准备hadoop2(master), Hadoop3,hadoop4,三台机器
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vi /etc/profile.d/hadoop.sh
export JAVA_HOME=/usr/local/src/jdk1.8.0_92 export JRE_HOME=${JAVA_HOME}/jre export CLASSPATH=.:${JAVA_HOME}/lib:${JRE_HOME}/lib:$CLASSPATH export JAVA_PATH=${JAVA_HOME}/bin:${JRE_HOME}/bin export PATH=$PATH:${JAVA_PATH} export HADOOP_HOME=/usr/local/src/hadoop-2.7.7 export PATH=$PATH:$HADOOP_HOME/bin:$HADOOP_HOME/sbin export HDFS_DATANODE_USER=root export HDFS_DATANODE_SECURE_USER=root export HDFS_SECONDARYNAMENODE_USER=root export HDFS_NAMENODE_USER=root export YARN_RESOURCEMANAGER_USER=root export YARN_NODEMANAGER_USER=root
mapred-env.sh hadoop-env.xml yarn-env.sh 至少有一个设置JAVA_HOME
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core-site.xml,配置hdfs端口和地址,临时文件存放地址
更多参考core-site.xml
<configuration> <property> <name>fs.default.name</name> <value>hdfs://hadoop2:9091</value> </property> <property> <name>hadoop.tmp.dir</name> <value>/data/docker/hadoop/tmp</value> </property> </configuration>
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hdfs-site.xml, 配置HDFS组件属性,副本个数以及数据存放的路径
更多参考hdfs-site.xml
dfs.namenode.name.dir和dfs.datanode.data.dir不再单独配置,官网给出的配置是针对规模较大的集群的较高配置。
<font color=red>注意:这里目录是每台机器上的,不要去使用volumes-from data_docker资源共享卷</font>
三台机器同时做
mkdir -p /opt/hadoop/tmp && mkdir -p /opt/hadoop/dfs/data && mkdir -p /opt/hadoop/dfs/name
<configuration> <property> <name>dfs.namenode.http-address</name> <value>hadoop2:9092</value> </property> <property> <name>dfs.replication</name> <value>2</value> </property> <property> <name>dfs.namenode.name.dir</name> <value>file:/opt/hadoop/dfs/name</value> </property> <property> <name>dfs.datanode.data.dir</name> <value>file:/opt/hadoop/dfs/data</value> </property> <property> <name>dfs.namenode.handler.count</name> <value>100</value> </property> </configuration>
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mapred-site.xml,配置使用yarn框架执行mapreduce处理程序
更多参考mapred-site.xml
<configuration> <property> <name>mapreduce.framework.name</name> <value>yarn</value> </property> <property> <name>mapreduce.jobhistory.address</name> <value>hadoop2:9094</value> </property> <property> <name>mapreduce.jobhistory.webapp.address</name> <value>hadoop2:9095</value> </property> <property> <name>mapreduce.application.classpath</name> <value> /usr/local/src/hadoop-3.1.2/etc/hadoop, /usr/local/src/hadoop-3.1.2/share/hadoop/common/*, /usr/local/src/hadoop-3.1.2/share/hadoop/common/lib/*, /usr/local/src/hadoop-3.1.2/share/hadoop/hdfs/*, /usr/local/src/hadoop-3.1.2/share/hadoop/hdfs/lib/*, /usr/local/src/hadoop-3.1.2/share/hadoop/mapreduce/*, /usr/local/src/hadoop-3.1.2/share/hadoop/mapreduce/lib/*, /usr/local/src/hadoop-3.1.2/share/hadoop/yarn/*, /usr/local/src/hadoop-3.1.2/share/share/hadoop/yarn/lib/* </value> </property> </configuration>
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yarn-site.xml
更多配置信息,请参考yarn-site.xml。<configuration> <property> <name>yarn.resourcemanager.hostname</name> <value>bdfb9324ff7d</value> </property> <property> <name>yarn.nodemanager.aux-services</name> <value>mapreduce_shuffle</value> </property> <property> <name>yarn.resourcemanager.webapp.address</name> <value>hadoop2:9093</value> </property> <property> <name>yarn.nodemanager.aux-services.mapreduce.shuffle.class</name> <value>org.apache.hadoop.mapred.ShuffleHandler</value> </property> </configuration>
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配置ssh免密登录
