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hadoop HA 高可用集群部署搭建

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HADOOP HA 介绍

1. 概论

本指南提供了一个HDFS 的高可用性（HA ）功能的概述，以及如何配置和管理HDFS 高可用性(HA) 集群。本文档假定读者具有对HDFS 集群的组件和节点类型具有一定理解。有关详情，请参阅Apache 的HDFS 的架构指南。
http://hadoop.apache.org/common/docs/current/hdfs_design.html


2. 背景

CDH4 之前，在HDFS 集群中NameNode 存在单点故障（SPOF ）。对于只有一个NameNode 的集群，如果NameNode 机器出现故障，那么整个集群将无法使用，直到NameNode 重新启动。
NameNode 主要在以下两个方面影响HDFS 集群:
(1). NameNode 机器发生意外，比如宕机，集群将无法使用，直到管理员重启NameNode
(2). NameNode 机器需要升级，包括软件、硬件升级，此时集群也将无法使用
HDFS 的HA 功能通过配置Active/Standby 两个NameNodes 实现在集群中对NameNode 的热备来解决上述问题。如果出现故障，如机器崩溃或机器需要升级维护，这时可通过此种方式将NameNode 很快的切换到另外一台机器。


3. 架构

在一个典型的HDFS(HA) 集群中，使用两台单独的机器配置为NameNodes 。在任何时间点，确保NameNodes 中只有一个处于Active 状态，其他的处在Standby 状态。其中ActiveNameNode 负责集群中的所有客户端操作，StandbyNameNode 仅仅充当备机，保证一旦ActiveNameNode 出现问题能够快速切换。
为了保证Standby 节点与Active 节点的状态保持同步，目前是通过两个节点同时访问一个共享的存储设备( 如NFS) 来实现的，在以后的版本中可能会做进一步的改进。
当Active 节点的namespace 发生改变时，存储在共享目录中的日志文件也会被修改，Standby 节点监测到日志变化后，将其作用到自身的namespace 。当Active 节点发生故障需要进行切换时，Standby 节点由Standby 状态转换为Active 状态前将会把所有未读日志作用到自身的namespace 以确保自身的namespace 与主节点的namespace 保持一致。
为了实现快速切换，Standby 节点获取集群的最新文件块信息也是很有必要的。为了实现这一目标，DataNode 需要配置NameNodes 的位置，并同时给他们发送文件块信息以及心跳检测。
任意时间只有一个ActiveNameNode 对于HDFS(HA) 集群的正常运行至关重要，否则两者的namespace 将不能保持同步，面临数据丢失和其它问题的危险性。为了防止出现这种情况，管理员必须为共享存储配置至少一个安全机制。这种机制应该保证: 在切换期间，如果不能证实当前Active 节点已经改变了状态，那么此机制应切断当前Active 节点对共享存储的访问，这样可以防止在切换期间当前Active 节点继续对namespace 进行修改，确保新的Active 节点能够安全的切换.

系统环境

hadoop 2.5.0 zookeeper 3.4.5 JDK 1.7 

集群节点

m1192.168.2.100namenode resourcemanager zookeepers1192.168.2.101standbyNameNode datanode nodeManager zookeepers2192.168.2.102datanode nodeManager zookeeper

配置zookeeper

配置HADOOP

配置HADOOP HA 主要需要修改两个配置文件：core-site.xml / hdfs-site.xml 

hdfs-site.xml

<configuration><!--命名空间设置ns1--><property><name>dfs.nameservices</name><value>mycluster</value></property><!--namenodes节点ID:nn1,nn2(配置在命名空间mycluster下)--><property><name>dfs.ha.namenodes.mycluster</name><value>nn1,nn2</value></property><!--nn1,nn2节点地址配置--><property><name>dfs.namenode.rpc-address.mycluster.nn1</name><value>nameNode:8020</value></property><property><name>dfs.namenode.rpc-address.mycluster.nn2</name><value>dataNode1:8020</value></property><!--nn1,nn2节点WEB地址配置--><property><name>dfs.namenode.http-address.mycluster.nn1</name><value>nameNode:50070</value></property><property><name>dfs.namenode.http-address.mycluster.nn2</name><value>dataNode1:50070</value></property><property><name>dfs.namenode.shared.edits.dir</name><value>qjournal://nameNode:8485;dataNode1:8485;dataNode2:8485/mycluster</value></property><property><name>dfs.journalnode.edits.dir</name><value>/home/hadoop/hadoop/src/hadoop-2.5.0/tmp/dfs/journalnode</value></property><property><name>dfs.client.failover.proxy.provider.mycluster</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>/home/hadoop/.ssh/id_dsa</value></property><!--启用自动故障转移--><property><name>dfs.ha.automatic-failover.enabled</name><value>true</value></property><property><name>dfs.replication.max</name><value>32767</value></property></configuration>


core-site.xml
<configuration> <property> <!-- 配置 hadoop NameNode ip地址 ,由于我们配置的 HA 那么有两个namenode 所以这里配置的地址必须是动态的-->  <name>fs.defaultFS</name>  <value>hdfs://mycluster</value> </property><property>  <name>dfs.nameservices</name>  <value>mycluster</value> </property><property><!-- 整合 Zookeeper -->  <name>ha.zookeeper.quorum</name>  <value>nameNode:2181,dataNode1:2181,dataNode2:2181</value> </property>        <property>        <!-- 配置hadoop缓存地址 -->                <name>hadoop.tmp.dir</name>                <value>/home/hadoop/hadoop/src/hadoop-2.5.0/tmp</value>                <description></description>        </property></configuration>


