标签:生效 https secondary common hadoop exception comm led ado
这里是当初在三个ECS节点上搭建hadoop+zookeeper+hbase+solr的主要步骤,文章内容未经过润色,请参考的同学搭配其他博客一同使用,并记得根据实际情况调整相关参数。
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jdk,推荐1.8
关闭防火墙
开放ECS安全组
?三台机器之间的免密登陆ssh
ip映射:【question1】hadoop启动时出现报错java.net.BindException: Cannot assign requested address
说明ip映射没有配置正确,正确的方式是在每一个节点上,都执行"内外外"的配置方式,即将本机与本机的内网ip对应,其他机器设置为外网ip
下面的文件要在每个节点上都修改
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1. vi /etc/profile
/opt/hadoop/hadoop-2.7.7
export HADOOP_HOME=/opt/hadoop/hadoop-2.7.7
export HADOOP_COMMON_LIB_NATIVE_DIR=$HADOOP_HOME/lib/native
export HADOOP_OPTS="-Djava.library.path=$HADOOP_HOME/lib"
export PATH=.:${JAVA_HOME}/bin:${HADOOP_HOME}/bin:$PATH
#使环境变量生效
souce /etc/profile
#检验
hadoop version
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<configuration>
<property>
<name>fs.defaultFS</name>
<value>hdfs://Gwj:8020</value>
<description>定义默认的文件系统主机和端口</description>
</property>
<property>
<name>io.file.buffer.size</name>
<value>4096</value>
<description>流文件的缓冲区为4K</description>
</property>
<property>
<name>hadoop.tmp.dir</name>
<value>file:/opt/hadoop/hadoop-2.7.7/tempdata</value>
<description>A base for other temporary directories.</description>
</property>
</configuration>
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<configuration>
<property>
<name>dfs.replication</name>
<value>2</value>
</property>
<property>
<name>dfs.namenode.name.dir</name>
<value>/opt/hadoop/hadoop-2.7.7/dfs/name</value>
</property>
<property>
<name>dfs.datanode.data.dir</name>
<value>/opt/hadoop/hadoop-2.7.7/dfs/data</value>
</property>
<property>
<name>dfs.webhdfs.enabled</name>
<value>true</value>
</property>
??? <!--后增,如果想让solr索引存放到hdfs中,则还须添加下面两个属性-->
?? ???? <property>
?? ??? ??? ?<name>dfs.webhdfs.enabled</name>
?? ??? ??? ?<value>true</value>
?? ??? ?</property>
?? ??? ?<property>
?? ??? ??? ?<name>dfs.permissions.enabled</name>
?? ??? ??? ?<value>false</value>
?? ??? ?</property>
?? ??? ?
?? ??? ?<!--【question2】SecondayNameNode默认与NameNode在同一台节点上,在实际生产过程中有安全隐患。解决方法:加入如下配置信息,指定NameNode和SecondaryNameNode节点位置-->
<property>
<name>dfs.http.address</name>
<value>Gwj:50070</value>
</property>
<property>
<name>dfs.namenode.secondary.http-address</name>
<value>Ssj:50090</value>
</property>
</configuration>
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<configuration>
<property>
<name>mapreduce.framework.name</name>
<value>local</value>
</property>
<!-- 指定mapreduce jobhistory地址 -->
<property>
<name>mapreduce.jobhistory.address</name>
<value>0.0.0.0:10020</value>
</property>
<!-- 任务历史服务器的web地址 -->
<property>
<name>mapreduce.jobhistory.webapp.address</name>
<value>0.0.0.0:19888</value>
</property>
</configuration>
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<configuration>
<property>
<name>yarn.resourcemanager.hostname</name>
<value>Gwj</value>
<description>指定resourcemanager所在的hostname</description>
</property>
<property>
<name>yarn.nodemanager.aux-services</name>
<value>mapreduce_shuffle</value>
<description>NodeManager上运行的附属服务。需配置成mapreduce_shuffle,才可运行MapReduce程序 </description>
</property>
</configuration>
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老版本是slaves文件,3.0.3 用 workers 文件代替 slaves 文件
将localhost删掉,加入dataNode节点的主机名
[root@Gwj ~]# cat /opt/hadoop/hadoop-2.7.7/etc/hadoop/slaves
Ssj
Pyf
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hdfs namenode -format
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/.../hadoop-2.7.7/sbin/start/start-all.sh
hdfs
/.../hadoop-2.7.7/sbin/start/start-dfs.sh
Yarn
/.../hadoop-2.7.7/sbin/start/start-yarn.sh
#start可替换为stop、status
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使用jps检验
hadoop
hdfs
Master---NameNode (SecondaryNameNode)
Slave---DataNode
Yarn
Master---ResourceManager
Slave---NodeManager
或者使用 “Master ip+50070”
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---以下的yarn未设置,注意<configuration>!!!
<property>
<name>yarn.resourcemanager.address</name>
<value>${yarn.resourcemanager.hostname}:8032</value>
</property>
<property>
<description>The address of the scheduler interface.</description>
<name>yarn.resourcemanager.scheduler.address</name>
<value>${yarn.resourcemanager.hostname}:8030</value>
</property>
<property>
<description>The http address of the RM web application.</description>
<name>yarn.resourcemanager.webapp.address</name>
<value>${yarn.resourcemanager.hostname}:8088</value>
</property>
<property>
<description>The https adddress of the RM web application.</description>
<name>yarn.resourcemanager.webapp.https.address</name>
<value>${yarn.resourcemanager.hostname}:8090</value>
</property>
<property>
<name>yarn.resourcemanager.resource-tracker.address</name>
<value>${yarn.resourcemanager.hostname}:8031</value>
</property>
<property>
<description>The address of the RM admin interface.</description>
<name>yarn.resourcemanager.admin.address</name>
<value>${yarn.resourcemanager.hostname}:8033</value>
</property>
<property>
<name>yarn.scheduler.maximum-allocation-mb</name>
<value>2048</value>
<discription>每个节点可用内存,单位MB,默认8182MB,根据阿里云ECS性能配置为2048MB</discription>
</property>
<property>
<name>yarn.nodemanager.vmem-pmem-ratio</name>
<value>2.1</value>
</property>
<property>
<name>yarn.nodemanager.resource.memory-mb</name>
<value>2048</value>
</property>
<property>
<name>yarn.nodemanager.vmem-check-enabled</name>
<value>false</value>
</property>
</configuration>
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Hadoop2.7.7 centos7 完全分布式 配置与问题随记
标签:生效 https secondary common hadoop exception comm led ado
原文地址:https://www.cnblogs.com/G-Aurora/p/13235764.html