我是靠谱客的博主 沉默煎饼,最近开发中收集的这篇文章主要介绍HA HADOOP集群和HIVE部署,觉得挺不错的,现在分享给大家,希望可以做个参考。

概述

HDFS HA HADOOP集群部署

1.集群环境节点分布

JournalNode: bigdatasvr01 ,  bigdatasvr02 ,bigdatasvr03
namenode: bigdatasvr02(active),bigdatasvr03(standby)
datanode: bigdatasvr01, bigdatasvr03
nodemanager: bigdatasvr01, bigdatasvr03
ResourceManager:   bigdatasvr02

2.修改主机名


3.设置免密码登录

每台机器上都执行命令:
ssh-keygen -t rsa -''
bigdatasvr02 的公钥拷贝到 bigdatasvr01 , bigdatasvr03上
ssh-copy-id hadoop@bigdatasvr01
ssh-copy-id hadoop@bigdatasvr03
至少要保证bigdatasvr02免密码登录到bigdatasvr01 ,bigdatasvr03上

4.设置环境变量

1.设置JDK环境变量
2.设置hadoop环境变量,在/etc/profile.d下新建一个hadoop.sh:
export HADOOP_HOME=/home/hadoop/hadoop
export HADOOP_COMMON_LIB_NATIVE_DIR=$HADOOP_HOME/lib/native
export HADOOP_CONF_DIR=$HADOOP_HOME/etc/hadoop
export HADOOP_OPTS="-Djava.library.path=$HADOOP_HOME/lib"
export PATH=$HADOOP_HOME/bin:$HADOOP_HOME/sbin:$PATH
使其生效:
source hadoop.sh

5.搭建hadoop集群

用的hadoop是apache原生包hadoop-2.7.1.tar.gz

5.1 修改配置文件

把下面6个文件修改好,然后拷贝到所有节点。
hadoop-env.sh,core-stie.xml,hdfs-site.xml,yarn-site.xml,mapred-site.xml,slaves   

5.1.1修改core-stie.xml

	<property>
		<name>fs.defaultFS</name>
		<value>hdfs://bigdatasvr02:9000</value>
	</property>
	<property>
		<name>io.file.buffer.size</name>
		<value>131072</value>
	</property>
	<property>
		<name>hadoop.tmp.dir</name>
		<value>file:/home/hadoop/hadoop/tmp</value>
		<description>Abasefor other temporary directories.</description>
	</property>

5.1.2修改hdfs-site.xml

	 <property>
		<name>dfs.nameservices</name>
		<value>hadoopcluster</value>
	</property>
	
	<property>
		<name>dfs.ha.namenodes.hadoopcluster</name>
		<value>nn1,nn2</value>
	</property>

	<property>
		<name>dfs.namenode.rpc-address.hadoopcluster.nn1</name>
		<value>bigdatasvr02:9000</value>
	</property>
	<property>
		<name>dfs.namenode.rpc-address.hadoopcluster.nn2</name>
		<value>bigdatasvr03:9000</value>
	</property>
	<property>
		<name>dfs.namenode.http-address.hadoopcluster.nn1</name>
		<value>bigdatasvr02:50070</value>
	</property>
	<property>
		<name>dfs.namenode.http-address.hadoopcluster.nn2</name>
		<value>bigdatasvr03:50070</value>
	</property>
	
	<property>
		<name>dfs.namenode.name.dir</name>
		<value>file:/home/hadoop/hadoop/ha/hdfs/name</value>
		<description>allow multiple directory split by ,</description>
	</property>
	<property>
		<name>dfs.namenode.shared.edits.dir</name>
		<value>qjournal://bigdatasvr01:8485;bigdatasvr02:8485;bigdatasvr03:8485/hadoopcluster</value>
	</property>
	<property>
		<name>dfs.datanode.data.dir</name>
		<value>file:/home/hadoop/hadoop/ha/hdfs/data</value>
		<description>allow multiple directory split by ,</description>
	</property>

	<property>
		<name>dfs.ha.automatic-failover.enabled</name>
		<value>false</value>
	<description>Whether automatic failover is enabled. See the HDFS High
Availability documentation for details on automatic HA configuration.</description>
	</property>
	<property>
		<name>dfs.journalnode.edits.dir</name>
		<value>/home/hadoop/hadoop/ha/hdfs/journal</value>
	</property>
	
	 <property>
	  <name>dfs.replication</name>
	  <value>2</value>
	 </property>

	<property>
		 <name>dfs.webhdfs.enabled</name>
	     <value>true</value>
	 </property>

5.1.3修改mapred-site.xml

 <property>
   <name>mapreduce.framework.name</name>
   <value>yarn</value>
 </property>
  
 <property>
	<name>mapreduce.jobhistory.address</name>
	<value>bigdatasvr03:10020</value>
 </property>
 <property>
	<name>mapreduce.jobhistory.webapp.address</name>
	<value>bigdatasvr03:19888</value>
 </property>