如何使用
启动zookeeper
在m1,s1,s2所有机器上执行,下面的代码是在m1上执行的示例

root@s1:/home/hadoop# /home/hadoop/zookeeper-3.4.5/bin/zkServer.sh startJMX enabled by defaultUsing config: /home/hadoop/zookeeper-3.4.5/bin/../conf/zoo.cfgStarting zookeeper ... STARTEDroot@s1:/home/hadoop# /home/hadoop/zookeeper-3.4.5/bin/zkServer.sh statusJMX enabled by defaultUsing config: /home/hadoop/zookeeper-3.4.5/bin/../conf/zoo.cfgMode: leaderroot@s1:/home/hadoop#

测试zookeeper是否启动成功，看下面第29行高亮处，表示成功。
root@m1:/home/hadoop# /home/hadoop/zookeeper-3.4.5/bin/zkCli.shConnecting to localhost:21812014-07-27 00:27:16,621 [myid:] - INFO  [main:Environment@100] - Client environment:zookeeper.version=3.4.5-1392090, built on 09/30/2012 17:52 GMT2014-07-27 00:27:16,628 [myid:] - INFO  [main:Environment@100] - Client environment:host.name=m12014-07-27 00:27:16,628 [myid:] - INFO  [main:Environment@100] - Client environment:java.version=1.7.0_652014-07-27 00:27:16,629 [myid:] - INFO  [main:Environment@100] - Client environment:java.vendor=Oracle Corporation2014-07-27 00:27:16,629 [myid:] - INFO  [main:Environment@100] - Client environment:java.home=/usr/lib/jvm/java-7-oracle/jre2014-07-27 00:27:16,630 [myid:] - INFO  [main:Environment@100] - Client environment:java.class.path=/home/hadoop/zookeeper-3.4.5/bin/../build/classes:/home/hadoop/zookeeper-3.4.5/bin/../build/lib/*.jar:/home/hadoop/zookeeper-3.4.5/bin/../lib/slf4j-log4j12-1.6.1.jar:/home/hadoop/zookeeper-3.4.5/bin/../lib/slf4j-api-1.6.1.jar:/home/hadoop/zookeeper-3.4.5/bin/../lib/netty-3.2.2.Final.jar:/home/hadoop/zookeeper-3.4.5/bin/../lib/log4j-1.2.15.jar:/home/hadoop/zookeeper-3.4.5/bin/../lib/jline-0.9.94.jar:/home/hadoop/zookeeper-3.4.5/bin/../zookeeper-3.4.5.jar:/home/hadoop/zookeeper-3.4.5/bin/../src/java/lib/*.jar:/home/hadoop/zookeeper-3.4.5/bin/../conf:/usr/lib/jvm/java-7-oracle/lib2014-07-27 00:27:16,630 [myid:] - INFO  [main:Environment@100] - Client environment:java.library.path=:/usr/local/lib:/usr/java/packages/lib/amd64:/usr/lib64:/lib64:/lib:/usr/lib2014-07-27 00:27:16,631 [myid:] - INFO  [main:Environment@100] - Client environment:java.io.tmpdir=/tmp2014-07-27 00:27:16,631 [myid:] - INFO  [main:Environment@100] - Client environment:java.compiler=<NA>2014-07-27 00:27:16,632 [myid:] - INFO  [main:Environment@100] - Client environment:os.name=Linux2014-07-27 00:27:16,632 [myid:] - INFO  [main:Environment@100] - Client environment:os.arch=amd642014-07-27 00:27:16,632 [myid:] - INFO  [main:Environment@100] - Client environment:os.version=3.11.0-15-generic2014-07-27 00:27:16,633 [myid:] - INFO  [main:Environment@100] - Client environment:user.name=root2014-07-27 00:27:16,633 [myid:] - INFO  [main:Environment@100] - Client environment:user.home=/root2014-07-27 00:27:16,634 [myid:] - INFO  [main:Environment@100] - Client environment:user.dir=/home/hadoop2014-07-27 00:27:16,636 [myid:] - INFO  [main:ZooKeeper@438] - Initiating client connection, connectString=localhost:2181 sessionTimeout=30000 watcher=org.apache.zookeeper.ZooKeeperMain$MyWatcher@19b1ebe5Welcome to ZooKeeper!2014-07-27 00:27:16,672 [myid:] - INFO  [main-SendThread(localhost:2181):ClientCnxn$SendThread@966] - Opening socket connection to server localhost/127.0.0.1:2181. Will not attempt to authenticate using SASL (unknown error)2014-07-27 00:27:16,685 [myid:] - INFO  [main-SendThread(localhost:2181):ClientCnxn$SendThread@849] - Socket connection established to localhost/127.0.0.1:2181, initiating sessionJLine support is enabled2014-07-27 00:27:16,719 [myid:] - INFO  [main-SendThread(localhost:2181):ClientCnxn$SendThread@1207] - Session establishment complete on server localhost/127.0.0.1:2181, sessionid = 0x147737cd5d30000, negotiated timeout = 30000WATCHER::WatchedEvent state:SyncConnected type:None path:null[zk: localhost:2181(CONNECTED) 0] ls /[zookeeper][zk: localhost:2181(CONNECTED) 1]

