Hadoop安装杂记
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一、分布式模型
1、环境准备
准备4个节点，master1为主控节点（NameNode、SecondaryNameNode、ResourceManager），master2-4作为数据节点（DataNode、NodeManager）。并做好ntp时间同步
1.1 每个节点配置JAVA环境
[[email protected] ~]# vim /etc/profile.d/java.sh
export JAVA_HOME=/usr
[[email protected] ~]# scp /etc/profile.d/java.sh [email protected]:/etc/profile.d/
[[email protected] ~]# scp /etc/profile.d/java.sh [email protected]:/etc/profile.d/
[[email protected] ~]# scp /etc/profile.d/java.sh [email protected]:/etc/profile.d/
每个节点安装java-devel
[[email protected] ~]# yum install -y java-1.7.0-openjdk-devel
[[email protected] ~]# yum install -y java-1.7.0-openjdk-devel
[[email protected] ~]# yum install -y java-1.7.0-openjdk-devel
[[email protected] ~]# yum install -y java-1.7.0-openjdk-devel
配置hadoop环境变量：
[[email protected] ~]# vim /etc/profile.d/hadoop.sh
export HADOOP_PREFIX=/bdapps/hadoop
export PATH=$PATH:${HADOOP_PREFIX}/bin:${HADOOP_PREFIX}/sbin
export HADOOP_YARN_HOME=${HADOOP_PREFIX}
export HADOOP_MAPPERD_HOME=${HADOOP_PREFIX}
export HADOOP_COMMON_HOME=${HADOOP_PREFIX}
export HADOOP_HDFS_HOME=${HADOOP_PREFIX}
[[email protected] ~]# source /etc/profile.d/hadoop.sh
scp /etc/profile.d/hadoop.sh master2:/etc/profile.d/hadoop.sh
scp /etc/profile.d/hadoop.sh master3:/etc/profile.d/hadoop.sh
scp /etc/profile.d/hadoop.sh master4:/etc/profile.d/hadoop.sh1.2 每个节点准备host文件，实验使用别名调用
[[email protected] ~]# cat /etc/hosts
127.0.0.1 localhost localhost.localdomain localhost4 localhost4.localdomain4
::1 localhost localhost.localdomain localhost6 localhost6.localdomain6
10.201.106.131 master1 master1.com master
10.201.106.132 master2 master2.com
10.201.106.133 master3 master3.com
10.201.106.134 master4 master4.com
master2,3,4节点同上1.3 创建用户组和用户
[[email protected] ~]# useradd -g hadoop hadoop
设置用户密码：
echo ‘hadoop‘ | passwd --stdin hadoop
master2,3,4节点同上
for i in `seq 2 4`;do ssh [email protected]${i} "echo ‘hadoop‘ | passwd --stdin hadoop";done1.4 让master1（主控节点）的hadoop用户能通过密钥登录master1，2,3,4
[[email protected] ~]# su - hadoop
生成密钥和公钥：
[[email protected] ~]$ ssh-keygen -t rsa -P ‘hadoop‘
将master1的公钥拷贝到master1，2,3,4节点：
[[email protected] ~]$ for i in `seq 1 4`;do ssh-copy-id -i .ssh/id_rsa.pub [email protected]${i};done2、hadoop安装
2.1 创建目录并配置权限
[[email protected] ~]# mkdir -pv /bdapps /data/hadoop/hdfs/{nn,snn,dn}
[[email protected] ~]# chown -R hadoop:hadoop /data/hadoop/hdfs/
展开hadoop：
[[email protected] ~]# tar xf hadoop-2.6.2.tar.gz -C /bdapps/
创建软链接：
[ro[email protected] ~]# cd /bdapps/
[[email protected] bdapps]# ln -sv hadoop-2.6.2 hadoop
创建日志目录，并授权
[[email protected] ~]# cd /bdapps/hadoop
[[email protected] hadoop]# mkdir logs
[[email protected] hadoop]# chmod g+w logs
修改hadoop安装目录权限
[[email protected] hadoop]# chown -R hadoop:hadoop ./*2.2 主节点（master1）配置
[[email protected] ~]# cd /bdapps/hadoop/etc/hadoop/
[[email protected] hadoop]# vim core-site.xml
<configuration>
<property>
<name>fs.defaultFS</name>
<value>hdfs://master:8020</value>
<final>true</final>
</property>
</configuration>
[[email protected] hadoop]# vim yarn-site.xml
