[Hive] 完全分布式安装过程（MetaStore: MySQL）
Hadoop版本：0.20.2
Hive版本：0.9.0
mysql版本: 5.6.11
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