一个分布式系统基础架构，由Apache基金会所开发。 用户可以在不了解分布式底层细节的情况下，开发分布式程序。充分利用集群的威力高速运算和存储。
- 首先搭建Docker环境,Docker版本大于1.3.2
- 安装主机监控程序和加速器(curl -sSL https://get.daocloud.io/daomonit/install.sh | sh -s 7a029f60d36056fe1b85fabca6a133887245abe6)
- docker pull daocloud.io/library/centos:centos6.7
- docker run -it -h master --name master insaneworks/centos /bin/bash
- yum install -y gcc vim openssh-server openssh-clients java-1.7.0-openjdk-devel.x86_64 tar wget
这里java使用了openjdk1.7.0的版本，因为安装方便- vim /etc/ssh/sshd_config
放开PermitEmptyPasswords no
更改UsePAM no
放开PermitRootLogin yes- /etc/rc.d/init.d/sshd start
- ssh-keygen -t rsa -P ‘‘
- cat ~/.ssh/id_dsa.pub >> ~/.ssh/authorized_keys
- 配置/etc/profile
export JAVA_HOME=/usr/lib/jvm/java-1.7.0-openjdk.x86_64/
export CLASSPATH=.:$JAVA_HOME/lib/dt:$JAVA_HOME/lib/tools.jar
export HADOOP_HOME=/root/hadoop-2.7.1
export PATH=$JAVA_HOME/bin:$PATH:$HADOOP_HOME/bin11. 配置core-site.xml
<configuration>
<property>
<name>fs.defaultFS</name>
<value>hdfs://master:9000</value>
</property>
<property>
<name>fs.defaultFS</name>
<value>hdfs://master:9000</value>
</property>
<property>
<name>io.file.buffer.size</name>
<value>131702</value>
</property>
<property>
<name>hadoop.tmp.dir</name>
<value>file:/root/hadoop-2.7.1/tmp</value>
</property>
</configuration>12. 配置hdfs-site.xml
<configuration>
<property>
<name>dfs.namenode.name.dir</name>
<value>file:/root/hadoop-2.7.1/dfs/name</value>
</property>
<property>
<name>dfs.datanode.data.dir</name>
<value>file:/root/hadoop-2.7.1/dfs/data</value>
</property>
<property>
<name>dfs.replication</name>
<value>2</value>
</property>
<property>
<name>dfs.namenode.secondary.http-address</name>
<value>master:9001</value>
</property>
<property>
<name>dfs.webhdfs.enabled</name>
<value>true</value>
</property>
</configuration>13. 配置mapred-site.xml
<configuration>
<property>
<name>mapreduce.framework.name</name>
<value>yarn</value>
</property>
<property>
<name>mapreduce.jobhistory.address</name>
<value>master:10020</value>
</property>
<property>
<name>mapreduce.jobhistory.webapp.address</name>
<value>master:19888</value>
</property>
</configuration>14. 配置yarn.site.xml
<configuration>
<property>
<name>yarn.nodemanager.aux-services</name>
<value>mapreduce_shuffle</value>
</property>
<property>
<name>yarn.nodemanager.auxservices.mapreduce.shuffle.class</name>
<value>org.apache.hadoop.mapred.ShuffleHandler</value>
</property>
<property>
<name>yarn.resourcemanager.address</name>
<value>master:8032</value>
</property>
<property>
<name>yarn.resourcemanager.scheduler.address</name>
<value>master:8030</value>
</property>
<property>
<name>yarn.resourcemanager.resource-tracker.address</name>
<value>master:8031</value>
</property>
<property>
<name>yarn.resourcemanager.admin.address</name>
<value>master:8033</value>
