linux安装卸载MySQL以及密码设置+Hive测试

linux系统卸载MYSQL

	1,先通过yum方式卸载mysql及相关组件 命令：yum remove mysql*
	2.通过命令：rpm -qa|grep -i mysql   查找系统的有关于mysql的文件
	3.然后通过命令：sudo rpm -e --nodeps 包名删除mysql有关软件
	4.卸载后/etc/my.cnf不会删除，需要进行手工删除通过命令：rm -rf /etc/my.cnf
	需要删除配置文件/etc/my.cnf和数据库文件/var/lib/mysql  删除命令 rm- rf 文件名/文件夹名
	5.最后再次通过命令 rpm -qa|grep -i mysql来确认系统中是否还含有mysql相关的文件，若没有，则表示卸载干净

Linux系统安装MySQL

	1.下载MySQL的Linux版本注意：下载好的MySQL你需要上传到Linux上才行，同时使用tar -zxvf压缩文件名解压
	2.进入Linux系统后，先切换成root用户，root用户有更高的权限，有权限卸载系统服务,su - root  回车，然后输入密码
	3.查看系统是否已经安装MySQL rpm -qa | grep mysql     或 rpm -qa | grep -i mysql
	4.安装命令   rpm -ivh 服务名
	我们需要安装MySQL服务端(Server)和客户端(client)
	rpm -ivh MySQL-server-5.6.30-1. linux_glibc2.5. x86_64.rpm
	rpm -ivh MySQL-client-5.6.30-1. linux_glibc2.5. x86_64.rpm
	注意： 必须安装客户端，否则你在Linux上通过命令是不能进入MySQL的，如输入命令mysql会提示错误.
	开启MySQL服务 service mysql start
	5.安装完成后，可以通过命令netstat -nat查看Linux的端口监控，看看Linux有没有在监控3306端口
	
	yum install 安装方式
	
	1.1、查看有没有安装过：yum list installed mysql*
	1.2、查看有没有安装包：yum list mysql*
	1.3、安装mysql客户端：yum install mysql
	1.4、安装mysql 服务器端：yum install mysql-server
	1.5、数据库字符集设置mysql配置文件/etc/my.cnf中加入default-character-set=utf8
	1.6、启动mysql服务：service mysqld start或者/etc/init.d/mysqld start
	1.7、开机启动：sudo chkconfig mysqld on，chkconfig --list | grep mysql*
	mysqld             0:关闭    1:关闭    2:启用    3:启用    4:启用    5:启用    6:关闭
	1.8、停止：service mysqld stop
	1.9、开启登录创建root管理员：mysqladmin -u root password 123456
	登录： mysql -u root -p输入密码即可
	2.0、忘记密码：
	service mysqld stop
	mysqld_safe --user=root --skip-grant-tables
	mysql -u root
	use mysql
	update user set password=password("new_pass") where user="root";
	flush privileges; 

MySQL修改初始密码

	注意：先stop你的myslq服务，service mysql stop或者  /etc/init.d/mysqld stop
	
	1.若没有root权限，这种情况下，我们可以采用类似安全模式的方法修改初始密码,先执行命令  mysqld_safe --skip-grant-tables &   （设置成安全模式）&，表示在后台运行，不再后台运行的话，就再打开一个终端咯
	
	<1># mysql
	mysql> use mysql;
	mysql> UPDATE user SET password=password("123456") WHERE user='root';    （会提示修改成功query ok）
	mysql> flush privileges;
	mysql> exit;
	
	<2>在mysql系统外，使用mysqladmin
	# mysqladmin -u root -p password "test123"
	Enter password: 【输入原来的密码】
	
	<3>. 可以登录mysql系统的情况下，通过登录mysql系统修改
	# mysql -uroot -p
	Enter password: 【输入原来的密码】
	mysql>use mysql;
	mysql> update user set password=password("123456") where user='root';
	mysql> flush privileges;
	mysql> exit; 
	
	2.将MySQL加入到系统启动项中 chkconfig mysql on 查看MySQL是否加入到系统启动项中  chkconfig --list | grep mysql
	3.登录你的MySQL系统  mysql -uroot -p回车，然后输入你的密码
	4.添加系统mysql组和mysql用户：执行命令：groupadd mysql和useradd -r -g mysql mysql
	5.修改当前data目录拥有者为mysql用户：执行命令 chown -R mysql:mysql data
	6.把mysql客户端放到默认路径：ln -s /usr/local/mysql/bin/mysql /usr/local/bin/mysql
	注意：建议使用软链过去，不要直接包文件复制，便于系统安装多个版本的mysql

MYSQL服务的状态、启动、停止、重启命令

	service mysql start      或    /etc/init.d/mysql start
	service mysql stop      或    /etc/init.d/mysql stop
	service mysql restart   或    /etc/init.d/mysql restart
	service mysql status    或    /etc/init.d/mysql status

hive的安装及配置

	1.启动设置mysql
	启动mysql服务
	sudo service mysql start

	2.设置为开机自启动
	sudo chkconfig mysql on

	3.设置root用户登录密码
	sudo /usr/bin/mysqladmin -u root password 'root123'