<configuration>
<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.address</name>
<value>master:8032</value>
</property>
<property>
<name>yarn.resourcemanager.scheduler.address</name>
<value>master:8030</value>
</property>
<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>10.201.106.131:8088</value>
</property>
<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.scheduler.class</name>
<value>org.apache.hadoop.yarn.server.resourcemanager.scheduler.capacity.CapacityScheduler</value>
</property>
</configuration>
[[email protected] hadoop]# vim hdfs-site.xml
<configuration>
<property>
<name>dfs.replication</name>
<value>2</value>
</property>
<property>
<name>dfs.namenode.name.dir</name>
<value>file:///data/hadoop/hdfs/nn</value>
</property>
<property>
<name>dfs.datanode.data.dir</name>
<value>file:///data/hadoop/hdfs/dn</value>
</property>
<property>
<name>fs.checkpoint.dir</name>
<value>file:///data/hadoop/hdfs/snn</value>
</property>
<property>
<name>fs.checkpoint.edits.dir</name>
<value>file:///data/hadoop/hdfs/snn</value>
</property>
</configuration>
[[email protected] hadoop]# vim mapred-site.xml
<configuration>
<property>
<name>mapreduce.framework.name</name>
<value>yarn</value>
</property>
</configuration>
[[email protected] hadoop]# vim slaves
master2
master3
master42.2 配置三个从节点
[[email protected] ~]# mkdir -pv /bdapps /data/hadoop/hdfs/dn
[[email protected] ~]# chown -R hadoop:hadoop /data/hadoop/hdfs/
[[email protected] ~]# tar xf hadoop-2.6.2.tar.gz -C /bdapps/
[[email protected] bdapps]# ln -sv hadoop-2.6.2 hadoop
[[email protected] bdapps]# cd hadoop
[[email protected] bdapps]# mkdir logs
[[email protected] bdapps]# chmod g+w logs
[[email protected] bdapps]# chown -R hadoop:hadoop ./*
从master1拷贝配置文件：
[[email protected] hadoop]# su - hadoop
[[email protected] ~]$ scp /bdapps/hadoop/etc/hadoop/* master2:/bdapps/hadoop/etc/hadoop/2.3 格式化文件系统
[[email protected] ~]$ hdfs namenode -format2.4 启动mapreduce集群
启动集群datanode节点
[[email protected] ~]$ start-dfs.sh
Starting namenodes on [master]
The authenticity of host ‘master (10.201.106.131)‘ can‘t be established.
ECDSA key fingerprint is 5e:5d:4d:d2:3f:73:fb:5c:c4:26:c7:c4:85:10:c9:75.
Are you sure you want to continue connecting (yes/no)? yes
master: Warning: Permanently added ‘master‘ (ECDSA) to the list of known hosts.
master: starting namenode, logging to /bdapps/hadoop/logs/hadoop-hadoop-namenode-master1.com.out
master2: starting datanode, logging to /bdapps/hadoop/logs/hadoop-hadoop-datanode-master2.com.out
master4: starting datanode, logging to /bdapps/hadoop/logs/hadoop-hadoop-datanode-master4.com.out
master3: starting datanode, logging to /bdapps/hadoop/logs/hadoop-hadoop-datanode-master3.com.out
Starting secondary namenodes [0.0.0.0]
The authenticity of host ‘0.0.0.0 (0.0.0.0)‘ can‘t be established.
ECDSA key fingerprint is 5e:5d:4d:d2:3f:73:fb:5c:c4:26:c7:c4:85:10:c9:75.
Are you sure you want to continue connecting (yes/no)? yes
0.0.0.0: Warning: Permanently added ‘0.0.0.0‘ (ECDSA) to the list of known hosts.