在m1上格式化zookeeper，第33行的日志表示创建成功。
  1. root@m1:/home/hadoop# /home/hadoop/hadoop-2.2.0/bin/hdfs zkfc -formatZK
  2. 14/07/2700:31:59 INFO tools.DFSZKFailoverController:Failover controller configuredforNameNodeNameNode at m1/192.168.1.50:9000
  3. 14/07/2700:32:00 INFO zookeeper.ZooKeeper:Client environment:zookeeper.version=3.4.5-1392090, built on 09/30/201217:52 GMT
  4. 14/07/2700:32:00 INFO zookeeper.ZooKeeper:Client environment:host.name=m1
  5. 14/07/2700:32:00 INFO zookeeper.ZooKeeper:Client environment:java.version=1.7.0_65
  6. 14/07/2700:32:00 INFO zookeeper.ZooKeeper:Client environment:java.vendor=OracleCorporation
  7. 14/07/2700:32:00 INFO zookeeper.ZooKeeper:Client environment:java.home=/usr/lib/jvm/java-7-oracle/jre
  8. 14/07/2700:32:00 INFO zookeeper.ZooKeeper:Client environment:java.class.path=/home/hadoop/hadoop-2.2.0/etc/hadoop:/home/hadoop/hadoop-2.2.0/share/hadoop/common/lib/guava-11.0.2.jar:/home/hadoop/hadoop-2.2.0/share/hadoop/common/lib/commons-codec-1.4.jar:/home/hadoop/hadoop-2.2.0/share/hadoop/common/lib/hadoop-annotations-2.2.0.jar:/home/hadoop/hadoop-2.2.0/share/hadoop/common/lib/slf4j-api-1.7.5.jar:/home/hadoop/hadoop-2.2.0/share/hadoop/common/lib/commons-net-3.1.jar:/home/hadoop/hadoop-2.2.0/share/hadoop/common/lib/paranamer-2.3.jar:/home/hadoop/hadoop-2.2.0/share/hadoop/common/lib/snappy-java-1.0.4.1.jar:/home/hadoop/hadoop-2.2.0/share/hadoop/common/lib/commons-beanutils-core-1.8.0.jar:/home/hadoop/hadoop-2.2.0/share/hadoop/common/lib/jasper-compiler-5.5.23.jar:/home/hadoop/hadoop-2.2.0/share/hadoop/common/lib/commons-math-2.1.jar:/home/hadoop/hadoop-2.2.0/share/hadoop/common/lib/commons-lang-2.5.jar:/home/hadoop/hadoop-2.2.0/share/hadoop/common/lib/servlet-api-2.5.jar:/home/hadoop/hadoop-2.2.0/share/hadoop/common/lib/commons-logging-1.1.1.jar:/home/hadoop/hadoop-2.2.0/share/hadoop/common/lib/log4j-1.2.17.jar:/home/hadoop/hadoop-2.2.0/share/hadoop/common/lib/jasper-runtime-5.5.23.jar:/home/hadoop/hadoop-2.2.0/share/hadoop/common/lib/protobuf-java-2.5.0.jar:/home/hadoop/hadoop-2.2.0/share/hadoop/common/lib/mockito-all-1.8.5.jar:/home/hadoop/hadoop-2.2.0/share/hadoop/common/lib/hadoop-auth-2.2.0.jar:/home/hadoop/hadoop-2.2.0/share/hadoop/common/lib/jackson-core-asl-1.8.8.jar:/home/hadoop/hadoop-2.2.0/share/hadoop/common/lib/commons-digester-1.8.jar:/home/hadoop/hadoop-2.2.0/share/hadoop/common/lib/jsp-api-2.1.jar:/home/hadoop/hadoop-2.2.0/share/hadoop/common/lib/jersey-core-1.9.jar:/home/hadoop/hadoop-2.2.0/share/hadoop/common/lib/jettison-1.1.jar:/home/hadoop/hadoop-2.2.0/share/hadoop/common/lib/xmlenc-0.52.jar:/home/hadoop/hadoop-2.2.0/share/hadoop/common/lib/netty-3.6.2.Final.jar:/home/hadoop/hadoop-2.2.0/share/hadoop/common/lib/commons-httpclient-3.1.jar:/home/hadoop/hadoop-2.2.0/share/hadoop/common/lib/commons-io-2.1.jar:/home/hadoop/hadoop-2.2.0/share/hadoop/common/lib/jsch-0.1.42.jar:/home/hadoop/hadoop-2.2.0/share/hadoop/common/lib/commons-beanutils-1.7.0.jar:/home/hadoop/hadoop-2.2.0/share/hadoop/common/lib/commons-compress-1.4.1.jar:/home/hadoop/hadoop-2.2.0/share/hadoop/common/lib/jackson-jaxrs-1.8.8.jar:/home/hadoop/hadoop-2.2.0/share/hadoop/common/lib/jackson-mapper-asl-1.8.8.jar:/home/hadoop/hadoop-2.2.0/share/hadoop/common/lib/junit-4.8.2.jar:/home/hadoop/hadoop-2.2.0/share/hadoop/common/lib/jetty-6.1.26.jar:/home/hadoop/hadoop-2.2.0/share/hadoop/common/lib/commons-collections-3.2.1.jar:/home/hadoop/hadoop-2.2.0/share/hadoop/common/lib/jsr305-1.3.9.jar:/home/hadoop/hadoop-2.2.0/share/hadoop/common/lib/jackson-xc-1.8.