Linux搭建Hadoop开发环境

Hadoop环境搭建安装配置：

[1].官网下载Hadoop-2.7.5安装包： hadoop-2.7.5/hadoop-2.7.5.tar.gz

[2].把Hadoop-2.7.5安装包利用Xftp5工具上传到：/usr/local/hadoop

[3].登录Liunx服务器，利用Xhell5进入：cd /usr/local/hadoop：

[root@marklin hadoop]# cd /usr/local/hadoop

[root@marklin hadoop]#

并使用tar -xvf 解压：tar -xvf hadoop-2.7.5.tar.gz，

[root@marklin hadoop]# tar -xvf hadoop-2.7.5.tar.gz

[4].配置Hadoop环境变量，输入：vim /etc/profile

#Setting HADOOP_HOME PATH

export HADOOP_HOME=/usr/local/hadoop/hadoop-2.7.5

export PATH=${PATH}:${HADOOP_HOME}/bin:${HADOOP_HOME}/sbin::${HADOOP_HOME}/lib

export HADOOP_COMMON_LIB_NATIVE_DIR=${HADOOP_HOME}/lib/native

export HADOOP_OPTS="-Djava.library.path=$HADOOP_HOME/lib"

export HADOOP_MAPARED_HOME=${HADOOP_HOME}

export HADOOP_COMMON_HOME=${HADOOP_HOME}

export HADOOP_HDFS_HOME=${HADOOP_HOME}

export YARN_HOME=${HADOOP_HOME}

export HADOOP_CONF_DIR=${HADOOP_HOME}/etc/hadoop

export HDFS_CONF_DIR=${HADOOP_HOME}/etc/hadoop

export YARN_CONF_DIR=${HADOOP_HOME}/etc/hadoop

保存配置，输入：source /etc/profile

[root@marklin ~]# source /etc/profile

[root@marklin ~]#

PS：最总要的2个点：

【1】修改主机名称：vim /etc/hostname

【2】修改配置主机与Ip地址的映射：vim /etc/hosts

[5].Hadoop修改配置文件：

core-site.xml：Hadoop的核心配置，包含tmp临时配置文件和访问地址，默认端口9000

mapred-site.xml：Hadoop中相关数据处理模型的配置处理

yarn-site.xml：Hadoop中相关Job的配置处理

hdfs-site.xml：Hadoop配置的文件备份个数以及数据文件夹的配置

(1). 配置core-site.xml，在Hadoop安装目录[/usr/local/hadoop/hadoop-2.7.5/etc/hadoop]下输入： vim core-site.xml

[root@marklin ~]# cd /usr/local/hadoop/hadoop-2.7.5/etc/hadoop

[root@marklin hadoop]#

输入：vim core-site.xml

并配置：

<name>fs.default.name</name>

<value>hdfs://marklin.com:9000</value>

</property>

<name>hadoop.tmp.dir</name>

<value>/usr/local/hadoop/repository/hdfs/tmp</value>

</property>

<name>io.file.buffer.size</name>

</property>

<name>hadoop.proxyuser.hadoop.hosts</name>

</property>

<name>hadoop.proxyuser.hadoop.groups</name>

</property>

</configuration>

同时在文件路径：/usr/local/hadoop/repository/hdfs，创建tmp目录： mkdir tmp

（2）修改 hdfs-site.xml，并配置：vim hdfs-site.xml

[root@marklin hadoop]# vim hdfs-site.xml

[root@marklin hadoop]#

<name>dfs.namenode.name.dir</name> --dfs.namenode.name.dir定义名称节点路径

<value>/usr/local/hadoop/repository/hdfs/name</value>

</property>

<name>dfs.datanode.data.dir</name> --dfs.datanode.data.dir定义数据节点路径

<value>/usr/local/hadoop/repository/hdfs/data</value>

</property>

<name>dfs.permissions</name> --dfs.permissions定义权限认证

<value>false</value>

</property>

<name>dfs.replication</name>--dfs.replication定义文件副本数

</property>

<name>dfs.namenode.http-address</name>--dfs.namenode.http-address定义服务http的访问

<value>marklin.com:50070</value>

</property>

<name>dfs.namenode.secondary.http-address</name>--dfs.namenode.secondary.http-address定义服务http的访问