	4.登录mysql  以root用户身份登录
	mysql -uroot -proot123
	
	5.创建hive用户,数据库等
	insert into mysql.user(Host,User,Password) 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; 

	6.退出mysql 
	exit
	
	7.验证hive用户
	mysql -uhive -phive
	show databases;
	+--------------------+
	| Database           |
	+--------------------+
	| information_schema |
	| hive               |
	| test               |
	+--------------------+
	3 rows in set (0.00 sec)
	退出mysql
	exit

安装hive

	1，解压安装包
	cd  ~
	tar -zxvf apache-hive-1.1.0-bin.tar.gz
	2，建立软连接
	ln -s apache-hive-1.1.0-bin hive
	3，添加环境变量
	vi  .bash_profile
	导入下面的环境变量
	export HIVE_HOME=/home/hdpsrc/hive
	export PATH=$PATH:$HIVE_HOME/bin

	使其有效
	source .bash_profile

配置hive
4.修改hive-site.xml
cp hive/conf/hive-default.xml.template hive/conf/hive-site.xml
编辑hive-site.xml

	主要修改以下参数
	<property> 
	   <name>javax.jdo.option.ConnectionURL </name> 
	   <value>jdbc:mysql://Master:3306/hive </value> 
	</property> 
	 
	<property> 
	   <name>javax.jdo.option.ConnectionDriverName </name> 
	   <value>com.mysql.jdbc.Driver </value> 
	</property>

	<property> 
	   <name>javax.jdo.option.ConnectionPassword </name> 
	   <value>hive </value> 
	</property> 
	 
	<property> 
	   <name>hive.hwi.listen.port </name> 
	   <value>9999 </value> 
	   <description>This is the port the Hive Web Interface will listen on </descript ion> 
	</property> 

	<property> 
	   <name>datanucleus.autoCreateSchema </name> 
	   <value>true</value> 
	</property> 
	 
	<property> 
	   <name>datanucleus.fixedDatastore </name> 
	   <value>false</value> 
	</property> 
	</property> 

	  <property>
	    <name>javax.jdo.option.ConnectionUserName</name>
	    <value>hive</value>
	    <description>Username to use against metastore database</description>
	  </property>

	  <property>
	    <name>hive.exec.local.scratchdir</name>
	    <value>/home/hdpsrc/hive/iotmp</value>
	    <description>Local scratch space for Hive jobs</description>
	  </property>
	  <property>
	    <name>hive.downloaded.resources.dir</name>
	    <value>/home/hdpsrc/hive/iotmp</value>
	    <description>Temporary local directory for added resources in the remote file system.</description>
	  </property>
	  <property>
	    <name>hive.querylog.location</name>
	    <value>/home/hdpsrc/hive/iotmp</value>
	    <description>Location of Hive run time structured log file</description>
	  </property>
	  
	5,拷贝mysql-connector-java-5.1.6-bin.jar 到hive 的lib下面
	mv /home/hdpsrc/Desktop/mysql-connector-java-5.1.6-bin.jar /home/hdpsrc/hive/lib/
	cp  mysql-connector-java-5.1.1.18-bin  /usr/hive/lib 

	6，把jline-2.12.jar拷贝到hadoop相应的目录下，替代jline-0.9.94.jar，否则启动会报错
	cp /home/hdpsrc/hive/lib/jline-2.12.jar /home/hdpsrc/hadoop-2.6.0/share/hadoop/yarn/lib/
	mv /home/hdpsrc/hadoop-2.6.0/share/hadoop/yarn/lib/jline-0.9.94.jar 
	/home/hdpsrc/hadoop-2.6.0/share/hadoop/yarn/lib/jline-0.9.94.jar.bak /
	7，穿件hive临时文件夹
	mkdir /home/hdpsrc/hive/iotmp
	
	四，启动测试hive
	
	初始化hive元数据仓库 
            该执行目录$HIVE_HOME/bin 
            bin]#./schematool -initSchema -dbType mysql -userName hive -passWord hive
            
	启动hadoop后，执行hive命令
	
	#hive

	测试输入 show database;
	hive> show databases;
	OK
	default
	Time taken: 0.907 seconds, Fetched: 1 row(s)

hive 产生的log 的路径

	<property>
	      <name>hive.querylog.location</name>
	      <value>${system:java.io.tmpdir}/${system:user.name}</value>
	      <description>Location of Hive run time structured log file</description>
       </property>
       修改hive-log4j.properties配置文件

      cp hive-log4j.properties.template  hive-log4j.proprties

       # list of properties
      property.hive.log.level = INFO
      property.hive.root.logger = DRFA
      property.hive.log.dir = ${sys:java.io.tmpdir}/${sys:user.name}
      property.hive.log.file = hive.log
      property.hive.perflogger.log.level = INFO
      

