zookeeper.quorum</name> <value> hadoop01:2181, hadoop02:2181, hadoop03:2181</value> </property> <!—zkfc程序的主類--> <property> <name>dfs.client.failover.proxy.provider.beiwang</name> <value>org.apache.hadoop.hdfs.server.namenode.ha.ConfiguredFailoverProxyProvider</value> </property> <!—防止多個namenode同時active(腦裂)的方式--> <property> <name>dfs.ha.fencing.methods</name> <value>sshfence</value> </property> <!—指定本機的私鑰所在目錄--> <property> <name>dfs.ha.fencing.ssh.private-key-files</name> <value>/root/.ssh/id_rsa</value> </property> <!—指定ssh通信超時時間--> <property> <name>dfs.ha.fencing.ssh.connect-timeout</name> <value>30000</value> </property> </configuration>
hadoop-env.sh
export JAVA_HOME="/home/bigdata/jdk1.8.0_161"
建一個master文本在hadoop-2.6.0/etc/hadoop/
注意:
新建master文件,該文件中寫 全部namenode主機
hu-hadoop1 hu-hadoop2 hu-hadoop3
slaves:
hu-hadoop1 hu-hadoop2 hu-hadoop3
開啓日誌文件:
hadoop-daemons.sh start journalnode
啓動zookeeper:
zkServer.sh start
而後進行格式化:
hadoop namenode -format
在master上開啓namenode
hadoop-daemon.sh start namenode
在salve11機上 同步元數據信息
hdfs namenode -bootstrapStandby
格式化ZK(在Master上執行便可)
# hdfs zkfc -formatZK
格式化後能夠查看zookeeper存放文件:
啓動dfs:而後再查看zookeeper
start-dfs.sh
進入網頁:
如今咱們來測試下,殺死hu-hadoop2 ,而後看hu-hadoop1是否 能夠從 standby=>active
而後咱們再啓動下剛剛的hu-hadoop2:查看它的狀態
很明確的看出來了吧
而後咱們看看zookeeper
而後如今咱們去殺掉hu-hadoop1:再看zookeeper
固然此時網頁hu-hadoop2又從剛剛的standby==>active
這是爲何呢?
記得咱們前面作了一步 hdfs zkfc -formatZK 這一步就是將hdfs信息記錄到zookeeper,還有hdfs-core.xml中的配置。
這就是zookeeper的強大之處。咱們能夠將zookeeper理解爲數據庫,而它和數據庫又不太是由於他是一個樹形,只有在樹枝的末梢纔會存儲數據。它的大小有1MB,不要小看它的1MB,它的做用比你想象的要強大
再記錄下我運行成功後的配置文件吧
hadoop-env.sh
export JAVA_HOME="/home/bigdata/jdk1.8.0_161"
core-site.xml
<configuration> <property> <name>fs.defaultFS</name> <value>hdfs://huhu</value> </property> <property> <name>hadoop.tmp.dir</name> <value>/home/hadoopdata/tmp</value> </property> <property> <name>io.file.buffer.size</name> <value>4096</value> </property> </configuration>
hdfs-site.xml
<configuration> <property> <name>dfs.nameservices</name> <value>huhu</value> </property> <property> <name>dfs.ha.namenodes.huhu</name> <value>huhu1,huhu2</value> </property> <property> <name>dfs.namenode.rpc-address.huhu.huhu1</name> <value>hu-hadoop1:8020</value> </property> <property> <name>dfs.namenode.rpc-address.huhu.huhu2</name> <value>hu-hadoop2:8020</value> </property> <property> <name>dfs.namenode.http-address.huhu.huhu1</name> <value>hu-hadoop1:50070</value> </property> <property> <name>dfs.namenode.http-address.huhu.huhu2</name> <value>hu-hadoop2:50070</value> </property> <property> <name>dfs.namenode.name.dir</name> <value>file:///home/hdfs/name</value> </property> <property> <name>dfs.datanode.data.dir</name> <value>file:///home/hdfs/data</value> </property> <property> <name>dfs.namenode.shared.edits.dir</name> <value>qjournal://hu-hadoop1:8485;hu-hadoop2:8485;hu-hadoop3:8485/huhu</value> </property> <property> <name>dfs.journalnode.edits.dir</name> <value>/home/bigdata/hadoop/journal1</value> </property> <property> <name>dfs.ha.automatic-failover.enabled</name> <value>true</value> </property> <property> <name>ha.zookeeper.quorum</name> <value>hu-hadoop1:2181,hu-hadoop2:2181,hu-hadoop3:2181</value> </property> <property> <name>dfs.client.failover.proxy.provider.huhu</name> <value>org.apache.hadoop.hdfs.server.namenode.ha.ConfiguredFailoverProxyProvider</value> </property> <property> <name>dfs.ha.fencing.methods</name> <value>sshfence</value> </property> <property> <name>dfs.ha.fencing.ssh.private-key-files</name> <value>/root/.ssh/id_rsa</value> </property> <property> <name>dfs.ha.fencing.ssh.connect-timeout</name> <value>30000</value> </property> </configuration>