</property>
<property>
<name>yarn.resourcemanager.webapp.address</name>
<value>master:8088</value>
</property>
<property>
<name>yarn.nodemanager.resource.memory-mb</name>
<value>1024</value>
</property>
</configuration>15. 配置etc/hadoop/slaves文件
追加
slave1
slave2
slave316. 配置hadoop-env.sh和yarn-env.sh
在文件第一行中添加：export JAVA_HOME=/usr/lib/jvm/java-1.7.0-openjdk.x86_64/17. 测试链接文件
ldd /root/hadoop-2.7.1/lib/native/libhadoop.so.1.0.0
/root/hadoop-2.7.1/lib/native/libhadoop.so.1.0.0: /lib64/libc.so.6: version `GLIBC_2.14‘ not found (required by /root/hadoop-2.7.1/lib/native/libhadoop.so.1.0.0)
linux-vdso.so.1 => (0x00007fff24dbc000)
libdl.so.2 => /lib64/libdl.so.2 (0x00007ff8c6371000)
libc.so.6 => /lib64/libc.so.6 (0x00007ff8c5fdc000)
/lib64/ld-linux-x86-64.so.2 (0x00007ff8c679b000)18. 安装glibc-2.14
tar zxvf glibc-2.14.tar.gz
cd glibc-2.14
mkdir build
cd build
../configure --prefix=/usr/local/glibc-2.14
make
make install
ln -sf /usr/local/glibc-2.14/lib/libc-2.14.so /lib64/libc.so.619. 测试链接文件
ldd /root/hadoop-2.7.1/lib/native/libhadoop.so.1.0.0
linux-vdso.so.1 => (0x00007fff72b7c000)
libdl.so.2 => /lib64/libdl.so.2 (0x00007fb996ce9000)
libc.so.6 => /lib64/libc.so.6 (0x00007fb99695c000)
/lib64/ld-linux-x86-64.so.2 (0x00007fb99711300020. 提交改镜像即可
docker commit master ice/hadoop21. 查看镜像列表
docker images
REPOSITORY TAG IMAGE ID CREATED VIRTUAL SIZE
ice/hadoop latest 385a97765871 7 hours ago 1.731 GB
daocloud.io/library/centos centos6.7 3fba1048142f 11 days ago 190.6 MB
daocloud.io/daocloud/daocloud-toolset latest aa5dc2eecd4a 6 weeks ago 145.8 MB
daocloud.io/daocloud/daomonit latest ae375c157c27 7 weeks ago 149 MB22. 干掉该配置镜像
docker rm master23. 启动集群脚本
docker run --rm -it -p 50070:50070 -p 19888:19888 -p 8088:8088 -p 50030:50030 -h master --name master ice/hadoop /bin/bash
docker run --rm -it -h slave1 --name slave1 ice/hadoop /bin/bash
docker run --rm -it -h slave2 --name slave2 ice/hadoop /bin/bash
docker run --rm -it -h slave3 --name slave3 ice/hadoop /bin/bash24. 配置环境变量和sshd服务
source /etc/profile
/etc/rc.d/init.d/sshd start25. 查看各个节点的IP
docker inspect --format=‘{{.NetworkSettings.IPAddress}}‘ master
docker inspect --format=‘{{.NetworkSettings.IPAddress}}‘ slave1
docker inspect --format=‘{{.NetworkSettings.IPAddress}}‘ slave2
docker inspect --format=‘{{.NetworkSettings.IPAddress}}‘ slave326. 启动Hadoop集群
hadoop namenode -format
/root/hadoop-2.7.1/sbin/start-dfs.sh
/root/hadoop-2.7.1/sbin/start-yarn.sh
注意??第一执行脚本时，需要确认一次27. 关闭脚本
/root/hadoop-2.7.1/sbin/stop-dfs.sh
/root/hadoop-2.7.1/sbin/stop-yarn.sh28. 测试命令
hadoop fs -mkdir /input
hadoop fs -ls /
hadoop fs -put /root/hadoop-2.7.1/etc/hadoop/* /input/
hadoop jar /root/hadoop-2.7.1/share/hadoop/mapreduce/hadoop-mapreduce-examples-2.7.1.jar wordcount /input/ /output/wordcount/ 时间： 2024-10-17 14:06:02