	1) 在mysql里创建hive用户，并赋予其足够权限
	[root@node01 mysql]# mysql -u root -p
	Enter password:

	mysql> create user 'hive' identified by 'hive';
	Query OK, 0 rows affected (0.00 sec)

	mysql> grant all privileges on *.* to 'hive' with grant option;
	Query OK, 0 rows affected (0.00 sec)

	mysql> flush privileges;
	Query OK, 0 rows affected (0.01 sec)

	2）测试hive用户是否能正常连接mysql，并创建hive数据库
	[root@node01 mysql]# mysql -u hive -p
	Enter password:

	mysql> create database hive;
	Query OK, 1 row affected (0.00 sec)

	mysql> use hive;
	Database changed
	mysql> show tables;
	Empty set (0.00 sec)

	3）解压缩hive安装包
	tar -xzvf hive-0.9.0.tar.gz
	[hadoop@node01 ~]$ cd hive-0.9.0
	[hadoop@node01 hive-0.9.0]$ ls
	bin  conf  docs  examples  lib  LICENSE  NOTICE  README.txt  RELEASE_NOTES.txt  scripts  src

	4）下载mysql连接java的驱动 并拷入hive home的lib下
	[hadoop@node01 ~]$ mv mysql-connector-java-5.1.24-bin.jar ./hive-0.9.0/lib

	5）修改环境变量，把Hive加到PATH
	/etc/profile
	export HIVE_HOME=/home/hadoop/hive-0.9.0
	export PATH=$PATH:$HIVE_HOME/bin

	6）修改hive-env.sh
	[hadoop@node01 conf]$ cp hive-env.sh.template hive-env.sh
	[hadoop@node01 conf]$ vi hive-env.sh

	7）拷贝hive-default.xml 并命名为 hive-site.xml
	修改四个关键配置 为上面mysql的配置
	[hadoop@node01 conf]$ cp hive-default.xml.template hive-site.xml
	[hadoop@node01 conf]$ vi hive-site.xml
	<property>
	  <name>javax.jdo.option.ConnectionURL</name>
	  <value>jdbc:mysql://localhost:3306/hive?createDatabaseIfNotExist=true</value>
	  <description>JDBC connect string for a JDBC metastore</description>
	</property>

	<property>
	  <name>javax.jdo.option.ConnectionDriverName</name>
	  <value>com.mysql.jdbc.Driver</value>
	  <description>Driver class name for a JDBC metastore</description>
	</property>

	<property>
	  <name>javax.jdo.option.ConnectionUserName</name>
	  <value>hive</value>
	  <description>username to use against metastore database</description>
	</property>

	<property>
	  <name>javax.jdo.option.ConnectionPassword</name>
	  <value>hive</value>
	  <description>password to use against metastore database</description>
	</property>

	8）启动Hadoop，打开hive shell 测试
	[hadoop@node01 conf]$ start-all.sh

	hive> load data inpath 'hdfs://node01:9000/user/hadoop/access_log.txt'
	    > overwrite into table records;
	Loading data to table default.records
	Moved to trash: hdfs://node01:9000/user/hive/warehouse/records
	OK
	Time taken: 0.526 seconds
	hive> select ip, count(*) from records
	    > group by ip;
	Total MapReduce jobs = 1
	Launching Job 1 out of 1
	Number of reduce tasks not specified. Estimated from input data size: 1
	In order to change the average load for a reducer (in bytes):
	  set hive.exec.reducers.bytes.per.reducer=<number>
	In order to limit the maximum number of reducers:
	  set hive.exec.reducers.max=<number>
	In order to set a constant number of reducers:
	  set mapred.reduce.tasks=<number>
	Starting Job = job_201304242001_0001, Tracking URL = http://node01:50030/jobdetails.jsp?jobid=job_201304242001_0001
	Kill Command = /home/hadoop/hadoop-0.20.2/bin/../bin/hadoop job  -Dmapred.job.tracker=192.168.231.131:9001 -kill job_201304242001_0001
	Hadoop job information for Stage-1: number of mappers: 1; number of reducers: 1
	2013-04-24 20:11:03,127 Stage-1 map = 0%,  reduce = 0%
	2013-04-24 20:11:11,196 Stage-1 map = 100%,  reduce = 0%
	2013-04-24 20:11:23,331 Stage-1 map = 100%,  reduce = 100%
	Ended Job = job_201304242001_0001
	MapReduce Jobs Launched:
	Job 0: Map: 1  Reduce: 1   HDFS Read: 7118627 HDFS Write: 9 SUCCESS
	Total MapReduce CPU Time Spent: 0 msec
	OK
	NULL    28134
	Time taken: 33.273 seconds

	records在HDFS中就是一个文件：
	[hadoop@node01 home]$ hadoop fs -ls /user/hive/warehouse/records
	Found 1 items
	-rw-r--r--   2 hadoop supergroup    7118627 2013-04-15 20:06 /user/hive/warehouse/records/access_log.txt