<value>marklin.com:50090</value>

</property>

<name>dfs.webhdfs.enabled</name>

</property>

</configuration>

<name>dfs.namenode.name.dir</name>

<value>/usr/local/hadoop/repository/hdfs/name</value>

</property>

<name>dfs.datanode.data.dir</name>

<value>/usr/local/hadoop/repository/hdfs/data</value>

</property>

<name>dfs.replication</name>

</property>

<name>dfs.namenode.http-address</name>

<value>marklin.com:50070</value>

</property>

<name>dfs.namenode.secondary.http-address</name>

<value>marklin.com:50090</value>

</property>

<name>dfs.webhdfs.enabled</name>

</property>

<name>dfs.permissions</name>

<value>false</value>

</property>

</configuration>

同时在文件路径：/usr/local/hadoop/repository/hdfs，创建name和data目录： mkdir name 和mkdir data

（3）创建mapred-site.xml文件，输入：cp mapred-site.xml.template mapred-site.xml

[root@marklin hadoop]# cp mapred-site.xml.template mapred-site.xml

编辑mapred-site.xml文件，并配置：

<name>mapreduce.framework.name</name>

</property>

<name>mapred.job.tracker</name>

<value>hdfs://marklin.com:8021/</value>

</property>

<name>mapreduce.jobhistory.address</name>

<value>marklin.com:10020</value>

</property>

<name>mapreduce.jobhistory.webapp.address</name>

<value>marklin.com:19888</value>

</property>

<name>mapreduce.reduce.java.opts</name>

</property>

<name>mapreduce.map.memory.mb</name>

</property>

<name>mapreduce.reduce.input.buffer.percent</name>

</property>

<name>mapreduce.reduce.memory.mb</name>

</property>

<name>mapred.tasktracker.reduce.tasks.maximum</name>

</property>

<name>mapred.system.dir</name>

<value>/usr/local/hadoop/repository/mapreduce/system</value>

</property>

<name>mapred.local.dir</name>

<value>/usr/local/hadoop/repository/mapreduce/local</value>

</property>

</configuration>

（4）修改 yarn-site.xml，并输入：:vim yarn-site.xml

[root@marklin hadoop]# vim yarn-site.xml

[root@marklin hadoop]#

并配置：

<name>yarn.nodemanager.aux-services</name>

<value>mapreduce_shuffle</value>

</property>

<name>yarn.nodemanager.auxservices.mapreduce.shuffle.class</name>

<value>org.apache.hadoop.mapred.ShuffleHandler</value>

</property>

<name>yarn.resourcemanager.hostname</name>

<value>marklin.com</value>

</property>

<name>yarn.resourcemanager.address</name>

<value>${yarn.resourcemanager.hostname}:8032</value>

</property>

<name>yarn.resourcemanager.scheduler.address</name>

<value>${yarn.resourcemanager.hostname}:8030</value>

</property>

<name>yarn.resourcemanager.resource-tracker.address</name>

<value>${yarn.resourcemanager.hostname}:8031</value>

</property>

<name>yarn.resourcemanager.admin.address</name>

<value>${yarn.resourcemanager.hostname}:8033</value>

</property>

<name>yarn.resourcemanager.webapp.address</name>

<value>${yarn.resourcemanager.hostname}:8088</value>

</property>

<name>yarn.nodemanager.resource.memory-mb</name>

</property>

<name>yarn.app.mapreduce.am.staging-dir</name>

<value>/usr/local/hadoop/repository/mapreduce/staging</value>

</property>

<name>mapreduce.jobhistory.intermediate-done-dir</name>

<value>${yarn.app.mapreduce.am.staging-dir}/history/done_intermediate</value>

</property>

<name>mapreduce.jobhistory.done-dir</name>

<value>${yarn.app.mapreduce.am.staging-dir}/history/done</value>

</property>

</configuration>

【6】在Hadoop文件目录[/usr/local/hadoop/hadoop-2.7.5/etc/hadoop]下，

对应的 hadoop-env.sh,mapred-env.sh以及yarn-env.sh文件配置JAVA_HOME：export JAVA_HOME=/usr/local/java/jdk1.8.0_162

输入：vim hadoop-env.sh ：

[root@marklin hadoop]# vim hadoop-env.sh

[root@marklin hadoop]#

export JAVA_HOME=/usr/local/java/jdk1.8.0_162

输入：vim mapred-env.sh：

export JAVA_HOME=/usr/local/java/jdk1.8.0_162

[root@marklin hadoop]# vim mapred-env.sh

[root@marklin hadoop]#

输入：vim yarn-env.sh

export JAVA_HOME=/usr/local/java/jdk1.8.0_162

[root@marklin hadoop]# vim yarn-env.sh

[root@marklin hadoop]#

【6】开放端口：50070

（1）启动防火墙：systemctl start firewalld.service

[root@marklin ~]# systemctl start firewalld.service

[root@marklin ~]#

（2）启动防火墙：firewall-cmd --zone=public --add-port=50070/tcp --permanent

[root@marklin ~]# firewall-cmd --zone=public --add-port=50070/tcp --permanent

[root@marklin ~]#

(3)启动：firewall-cmd --reload

[root@marklin ~]# firewall-cmd --reload

[root@marklin ~]#

（4）格式化：hdfs namenode -format

[root@marklin ~]# hdfs namenode -format

[root@marklin ~]#

（5）启动脚本：start-all.sh

[root@marklin ~]# start-all.sh

[root@marklin ~]#

[root@marklin ~]# start-dfs.sh

Starting namenodes on [marklin.com]

marklin.com: starting namenode, logging to /usr/local/hadoop/hadoop-2.7.5/logs/hadoop-root-namenode-marklin.com.out

marklin.com: starting datanode, logging to /usr/local/hadoop/hadoop-2.7.5/logs/hadoop-root-datanode-marklin.com.out

Starting secondary namenodes [marklin.com]

marklin.com: starting secondarynamenode, logging to /usr/local/hadoop/hadoop-2.7.5/logs/hadoop-root-secondarynamenode-marklin.com.out

[root@marklin ~]# start-yarn.sh

starting yarn daemons

starting resourcemanager, logging to /usr/local/hadoop/hadoop-2.7.5/logs/yarn-root-resourcemanager-marklin.com.out

marklin.com: starting nodemanager, logging to /usr/local/hadoop/hadoop-2.7.5/logs/yarn-root-nodemanager-marklin.com.out

[root@marklin ~]# jps

1122 QuorumPeerMain

6034 Jps

1043 QuorumPeerMain

5413 SecondaryNameNode

5580 ResourceManager

5085 NameNode

5709 NodeManager

5230 DataNode

1119 QuorumPeerMain

【7】输入测试地址：

【1】浏览器输入：http://192.168.3.4:50070/dfshealth.html#tab-overview

【2】浏览器输入：http://192.168.3.4:8088/cluster

Linux搭建Hadoop开发环境

相关推荐