HIVE完全分布式集群安装过程（元数据库: MySQL）

本帖最后由 pig2 于 2014-2-14 13:39 编辑

阅读本文可以带着下面问题：
1.mysql创建用户，需要注意什么？

思考：
HIVE与hadoop是什么关系？hive是如何借助hadoop实现集群的？hadoop集群与hive集群是什么关系？

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

来自群组: Hadoop技术组