• hadoop2.2配置文件(较简单版)-最新版本


    一些准备工作就不说了,包括设置ssh连接等,主要说一下配置文件内容及启动过程,以192.168.157.100~105几台服务器为例:

    1、core-site.xml:

    <configuration>
    <property>
    <name>fs.defaultFS</name>
    <value>hdfs://hadoop-kf100.jd.com:8020</value>
    </property>
    <property>
    <name>io.file.buffer.size</name>
    <value>131072</value>
    </property>
    <property>
    <name>hadoop.tmp.dir</name>
    <value>/usr/local/hadoop/tmp/hadoop-${user.name}</value>
    </property>
    <property>
    <name>hadoop.proxyuser.hadoop.hosts</name>
    <value>*</value>
    </property>
    <property>
    <name>hadoop.proxyuser.hadoop.groups</name>
    <value>*</value>
    </property>
    </configuration>

    2、hadoop-env.sh:

    添加jdk安装目录:export JAVA_HOME=/export/servers/jdk1.6.0_25

    3、hdfs-site.xml:

    <configuration>
    <property>
    <name>dfs.namenode.secondary.http-address</name>
    <value>hadoop-kf100.jd.com:9001</value>
    </property>
    <property>
    <name>dfs.namenode.name.dir</name>
    <value>/usr/local/hadoop/dfs/name</value>
    </property>
    <property>
    <name>dfs.datanode.data.dir</name>
    <value>/usr/local/hadoop/dfs/data</value>
    </property>
    <property>
    <name>dfs.replication</name>
    <value>3</value>
    </property>
    <property>
    <name>dfs.permissions</name>
    <value>false</value>
    </property>
    <property>
    <name>dfs.webhdfs.enabled</name>
    <value>true</value>
    </property>
    </configuration>

    4、mapred-site.xml:

    <configuration>
    <property>
    <name>mapreduce.framework.name</name>
    <value>yarn</value>
    </property>
    <property>
    <name>mapreduce.jobhistory.address</name>
    <value>hadoop-kf100.jd.com:10020</value>
    </property>
    <property>
    <name>mapreduce.jobhistory.webapp.address</name>
    <value>hadoop-kf100.jd.com:19888</value>
    </property>
    <property>
    <name>mapreduce.map.java.opts</name>
    <value>-Xmx768M</value>
    </property>
    <property>
    <name>mapreduce.reduce.java.opts</name>
    <value>-Xmx1024M</value>
    </property>
    </configuration>

    5、slaves:

    hadoop-kf101.jd.com
    hadoop-kf102.jd.com
    hadoop-kf103.jd.com
    hadoop-kf104.jd.com
    hadoop-kf105.jd.com

    6、yarn-site.xml:

    <configuration>
    <property>
    <name>yarn.nodemanager.aux-services</name>
    <value>mapreduce_shuffle</value>
    </property>
    <property>
    <name>yarn.nodemanager.aux-services.mapreduce.shuffle.class</name>
    <value>org.apache.hadoop.mapred.ShuffleHandler</value>
    </property>
    <property>
    <name>yarn.resourcemanager.address</name>
    <value>hadoop-kf100.jd.com:8032</value>
    </property>
    <property>
    <name>yarn.resourcemanager.scheduler.address</name>
    <value>hadoop-kf100.jd.com:8030</value>
    </property>
    <property>
    <name>yarn.resourcemanager.resource-tracker.address</name>
    <value>hadoop-kf100.jd.com:8031</value>
    </property>
    <property>
    <name>yarn.resourcemanager.admin.address</name>

    <value>hadoop-kf100.jd.com:8033</value>

    </property>
    <property>

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

    <value>hadoop-kf100.jd.com:8088</value>
    </property>
    <property>
    <name>yarn.resourcemanager.scheduler.class</name>
    <value>org.apache.hadoop.yarn.server.resourcemanager.scheduler.fair.FairScheduler</value>
    </property>
    <property>
    <name>yarn.scheduler.fair.allocation.file</name>
    <value>/usr/local/hadoop-2.2.0/etc/hadoop/fair-scheduler.xml</value>
    </property>
    <property>
    <name>yarn.log-aggregation-enable</name>
    <value>true</value>
    </property>
    </configuration>

    7、fair-scheduler.xml:--设置队列的app数

    <allocations>
    <queue name="erpmerge">
    <minResources>671193 mb,378vcores</minResources>
    <maxResources>851151 mb,480vcores</maxResources>
    <maxRunningApps>200</maxRunningApps>
    <weight>1.0</weight>
    <schedulingPolicy>fair</schedulingPolicy>
    </queue>
    <user name="erpmerge">
    <maxRunningApps>200</maxRunningApps>
    </user>
    <queue name="mart_cfo">
    <minResources>671193 mb,378vcores</minResources>
    <maxResources>851151 mb,480vcores</maxResources>
    <maxRunningApps>200</maxRunningApps>
    <weight>1.0</weight>
    <schedulingPolicy>fair</schedulingPolicy>
    </queue>
    <user name="mart_cfo">
    <maxRunningApps>200</maxRunningApps>
    </user>
    <userMaxAppsDefault>100</userMaxAppsDefault>
    <defaultQueueSchedulingPolicy>fair</defaultQueueSchedulingPolicy>
    </allocations>

    每个节点的内容都是一样的,下面是启动过程:

    namenode:sh hadoop-daemon.sh namenode start

    datanode:sh hadoop-daemons.sh datanode start 

    jobhistory:sh mr-jobhistory-daemon.sh jobhistory start

    resoucemanager、nodemanager:sh start-yarn.sh

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  • 原文地址:https://www.cnblogs.com/zhli/p/5216252.html
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