5.1.4修改yarn-site.xml

	<property>
		<description>The hostname of the RM.</description>
		<name>yarn.resourcemanager.hostname</name>
		<value>bigdatasvr02</value>
	</property>    
	<property>
		<description>The address of the applications manager interface in the RM.</description>
		<name>yarn.resourcemanager.address</name>
		<value>${yarn.resourcemanager.hostname}:8032</value>
	</property>
	<property>
		<description>The http address of the RM web application.</description>
		<name>yarn.resourcemanager.webapp.address</name>
		<value>${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>
	   <name>yarn.resourcemanager.scheduler.address</name>
	   <value>${yarn.resourcemanager.hostname}:8030</value>
	</property>
	<property>
		<description>The address of the RM admin interface.</description>
		<name>yarn.resourcemanager.admin.address</name>
		<value>${yarn.resourcemanager.hostname}:8033</value>
	</property>
	<property>
		<description>List of directories to store localized files in. An application's localized file directory will be found in:
${yarn.nodemanager.local-dirs}/usercache/${user}/appcache/application_${appid}.
Individual containers' work directories, called container_${contid}, will
be subdirectories of this.</description>
		<name>yarn.nodemanager.local-dirs</name>
		<value>/home/hadoop/hadoop/ha/yarn/local</value>
	</property>
	<property>
		<description>Whether to enable log aggregation</description>
		<name>yarn.log-aggregation-enable</name>
		<value>true</value>
	</property>
	<property>
		<description>Where to aggregate logs to.</description>
		<name>yarn.nodemanager.remote-app-log-dir</name>
		<value>/home/hadoop/logs</value>
	</property>
	
	<property>
		<description>Number of CPU cores that can be allocated for containers.</description>
		<name>yarn.nodemanager.resource.cpu-vcores</name>
		<value>4</value>
	</property>
	<property>
		<description>the valid service name should only contain a-zA-Z0-9_ and can not start with numbers</description>
		<name>yarn.nodemanager.aux-services</name>
		<value>mapreduce_shuffle</value>
	</property>

5.1.5修改slaves 

bigdatasvr01
bigdatasvr03
修改完配置文件后,将修改好的安装包分别拷贝到bigdatasvr01,bigdatasvr02,bigdatasvr03节点的/home/hadoop目录下.

5.2 启动journalnode(每个节点上都运行)

运行命令: sbin/hadoop-daemon.sh start  journalnode


5.3 格式化namenode(nn1)

bigdatasvr02 上运行命令: bin/hdfs namenode -format


5.4 启动namenode (nn1)

只有当namenode格式化成功之后才能正常启动namenode
bigdatasvr02 上运行命令: sbin/hadoop-daemon.sh start namenode


5.5格式化namenode(nn2)

bigdatasvr03 上运行命令: bin/hdfs namenode -bootstrapStandby 


5.6启动namenode (nn2)

bigdatasvr03 上运行命令: sbin/hadoop-daemon.sh start namenode


在浏览器上访问
http://bigdatasvr02:50070/
当前是 standby 状态

在浏览器上访问 http://bigdatasvr03:50070/ 当前是 standby 状态



5.7激活namenode

bigdatasvr02 上运行命令: bin/hdfs haadmin -transitionToActive nn1
在浏览器上访问http://bigdatasvr02:50070


5.8启动datanode

bigdatasvr02 上运行命令: sbin/hadoop-daemons.sh start datanode


5.9启动yarn

bigdatasvr02 上运行命令: sbin/start-yarn.sh
bigdatasvr02生成 ResourceManager进程


在datanode节点上生成 NodeManager进程


5.10执行一个MapReduce
hadoop jar share/hadoop/mapreduce/hadoop-mapreduce-examples-2.7.1.jar pi 2 10  


5.11启动日志记录服务


bigdatasvr03 上运行命令: sbin/mr-jobhistory-daemon.sh   start historyserver


在浏览器中输入:http://bigdatasvr03:19888/


6.停止hadoop集群

sbin/stop-all.sh

查看集群状态:
bin/hdfs dfsadmin -report

7.Hive部署安装

7.1安装mysql


7.2创建hive数据库和用户

1.登录mysql  以root用户身份登录

mysql -uroot -p123123

2.创建hive用户,数据库

insert into user(Host,User,Password,ssl_cipher,x509_issuer,x509_subject) values("localhost","hive",password("hive"),"","","");
create database hive;
grant all on hive.* to hive@'%'  identified by 'hive';
grant all on hive.* to hive@'localhost'  identified by 'hive';
flush privileges; 

7.3验证hive用户



7.4安装Hive

使用安装包为:hive-1.2.1-bin.tar.gz

1.下载解压安装包

2.配置hive环境变量:vi /etc/profile.d/hadoop.sh 


使其生效:source /etc/profile.d/hadoop.sh

3.修改hive-site.xml


4.启动hive的metastore

nohup hive --service metastore >> metaserver_logs/nohup.out 2>&1 & 


5.启动hive的jdbc等服务程序,提供jdbc、beeline远端连接服务

hive --service hiveserver2 >> hiveserver_logs/nohup.out 2>&1 &


6.启动测试hive

执行hive命令:hive


7.创建hive表

create table  inter_table (id int,
        name string,
        age int,
        tele string)
    ROW FORMAT DELIMITED
    FIELDS TERMINATED BY 't'
    STORED AS TEXTFILE;
如果在创建表的时候卡很久一段时间并报错则需要设置mysql中hive数据库的编码为latin1.

最后

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