0.0.0.0: starting secondarynamenode, logging to /bdapps/hadoop/logs/hadoop-hadoop-secondarynamenode-master1.com.out
查看各节点启动的进程：
[[email protected] ~]$ jps
4977 NameNode
5324 Jps
5155 SecondaryNameNode
[[email protected] hadoop]# su - hadoop
Last login: Sun Apr 22 11:52:57 CST 2018 from master1 on pts/1
[[email protected] ~]$
[[email protected] ~]$
[[email protected] ~]$ jps
9972 DataNode
10131 Jps
确认主节点能够连接到另外三个从节点
[[email protected] ~]# netstat -tanp | grep 8020
tcp 0 0 10.201.106.131:8020 0.0.0.0:* LISTEN 4977/java
tcp 0 0 10.201.106.131:8020 10.201.106.134:51956 ESTABLISHED 4977/java
tcp 0 0 10.201.106.131:8020 10.201.106.133:36426 ESTABLISHED 4977/java
tcp 0 0 10.201.106.131:8020 10.201.106.132:37988 ESTABLISHED 4977/java
上传文件测试：
[[email protected] ~]$ hdfs dfs -mkdir /test
[[email protected] ~]$ hdfs dfs -put /etc/fstab /test/fstab
[[email protected] ~]$ hdfs dfs -ls /test/fstab
-rw-r--r-- 2 hadoop supergroup 1065 2018-04-23 03:00 /test/fstab
真实文件路径：
[[email protected] logs]$ cat /data/hadoop/hdfs/dn/current/BP-1262978243-10.201.106.131-1524421803827/current/finalized/subdir0/subdir0/blk_1073741827
[[email protected] ~]$ cat /data/hadoop/hdfs/dn/current/BP-1262978243-10.201.106.131-1524421803827/current/finalized/subdir0/subdir0/blk_10737418272.5 启动yarn集群
[[email protected] ~]$ start-yarn.sh
#主节点启动了ResourceManager
starting yarn daemons
starting resourcemanager, logging to /bdapps/hadoop/logs/yarn-hadoop-resourcemanager-master1.com.out
master3: starting nodemanager, logging to /bdapps/hadoop/logs/yarn-hadoop-nodemanager-master3.com.out
master4: starting nodemanager, logging to /bdapps/hadoop/logs/yarn-hadoop-nodemanager-master4.com.out
master2: starting nodemanager, logging to /bdapps/hadoop/logs/yarn-hadoop-nodemanager-master2.com.out
[[email protected] ~]$ jps
5919 ResourceManager
4977 NameNode
5155 SecondaryNameNode
6190 Jps
从节点启动了NodeManager
[[email protected] logs]$ jps
10243 DataNode
10508 Jps
10405 NodeManager
[[email protected] ~]$ jps
9380 DataNode
9696 NodeManager
9796 Jps2.6 查看WEB界面状态
浏览器访问：http://10.201.106.131:8088
浏览器访问：http://10.201.106.131:50070
3、其他操作
3.1 上传大文件观察切块
生成一个200M文件：
[[email protected] ~]$ dd if=/dev/zero of=test bs=1M count=200原始图：
上传后（超过64M后会切块）：
3.2 通过浏览器查看日志
访问：http://10.201.106.131:50070/logs/
3.2 运行任务测试
列出该测试程序的可用示例：
[[email protected] ~]$ yarn jar /bdapps/hadoop/share/hadoop/mapreduce/hadoop-mapreduce-examples-2.6.2.jar
统计文件单词数：
[[email protected] ~]$ yarn jar /bdapps/hadoop/share/hadoop/mapreduce/hadoop-mapreduce-examples-2.6.2.jar wordcount /test/fstab /test/functions /test/wordou查看：
查看任务进度：
查看结果 ：
[[email protected] ~]$ hdfs dfs -ls /test/wordout
Found 2 items
-rw-r--r-- 2 hadoop supergroup 0 2018-04-23 06:56 /test/wordout/_SUCCESS
-rw-r--r-- 2 hadoop supergroup 7855 2018-04-23 06:56 /test/wordout/part-r-00000
4、yarn集群管理命令
4.1 查看yarn的所有命令
[[email protected] ~]$ yarn
4.2 application
4.2.1 查看作业
列出活动作业：
[[email protected] ~]$ yarn application -list
18/04/23 07:23:47 INFO client.RMProxy: Connecting to ResourceManager at master/10.201.106.131:8032
Total number of applications (application-types: [] and states: [SUBMITTED, ACCEPTED, RUNNING]):0
Application-Id Application-Name Application-Type User Queue State Final-State Progress Tracking-URL
列出所有作业：
[[email protected] ~]$ yarn application -list -appStates=all
