[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

javax.jdo.option.ConnectionURL

jdbc:mysql://localhost:3306/hive?createDatabaseIfNotExist=true

JDBC connect string for a JDBC metastore

javax.jdo.option.ConnectionDriverName

com.mysql.jdbc.Driver

Driver class name for a JDBC metastore

javax.jdo.option.ConnectionUserName

hive

username to use against metastore database

javax.jdo.option.ConnectionPassword

hive

password to use against metastore database

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=

In order to limit the maximum number of reducers:

set hive.exec.reducers.max=

In order to set a constant number of reducers:

set mapred.reduce.tasks=

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