8.jar:/home/hadoop/hadoop-2.2.0/share/hadoop/common/lib/asm-3.2.jar:/home/hadoop/hadoop-2.2.0/share/hadoop/common/lib/jersey-json-1.9.jar:/home/hadoop/hadoop-2.2.0/share/hadoop/common/lib/stax-api-1.0.1.jar:/home/hadoop/hadoop-2.2.0/share/hadoop/common/lib/jets3t-0.6.1.jar:/home/hadoop/hadoop-2.2.0/share/hadoop/common/lib/avro-1.7.4.jar:/home/hadoop/hadoop-2.2.0/share/hadoop/common/lib/commons-el-1.0.jar:/home/hadoop/hadoop-2.2.0/share/hadoop/common/lib/commons-cli-1.2.jar:/home/hadoop/hadoop-2.2.0/share/hadoop/common/lib/commons-configuration-1.6.jar:/home/hadoop/hadoop-2.2.0/share/hadoop/common/lib/jersey-server-1.9.jar:/home/hadoop/hadoop-2.2.0/share/hadoop/common/lib/jetty-util-6.1.26.jar:/home/hadoop/hadoop-2.2.0/share/hadoop/common/lib/activation-1.1.jar:/home/hadoop/hadoop-2.2.0/share/hadoop/common/lib/jaxb-api-2.2.2.jar:/home/hadoop/hadoop-2.2.0/share/hadoop/common/lib/slf4j-log4j12-1.7.5.jar:/home/hadoop/hadoop-2.2.0/share/hadoop/common/lib/zookeeper-3.4.5.jar:/home/hadoop/hadoop-2.2.0/share/hadoop/common/lib/jaxb-impl-2.2.3-1.jar:/home/hadoop/hadoop-2.2.0/share/hadoop/common/lib/xz-1.0.jar:/home/hadoop/hadoop-2.2.0/share/hadoop/common/hadoop-nfs-2.2.0.jar:/home/hadoop/hadoop-2.2.0/share/hadoop/common/hadoop-common-2.2.0.jar:/home/hadoop/hadoop-2.2.0/share/hadoop/common/hadoop-common-2.2.0-tests.jar:/home/hadoop/hadoop-2.2.0/share/hadoop/hdfs:/home/hadoop/hadoop-2.2.0/share/hadoop/hdfs/lib/guava-11.0.2.jar:/home/hadoop/hadoop-2.2.0/share/hadoop/hdfs/lib/commons-codec-1.4.jar:/home/hadoop/hadoop-2.2.0/share/hadoop/hdfs/lib/commons-lang-2.5.jar:/home/hadoop/hadoop-2.2.0/share/hadoop/hdfs/lib/servlet-api-2.5.jar:/home/hadoop/hadoop-2.2.0/share/hadoop/hdfs/lib/commons-logging-1.1.1.jar:/home/hadoop/hadoop-2.2.0/share/hadoop/hdfs/lib/log4j-1.2.17.jar:/home/hadoop/hadoop-2.2.0/share/hadoop/hdfs/lib/jasper-runtime-5.5.23.jar:/home/hadoop/hadoop-2.2.0/share/hadoop/hdfs/lib/protobuf-java-2.5.0.jar:/home/hadoop/hadoop-2.2.0/share/hadoop/hdfs/lib/jackson-core-asl-1.8.8.jar:/home/hadoop/hadoop-2.2.0/share/hadoop/hdfs/lib/jsp-api-2.1.jar:/home/hadoop/hadoop-2.2.0/share/hadoop/hdfs/lib/jersey-core-1.9.jar:/home/hadoop/hadoop-2.2.0/share/hadoop/hdfs/lib/xmlenc-0.52.jar:/home/hadoop/hadoop-2.2.0/share/hadoop/hdfs/lib/netty-3.6.2.Final.jar:/home/hadoop/hadoop-2.2.0/share/hadoop/hdfs/lib/commons-io-2.1.jar:/home/hadoop/hadoop-2.2.0/share/hadoop/hdfs/lib/jackson-mapper-asl-1.8.8.jar:/home/hadoop/hadoop-2.2.0/share/hadoop/hdfs/lib/jetty-6.1.26.jar:/home/hadoop/hadoop-2.2.0/share/hadoop/hdfs/lib/jsr305-1.3.9.jar:/home/hadoop/hadoop-2.2.0/share/hadoop/hdfs/lib/asm-3.2.jar:/home/hadoop/hadoop-2.2.0/share/hadoop/hdfs/lib/commons-el-1.0.jar:/home/hadoop/hadoop-2.2.0/share/hadoop/hdfs/lib/commons-cli-1.2.jar:/home/hadoop/hadoop-2.2.0/share/hadoop/hdfs/lib/jersey-server-1.9.jar:/home/hadoop/hadoop-2.2.0/share/hadoop/hdfs/lib/commons-daemon-1.0.13.jar:/home/hadoop/hadoop-2.2.0/share/hadoop/hdfs/lib/jetty-util-6.1.26.jar:/home/hadoop/hadoop-2.2.0/share/hadoop/hdfs/hadoop-hdfs-2.2.0.jar:/home/hadoop/hadoop-2.2.0/share/hadoop/hdfs/hadoop-hdfs-nfs-2.2.0.jar:/home/hadoop/hadoop-2.2.0/share/hadoop/hdfs/hadoop-hdfs-2.2.0-tests.jar:/home/hadoop/hadoop-2.2.0/share/hadoop/yarn/lib/hamcrest-core-1.1.jar:/home/hadoop/hadoop-2.2.0/share/hadoop/yarn/lib/hadoop-annotations-2.2.0.jar:/home/hadoop/hadoop-2.2.0/share/hadoop/yarn/lib/jersey-guice-1.9.jar:/home/hadoop/hadoop-2.2.0/share/hadoop/yarn/lib/paranamer-2.3.jar:/home/hadoop/hadoop-2.2.0/share/hadoop/yarn/lib/guice-servlet-3.0.jar:/home/hadoop/hadoop-2.2.0/share/hadoop/yarn/lib/snappy-java-1.0.4.1.jar:/home/hadoop/hadoop-2.2.0/share/hadoop/yarn/lib/log4j-1.2.17.jar:/home/hadoop/hadoop-2.2.0/share/hadoop/yarn/lib/protobuf-java-2.5.0.jar:/home/hadoop/hadoop-2.2.0/share/hadoop/yarn/lib/jackson-core-asl-1.8.8.jar:/home/hadoop/hadoop-2.2.0/share/hadoop/yarn/lib/guice-3.0.jar:/home/hadoop/hadoop-2.2.0/share/hadoop/yarn/lib/jersey-core-1.9.jar:/home/hadoop/hadoop-2.2.0/share/hadoop/yarn/lib/netty-3.6.2.Final.jar:/home/hadoop/hadoop-2.2.0/share/hadoop/yarn/lib/junit-4.10.jar:/home/hadoop/hadoop-2.2.0/share/hadoop/yarn/lib/commons-io-2.1.jar:/home/hadoop/hadoop-2.2.0/share/hadoop/yarn/lib/commons-compress-1.4.1.jar:/home/hadoop/hadoop-2.2.0/share/hadoop/yarn/lib/jackson-mapper-asl-1.8.8.jar:/home/hadoop/hadoop-2.2.0/share/hadoop/yarn/lib/javax.inject-1.jar:/home/hadoop/hadoop-2.2.0/share/hadoop/yarn/lib/aopalliance-1.0.jar:/home/hadoop/hadoop-2.2.0/share/hadoop/yarn/lib/asm-3.2.jar:/home/hadoop/hadoop-2.2.0/share/hadoop/yarn/lib/avro-1.7.4.jar:/home/hadoop/hadoop-2.2.0/share/hadoop/yarn/lib/jersey-server-1.9.jar:/home/hadoop/hadoop-2.2.0/share/hadoop/yarn/lib/xz-1.0.jar:/home/hadoop/hadoop-2.2.0/share/hadoop/yarn/hadoop-yarn-server-nodemanager-2.2.0.jar:/home/hadoop/hadoop-2.2.0/share/hadoop/yarn/hadoop-yarn-client-2.2.0.jar:/home/hadoop/hadoop-2.2.0/share/hadoop/yarn/hadoop-yarn-applications-unmanaged-am-launcher-2.2.0.jar:/home/hadoop/hadoop-2.2.0/share/hadoop/yarn/hadoop-yarn-server-tests-2.2.0.jar:/home/hadoop/hadoop-2.2.0/share/hadoop/yarn/hadoop-yarn-common-2.2.0.jar:/home/hadoop/hadoop-2.2.0/share/hadoop/yarn/hadoop-yarn-server-common-2.2.0.jar:/home/hadoop/hadoop-2.2.0/share/hadoop/yarn/hadoop-yarn-server-resourcemanager-2.2.0.jar:/home/hadoop/hadoop-2.2.0/share/hadoop/yarn/hadoop-yarn-api-2.2.0.jar:/home/hadoop/hadoop-2.2.0/share/hadoop/yarn/hadoop-yarn-server-web-proxy-2.2.0.jar:/home/hadoop/hadoop-2.2.0/share/hadoop/yarn/hadoop-yarn-site-2.2.0.jar:/home/hadoop/hadoop-2.2.0/share/hadoop/yarn/hadoop-yarn-applications-distributedshell-2.2.0.jar:/home/hadoop/hadoop-2.2.0/share/hadoop/mapreduce/lib/hamcrest-core-1.1.jar:/home/hadoop/hadoop-2.2.0/share/hadoop/mapreduce/lib/hadoop-annotations-2.2.0.jar:/home/hadoop/hadoop-2.2.0/share/hadoop/mapreduce/lib/jersey-guice-1.9.jar:/home/hadoop/hadoop-2.2.0/share/hadoop/mapreduce/lib/paranamer-2.3.jar:/home/hadoop/hadoop-2.2.0/share/hadoop/mapreduce/lib/guice-servlet-3.0.jar:/home/hadoop/hadoop-2.2.0/share/hadoop/mapreduce/lib/snappy-java-1.0.4.1.jar:/home/hadoop/hadoop-2.2.0/share/hadoop/mapreduce/lib/log4j-1.2.17.jar:/home/hadoop/hadoop-2.2.0/share/hadoop/mapreduce/lib/protobuf-java-2.5.0.jar:/home/hadoop/hadoop-2.2.0/share/hadoop/mapreduce/lib/jackson-core-asl-1.8.8.jar:/home/hadoop/hadoop-2.2.0/share/hadoop/mapreduce/lib/guice-3.0.jar:/home/hadoop/hadoop-2.2.0/share/hadoop/mapreduce/lib/jersey-core-1.9.jar:/home/hadoop/hadoop-2.2.0/share/hadoop/mapreduce/lib/netty-3.6.2.Final.jar:/home/hadoop/hadoop-2.2.0/share/hadoop/mapreduce/lib/junit-4.10.jar:/home/hadoop/hadoop-2.2.0/share/hadoop/mapreduce/lib/commons-io-2.1.jar:/home/hadoop/hadoop-2.2.0/share/hadoop/mapreduce/lib/commons-compress-1.4.1.jar:/home/hadoop/hadoop-2.2.0/share/hadoop/mapreduce/lib/jackson-mapper-asl-1.8.8.jar:/home/hadoop/hadoop-2.2.0/share/hadoop/mapreduce/lib/javax.inject-1.jar:/home/hadoop/hadoop-2.2.0/share/hadoop/mapreduce/lib/aopalliance-1.0.jar:/home/hadoop/hadoop-2.2.0/share/hadoop/mapreduce/lib/asm-3.2.jar:/home/hadoop/hadoop-2.2.0/share/hadoop/mapreduce/lib/avro-1.7.4.jar:/home