mapred-site.xml
<configuration> <property> <name>mapreduce.framework.name</name> <value>yarn</value> <final>true</final> </property> </configuration>
yarn-site.xml
<configuration> <property> <name>yarn.resourcemanager.connect.retry-interval.ms</name> <value>2000</value> </property> <property> <name>yarn.resourcemanager.ha.enabled</name> <value>true</value> </property> <property> <name>yarn.resourcemanager.ha.automatic-failover.enabled</name> <value>true</value> </property> <property> <name>yarn.resourcemanager.ha.automatic-failover.embedded</name> <value>true</value> </property> <property> <name>yarn.resourcemanager.cluster-id</name> <value>beiwangyarn</value> </property> <property> <name>yarn.resourcemanager.ha.rm-ids</name> <value>rm1,rm2</value> </property> <property> <name>yarn.resourcemanager.hostname.rm1</name> <value>hu-hadoop1</value> </property> <property> <name>yarn.resourcemanager.hostname.rm2</name> <value>hu-hadoop2</value> </property> <property> <name>yarn.resourcemanager.scheduler.class</name> <value>org.apache.hadoop.yarn.server.resourcemanager.scheduler.fair.FairScheduler</value> </property> <property> <name>yarn.resourcemanager.recovery.enabled</name> <value>true</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.state-store.address</name> <value>hu-hadoop1:2181,hu-hadoop2:2181,hu-hadoop3:2181</value> </property> <property> <name>yarn.app.mapreduce.am.scheduler.connection.wait.interval-ms</name> <value>5000</value> </property> <property> <name>yarn.resourcemanager.address.rm1</name> <value>hu-hadoop1:8032</value> </property> <property> <name>yarn.resourcemanager.scheduler.address.rm1</name> <value>hu-hadoop1:8030</value> </property> <property> <name>yarn.resourcemanager.webapp.https.address.rm1</name> <value>hu-hadoop1:23189</value> </property> <property> <name>yarn.resourcemanager.webapp.address.rm1</name> <value>hu-hadoop1:8088</value> </property> <property> <name>yarn.resourcemanager.resource-tracker.address.rm1</name> <value>hu-hadoop1:8031</value> </property> <property> <name>yarn.resourcemanager.admin.address.rm1</name> <value>hu-hadoop1:8033</value> </property> <property> <name>yarn.resourcemanager.address.rm2</name> <value>hu-hadoop2:8032</value> </property> <property> <name>yarn.resourcemanager.scheduler.address.rm2</name> <value>hu-hadoop2:8030</value> </property> <property> <name>yarn.resourcemanager.webapp.https.address.rm2</name> <value>hu-hadoop2:23189</value> </property> <property> <name>yarn.resourcemanager.webapp.address.rm2</name> <value>hu-hadoop2:8088</value> </property> <property> <name>yarn.resourcemanager.resource-tracker.address.rm2</name> <value>hu-hadoop2:8031</value> </property> <property> <name>yarn.resourcemanager.admin.address.rm2</name> <value>hu-hadoop2:8033</value> </property> <property> <description>Address where the localizer IPC is.</description> <name>yarn.nodemanager.localizer.address</name> <value>0.0.0.0:23344</value> </property> <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>/tmp/pseudo-dist/yarn/local</value> </property> <name>yarn.nodemanager.log-dirs</name> <value>/tmp/pseudo-dist/yarn/log</value> </property> <property> <name>mapreduce.shuffle.port</name> <value>23080</value> </property> <property> <name>yarn.resourcemanager.zk-address</name> <value>hu-hadoop1:2181,hu-hadoop2:2181,hu-hadoop3:2181</value> </property> </configuration>
master
hu-hadoop1 hu-hadoop2 hu-hadoop3
slaves
hu-hadoop1 hu-hadoop2 hu-hadoop3