18/04/23 07:24:48 INFO client.RMProxy: Connecting to ResourceManager at master/10.201.106.131:8032
Total number of applications (application-types: [] and states: [NEW, NEW_SAVING, SUBMITTED, ACCEPTED, RUNNING, FINISHED, FAILED, KILLED]):1
Application-Id Application-Name Application-Type User Queue State Final-State Progress Tracking-URL
application_1524424153008_0001 word count MAPREDUCE hadoop default FINISHED SUCCEEDED 100% http://master2:19888/jobhistory/job/job_1524424153008_0001
[[email protected] ~]$
查看作业状态：
[[email protected] ~]$ yarn application -status application_1524424153008_0001
18/04/23 07:28:32 INFO client.RMProxy: Connecting to ResourceManager at master/10.201.106.131:8032
Application Report :
Application-Id : application_1524424153008_0001
Application-Name : word count
Application-Type : MAPREDUCE
User : hadoop
Queue : default
Start-Time : 1524437422005
Finish-Time : 1524437801216
Progress : 100%
State : FINISHED
Final-State : SUCCEEDED
Tracking-URL : http://master2:19888/jobhistory/job/job_1524424153008_0001
RPC Port : 40927
AM Host : master2
Aggregate Resource Allocation : 1326835 MB-seconds, 909 vcore-seconds
Diagnostics :
[[email protected] ~]$ 4.3 node
列出node列表：
[[email protected] ~]$ yarn node -list
18/04/23 07:33:37 INFO client.RMProxy: Connecting to ResourceManager at master/10.201.106.131:8032
Total Nodes:3
Node-Id Node-State Node-Http-Address Number-of-Running-Containers
master4:47410 RUNNING master4:8042 0
master3:55126 RUNNING master3:8042 0
master2:54307 RUNNING master2:8042 0
列出所有node节点，包括故障下线的：
[[email protected] ~]$ yarn node -list -all
查看指定节点状态信息：
[[email protected] ~]$ yarn node -status master2:54307
18/04/23 07:41:01 INFO client.RMProxy: Connecting to ResourceManager at master/10.201.106.131:8032
Node Report :
Node-Id : master2:54307
Rack : /default-rack
Node-State : RUNNING
Node-Http-Address : master2:8042
Last-Health-Update : Sun 22/Apr/18 10:06:49:900CST
Health-Report :
Containers : 0
Memory-Used : 0MB
Memory-Capacity : 8192MB
CPU-Used : 0 vcores
CPU-Capacity : 8 vcores
Node-Labels : 4.4 logs
在yarn-site.xml配置文件定义yarn.log-aggregation-enable属性的值为true即可。
需要重启集群
查看作业日志
[[email protected] ~]$ yarn logs -applicationId application_1524424153008_00014.5 classpath
查看java环境路径：
[[email protected] ~]$ yarn classpath
/bdapps/hadoop/etc/hadoop:/bdapps/hadoop/etc/hadoop:/bdapps/hadoop/etc/hadoop:/bdapps/hadoop/share/hadoop/common/lib/*:/bdapps/hadoop/share/hadoop/common/*:/bdapps/hadoop/share/hadoop/hdfs:/bdapps/hadoop/share/hadoop/hdfs/lib/*:/bdapps/hadoop/share/hadoop/hdfs/*:/bdapps/hadoop/share/hadoop/yarn/lib/*:/bdapps/hadoop/share/hadoop/yarn/*:/bdapps/hadoop/share/hadoop/mapreduce/lib/*:/bdapps/hadoop/share/hadoop/mapreduce/*:/contrib/capacity-scheduler/*.jar:/bdapps/hadoop/share/hadoop/yarn/*:/bdapps/hadoop/share/hadoop/yarn/lib/*yarn的管理命令
4.6 rmadmin
4.6.1 命令帮助
获取命令帮助：
[[email protected] ~]$ yarn rmadmin -help4.6.2 刷新node节点状态信息
[[email protected] ~]$ yarn rmadmin -refreshNodes
18/04/23 07:54:48 INFO client.RMProxy: Connecting to ResourceManager at master/10.201.106.131:80334.7 运行YARN Application流程
1、Application初始化及体检；
2、分配内存并启动AM；
3、AM注册及资源分配；
4、启动并监控容易；
5、Application进度报告；
6、Application运行完成；5、其他
5.1 官方自动安装部署hadoop工具：Ambari
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