/hadoop/hadoop-2.2.0/share/hadoop/mapreduce/lib/jersey-server-1.9.jar:/home/hadoop/hadoop-2.2.0/share/hadoop/mapreduce/lib/xz-1.0.jar:/home/hadoop/hadoop-2.2.0/share/hadoop/mapreduce/hadoop-mapreduce-client-common-2.2.0.jar:/home/hadoop/hadoop-2.2.0/share/hadoop/mapreduce/hadoop-mapreduce-client-jobclient-2.2.0-tests.jar:/home/hadoop/hadoop-2.2.0/share/hadoop/mapreduce/hadoop-mapreduce-client-hs-plugins-2.2.0.jar:/home/hadoop/hadoop-2.2.0/share/hadoop/mapreduce/hadoop-mapreduce-client-jobclient-2.2.0.jar:/home/hadoop/hadoop-2.2.0/share/hadoop/mapreduce/hadoop-mapreduce-client-shuffle-2.2.0.jar:/home/hadoop/hadoop-2.2.0/share/hadoop/mapreduce/hadoop-mapreduce-client-app-2.2.0.jar:/home/hadoop/hadoop-2.2.0/share/hadoop/mapreduce/hadoop-mapreduce-client-hs-2.2.0.jar:/home/hadoop/hadoop-2.2.0/share/hadoop/mapreduce/hadoop-mapreduce-examples-2.2.0.jar:/home/hadoop/hadoop-2.2.0/share/hadoop/mapreduce/hadoop-mapreduce-client-core-2.2.0.jar:/home/hadoop/hadoop-2.2.0/contrib/capacity-scheduler/*.jar
  9. 14/07/27 00:32:00 INFO zookeeper.ZooKeeper: Client environment:java.library.path=/home/hadoop/hadoop-2.2.0/lib/native
  10. 14/07/27 00:32:00 INFO zookeeper.ZooKeeper: Client environment:java.io.tmpdir=/tmp
  11. 14/07/27 00:32:00 INFO zookeeper.ZooKeeper: Client environment:java.compiler=<NA>
  12. 14/07/27 00:32:00 INFO zookeeper.ZooKeeper: Client environment:os.name=Linux
  13. 14/07/27 00:32:00 INFO zookeeper.ZooKeeper: Client environment:os.arch=amd64
  14. 14/07/27 00:32:00 INFO zookeeper.ZooKeeper: Client environment:os.version=3.11.0-15-generic
  15. 14/07/27 00:32:00 INFO zookeeper.ZooKeeper: Client environment:user.name=root
  16. 14/07/27 00:32:00 INFO zookeeper.ZooKeeper: Client environment:user.home=/root
  17. 14/07/27 00:32:00 INFO zookeeper.ZooKeeper: Client environment:user.dir=/home/hadoop
  18. 14/07/27 00:32:00 INFO zookeeper.ZooKeeper: Initiating client connection, connectString=m1:2181,m2:2181,s1:2181,s2:2181 sessionTimeout=5000 watcher=org.apache.hadoop.ha.ActiveStandbyElector$WatcherWithClientRef@5990054a
  19. 14/07/27 00:32:00 INFO zookeeper.ClientCnxn: Opening socket connection to server m1/192.168.1.50:2181. Will not attempt to authenticate using SASL (unknown error)
  20. 14/07/27 00:32:00 INFO zookeeper.ClientCnxn: Socket connection established to m1/192.168.1.50:2181, initiating session
  21. 14/07/27 00:32:00 INFO zookeeper.ClientCnxn: Session establishment complete on server m1/192.168.1.50:2181, sessionid = 0x147737cd5d30001, negotiated timeout = 5000
  22. ===============================================
  23. The configured parent znode /hadoop-ha/mycluster already exists.
  24. Are you sure you want to clear all failover information from
  25. ZooKeeper?
  26. WARNING: Before proceeding, ensure that all HDFS services and
  27. failover controllers are stopped!
  28. ===============================================
  29. Proceed formatting /hadoop-ha/mycluster? (Y or N) 14/07/27 00:32:00 INFO ha.ActiveStandbyElector: Session connected.
  30. y
  31. 14/07/27 00:32:13 INFO ha.ActiveStandbyElector: Recursively deleting /hadoop-ha/mycluster from ZK...
  32. 14/07/27 00:32:13 INFO ha.ActiveStandbyElector: Successfully deleted /hadoop-ha/mycluster from ZK.
  33. 14/07/27 00:32:13 INFO ha.ActiveStandbyElector: Successfully created /hadoop-ha/mycluster in ZK.
  34. 14/07/27 00:32:13 INFO zookeeper.ClientCnxn: EventThread shut down
  35. 14/07/27 00:32:13 INFO zookeeper.ZooKeeper: Session: 0x147737cd5d30001 closed
  36. root@m1:/home/hadoop#