yum -y install openssh-server openssh-clients ssh-keygen -q -t rsa -b 2048 -f /etc/ssh/ssh_host_rsa_key -N '' ssh-keygen -q -t ecdsa -f /etc/ssh/ssh_host_ecdsa_key -N '' ssh-keygen -t dsa -f /etc/ssh/ssh_host_ed25519_key -N '' ssh-keygen -t rsa -P '' -f ~/.ssh/id_rsa #这样可以没有交互 #进入~/.ssh cp id_rsa.pub authorized_keys cp authorized_keys /data/docker/hadoop/ #拷贝到共享磁盘 #在其他docker #1. 依次完成上述操作(1-4) #2. hadoop3 ,hadoop4操作如下 cp /data/docker/hadoop/authorized_keys ~/.ssh cat id_rsa.pub >> authorized_keys cp authorized_keys /data/docker/hadoop/authorized_keys #覆盖 #再回到hadoop2容器 cp /data/docker/hadoop/authorized_keys authorized_keys #覆盖,这样 #测试 #启动hadoop3,hadoop4的ssh /usr/sbin/sshd ssh root@hadoop3 ssh root@hadoop4
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配置hosts
172.17.0.9 hadoop2 172.17.0.10 hadoop3 172.17.0.11 hadoop4
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配置works定义工作节点
vi /usr/local/src/hadoop-3.1.2/etc/hadoop/workers ,2.7版本中应该是slave
hadoop2 #这台以既可以是namenode,也可以是datanode,不要浪费机器 hadoop3 #只做datanode hadoop4 #只做datanode
- 停止docker容器并创建镜像
172.17.0.0/24 可用ip: 1-255 ip总数256, 子网掩码:255.255.255.0
172.17.0.0/16 可用ip: 可用地址就是172.16.0.1-172.16.255.254. ip总数:65536 子网掩码:255.255.0.0
docker commit hadoop2 image_c
docker run --privileged -tdi --volumes-from data_docker --name hadoop2 --hostname hadoop2 --add-host hadoop2:172.17.0.8 --add-host hadoop3:172.17.0.9 --add-host hadoop4:172.17.0.10 --link mysqlcontainer:mysqlcontainer -p 5002:22 -p 8088:8088 -p 9090:9090 -p 9091:9091 -p 9092:9092 -p 9093:9093 -p 9094:9094 -p 9095:9095 -p 9096:9096 -p 9097:9097 -p 9098:9098 -p 9099:9099 centos:hadoop /bin/bash
docker run --privileged -tdi --volumes-from data_docker --name hadoop3 --hostname hadoop3 --add-host hadoop2:172.17.0.8 --add-host hadoop3:172.17.0.9 --add-host hadoop4:172.17.0.10 --link mysqlcontainer:mysqlcontainer -p 5003:22 centos:hadoop /bin/bash
docker run --privileged -tdi --volumes-from data_docker --name hadoop4 --hostname hadoop4 --add-host hadoop2:172.17.0.8 --add-host hadoop3:172.17.0.9 --add-host hadoop4:172.17.0.10 --link mysqlcontainer:mysqlcontainer -p 5004:22 centos:hadoop /bin/bash
- 启动
首次hdfs namenode -format
你会看到最后倒数: util.ExitUtil: Exiting with status 0
start-all.sh This script is Deprecated. Instead use start-dfs.sh and start-yarn.sh
#start-dfs.sh----------------------
# jps 可以在Master上看到如下进程:
5252 DataNode
5126 NameNode
5547 Jps
5423 SecondaryNameNode
# jps slave可以看到
1131 Jps
1052 DataNode
# start-yarn.sh------------------
# jps 可以在Master上看到如下进程:
5890 NodeManager
5252 DataNode
5126 NameNode
6009 Jps
5423 SecondaryNameNode
5615 ResourceManager
# jps slave可以看到
1177 NodeManager
1052 DataNode
1309 Jps
访问
http://hadoop2:9092
试用hadoop
准备test
cat test.txt
hadoop mapreduce hive
hbase spark storm
sqoop hadoop hive
spark hadoop
#hdfs dfs 看一下帮助
#创建hadoop下的目录
hadoop fs -mkdir /input
hadoop fs -ls /
#上传
hadoop fs -put test.txt /input
hadoop fs -ls /input
#运行hadoop自带workcount程序
#/hadoop-mapreduce-examples-2.7.7.jar里面有很多小程序
yarn jar /usr/local/src/hadoop-2.7.7/share/hadoop/mapreduce/hadoop-mapreduce-examples-2.7.7.jar wordcount /input/test.txt /output
hadoop fs -ls /output
-rw-r--r-- 2 root supergroup 0 2019-06-03 01:28 /output/_SUCCESS
-rw-r--r-- 2 root supergroup 60 2019-06-03 01:28 /output/part-r-00000
#查看结果
hadoop fs -cat /output/part-r-00000
#查看其他内置程序
hadoop jar /usr/local/src/hadoop-2.7.7/share/hadoop/mapreduce/hadoop-mapreduce-examples-2.7.7.jar
#可以看到grep的用法
hadoop jar /usr/local/src/hadoop-2.7.7/share/hadoop/mapreduce/hadoop-mapreduce-examples-2.7.7.jar grep
http://hadoop2:9093 看到任务信息
其他hadoop命令
#查看容量
hadoop fs -df -h
Filesystem Size Used Available Use%
hdfs://hadoop2:9091 150.1 G 412 K 129.9 G 0%
#查看各个机器状态
hdfs dfsadmin -report
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