5)验证zkfc是否格式化成功，如果多了一个hadoop-ha包就是成功了。
  1. root@m1:/home/hadoop# /home/hadoop/zookeeper-3.4.5/bin/zkCli.sh
  2. [zk: localhost:2181(CONNECTED)0] ls/
  3. [hadoop-ha, zookeeper]
  4. [zk: localhost:2181(CONNECTED)1]
启动JournalNode集群
1)依次在m1,s1,s2上面执行
  1. root@m1:/home/hadoop# /home/hadoop/hadoop-2.2.0/sbin/hadoop-daemon.sh start journalnode
  2. starting journalnode, logging to /home/hadoop/hadoop-2.2.0/logs/hadoop-root-journalnode-m1.out
  3. root@m1:/home/hadoop# jps
  4. 2884 JournalNode
  5. 2553 QuorumPeerMain
  6. 2922 Jps
  7. root@m1:/home/hadoop#
　　　　2)格式化集群的一个NameNode（m1），有两种方法，我使用的是第一种 
　　　　方法一：
  1. root@m1:/home/hadoop# /home/hadoop/hadoop-2.2.0/bin/hdfs namenode –format
　　　　方法二：
  1. root@m1:/home/hadoop/hadoop-2.2.0/bin/hdfs namenode -format -clusterId m1
　　　　3)在m1上启动刚才格式化的 namenode
  1. root@m1:/home/hadoop# /home/hadoop/hadoop-2.2.0/sbin/hadoop-daemon.sh start namenode
　　　　执行命令后，浏览:http://m1:50070/dfshealth.jsp可以看到m1的状态 
　　　　 
　　　　 
　　4)在s1机器上，将m1的数据复制到s1上来,在s1上执行
  1. root@s1:/home/hadoop# /home/hadoop/hadoop-2.2.0/bin/hdfs namenode –bootstrapStandby
　　　　5)启动s1上的namenode，执行命令后
  1. root@s1:/home/hadoop# /home/hadoop/hadoop-2.2.0/sbin/hadoop-daemon.sh start namenode
　　　　浏览:http://s1:50070/dfshealth.jsp可以看到s1的状态。这个时候在网址上可以发现m1和m2的状态都是standby。 
启动所有的datanode，在m1上执行
  1. root@m1:/home/hadoop# /home/hadoop/hadoop-2.2.0/sbin/hadoop-daemons.sh start datanode
  2. s2: starting datanode, logging to /home/hadoop/hadoop-2.2.0/logs/hadoop-root-datanode-s2.out
  3. s1: starting datanode, logging to /home/hadoop/hadoop-2.2.0/logs/hadoop-root-datanode-s1.out
  4. root@m1:/home/hadoop#
启动yarn，在m1上执行以下命令
  1. root@m1:/home/hadoop# /home/hadoop/hadoop-2.2.0/sbin/start-yarn.sh
  2. starting yarn daemons
  3. starting resourcemanager, logging to /home/hadoop/hadoop-2.2.0/logs/yarn-root-resourcemanager-m1.out
  4. s1: starting nodemanager, logging to /home/hadoop/hadoop-2.2.0/logs/yarn-root-nodemanager-s1.out
  5. s2: starting nodemanager, logging to /home/hadoop/hadoop-2.2.0/logs/yarn-root-nodemanager-s2.out
  6. root@m1:/home/hadoop#
然后浏览:http://m1:8088/cluster, 可以看到效果 
启动 ZooKeeperFailoverCotroller，在m1,m2机器上依次执行以下命令，这个时候再浏览50070端口，可以发现m1变成active状态了，而m2还是standby状态
  1. root@m1:/home/hadoop# /home/hadoop/hadoop-2.2.0/sbin/hadoop-daemon.sh start zkfc
  2. starting zkfc, logging to /home/hadoop/hadoop-2.2.0/logs/hadoop-root-zkfc-m1.out
  3. root@m1:/home/hadoop#
测试HDFS是否可用

  1. root@m1:/home/hadoop/hadoop-2.2.0/bin# /home/hadoop/hadoop-2.2.0/bin/hdfs dfs -ls /
测试YARN是否可用,我们来做一个经典的例子，统计刚才放入input下面的hadoop.cmd的单词频率
  1. root@m1:/home/hadoop/hadoop-2.2.0/bin# /home/hadoop/hadoop-2.2.0/bin/hadoop jar /home/hadoop/hadoop-2.2.0/share/hadoop/mapreduce/hadoop-mapreduce-examples-2.2.0.jar wordcount /input /output
  2. 14/07/27 01:22:41 INFO client.RMProxy: Connecting to ResourceManager at m1/192.168.1.50:8032
  3. 14/07/27 01:22:43 INFO input.FileInputFormat: Total input paths to process : 1
  4. 14/07/27 01:22:44 INFO mapreduce.JobSubmitter: number of splits:1
  5. 14/07/27 01:22:44 INFO Configuration.deprecation: user.name is deprecated. Instead, use mapreduce.job.user.name
  6. 14/07/27 01:22:44 INFO Configuration.deprecation: mapred.jar is deprecated. Instead, use mapreduce.job.jar
  7. 14/07/27 01:22:44 INFO Configuration.deprecation: mapred.output.value.class is deprecated. Instead, use mapreduce.job.output.value.class
  8. 14/07/27 01:22:44 INFO Configuration.deprecation: mapreduce.combine.class is deprecated. Instead, use mapreduce.job.combine.class
  9. 14/07/27 01:22:44 INFO Configuration.deprecation: mapreduce.map.class is deprecated. Instead, use mapreduce.job.map.class
  10. 14/07/27 01:22:44 INFO Configuration.deprecation: mapred.job.name is deprecated. Instead, use mapreduce.job.name
  11. 14/07/27 01:22:44 INFO Configuration.deprecation: mapreduce.reduce.class is deprecated. Instead, use mapreduce.job.reduce.class
  12. 14/07/27 01:22:44 INFO Configuration.deprecation: mapred.input.dir is deprecated. Instead, use mapreduce.input.fileinputformat.inputdir
  13. 14/07/27 01:22:44 INFO Configuration.deprecation: mapred.output.dir is deprecated. Instead, use mapreduce.output.fileoutputformat.outputdir
  14. 14/07/27 01:22:44 INFO Configuration.deprecation: mapred.map.tasks is deprecated. Instead, use mapreduce.job.maps
  15. 14/07/27 01:22:44 INFO Configuration.deprecation: mapred.output.key.class is deprecated. Instead, use mapreduce.job.output.key.class
  16. 14/07/27 01:22:44 INFO Configuration.deprecation: mapred.working.dir is deprecated. Instead, use mapreduce.job.working.dir
  17. 14/07/27 01:22:45 INFO mapreduce.JobSubmitter: Submitting tokens for job: job_1406394452186_0001
  18. 14/07/27 01:22:46 INFO impl.YarnClientImpl: Submitted application application_1406394452186_0001 to ResourceManager at m1/192.168.1.50:8032
  19. 14/07/27 01:22:46 INFO mapreduce.Job: The url to track the job: http://m1:8088/proxy/application_1406394452186_0001/
  20. 14/07/27 01:22:46 INFO mapreduce.Job: Running job: job_1406394452186_0001
  21. 14/07/27 01:23:10 INFO mapreduce.Job: Job job_1406394452186_0001 running in uber mode : false
  22. 14/07/27 01:23:10 INFO mapreduce.Job:  map 0% reduce 0%
  23. 14/07/27 01:23:31 INFO mapreduce.Job:  map 100% reduce 0%
  24. 14/07/27 01:23:48 INFO mapreduce.Job:  map 100% reduce 100%
  25. 14/07/27 01:23:48 INFO mapreduce.Job: Job job_1406394452186_0001 completed successfully
  26. 14/07/27 01:23:49 INFO mapreduce.Job: Counters: 43
  27.         File System Counters
  28.                 FILE: Number of bytes read=6574
  29.                 FILE: Number of bytes written=175057
  30.                 FILE: Number of read operations=0
  31.                 FILE: Number of large read operations=0
  32.                 FILE: Number of write operations=0
  33.                 HDFS: Number of bytes read=7628
  34.                 HDFS: Number of bytes written=5088
  35.                 HDFS: Number of read operations=6
  36.                 HDFS: Number of large read operations=0
  37.                 HDFS: Number of write operations=2
  38.         Job Counters 
  39.                 Launched map tasks=1
  40.                 Launched reduce tasks=1
  41.                 Data-local map tasks=1
  42.                 Total time spent by all maps in occupied slots (ms)=18062
  43.                 Total time spent by all reduces in occupied slots (ms)=14807
  44.         Map-Reduce Framework
  45.                 Map input records=240
  46.                 Map output records=827
  47.                 Map output bytes=9965
  48.                 Map output materialized bytes=6574
  49.                 Input split bytes=98
  50.                 Combine input records=827
  51.                 Combine output records=373
  52.                 Reduce input groups=373
  53.                 Reduce shuffle bytes=6574
  54.                 Reduce input records=373
  55.                 Reduce output records=373
  56.                 Spilled Records=746
  57.                 Shuffled Maps =1
  58.                 Failed Shuffles=0
  59.                 Merged Map outputs=1
  60.                 GC time elapsed (ms)=335
  61.                 CPU time spent (ms)=2960
  62.                 Physical memory (bytes) snapshot=270057472
  63.                 Virtual memory (bytes) snapshot=1990762496
  64.                 Total committed heap usage (bytes)=136450048
  65.         Shuffle Errors
  66.                 BAD_ID=0
  67.                 CONNECTION=0
  68.                 IO_ERROR=0
  69.                 WRONG_LENGTH=0
  70.                 WRONG_MAP=0
  71.                 WRONG_REDUCE=0
  72.         File Input Format Counters 
  73.                 Bytes Read=7530
  74.         File Output Format Counters 
  75.                 Bytes Written=5088
  76. root@m1:/home/hadoop/hadoop-2.2.0/bin#
验证HA的高可用性，故障转移，刚才我们用浏览器打开m1和s1的50070端口，已经看到m1的状态是active，s1的状态是standby 
a)我们在s1上kill掉namenode进程
  1. root@m1:/home/hadoop/hadoop-2.2.0/bin# jps
  2. 5492Jps
  3. 2884JournalNode
  4. 4375DFSZKFailoverController
  5. 2553QuorumPeerMain
  6. 3898NameNode
  7. 4075ResourceManager
  8. root@m1:/home/hadoop/hadoop-2.2.0/bin# kill -9 3898
  9. root@m1:/home/hadoop/hadoop-2.2.0/bin# jps
  10. 2884JournalNode
  11. 4375DFSZKFailoverController
  12. 2553QuorumPeerMain
  13. 4075ResourceManager
  14. 5627Jps
  15. root@m1:/home/hadoop/hadoop-2.2.0/bin#
再浏览m1和m2的50070端口，发现m1是打不开，而m2是active状态。 
这时候在m2上的HDFS和mapreduce还是可以正常运行的，虽然m1上的namenode进程已经被kill掉，但不影响使用这就是故障转移的优势！ 
大笑是不是感觉风格有点不同了，没错。
和后面的是copy的。




                                             
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