通常情况下对于一个全新的MySQL服务器，没有任何数据供我们测试和使用。对此，MySQL为我们提供了一些样本数据库，我们可以基于这些数据库作基本的操作以及压力测试等等。本文描述的是安装sakila数据库。该数据库需要安装在MySQL 5.0以上的版本。以下是其描述。
1、下载种子数据库
下载位置：
2、安装种子数据库sakila
代码如下:
[root@localhost ~]# unzip sakila-db.zip
Archive: sakila-db.zip
creating: sakila-db/
inflating: sakila-db/sakila-schema.sql
inflating: sakila-db/sakila.mwb
inflating: sakila-db/sakila-data.sql
The sakila-schema.sql file contains all the CREATE statements required to create the structure of the Sakila database including tables, views, stored procedures, and triggers.
The sakila-data.sql file contains the INSERT statements required to populate the structure created by the sakila-schema.sql file, along with definitions for triggers that must be created after the initial data load.
The sakila.mwb file is a MySQL Workbench data model that you can open within MySQL Workbench to examine the database structure. For more information, see MySQL Workbench.
[root@localhost ~]# ls
anaconda-ks.cfg Desktop install.log install.log.syslog sakila-db sakila-db.zip
[root@localhost ~]# cd sakila-db
[root@localhost sakila-db]# ls
sakila-data.sql sakila.mwb sakila-schema.sql
[root@localhost sakila-db]# mysql -uroot -p <sakila-schema.sql
Enter password:
[root@localhost sakila-db]# mysql -uroot -p <sakila-data.sql
Enter password:
3、验证安装结果
代码如下:
[root@localhost sakila-db]# mysql
)]> show databases;
+--------------------+
| Database |
+--------------------+
| information_schema |
| mysql |
| performance_schema |
| sakila |
| scottdb |
| tempdb |
| test |
+--------------------+
7 rows in set (0.01 sec)
)]> use sakila
Database changed
]> show tables;
+----------------------------+
| Tables_in_sakila |
+----------------------------+
| actor |
| actor_info |
| address |
| category |
| city |
| country |
| customer |
| customer_list |
| film |
| film_actor |
| film_category |
| film_list |
| film_text |
| inventory |
| language |
| nicer_but_slower_film_list |
| payment |
| rental |
| sales_by_film_category |
| sales_by_store |
| staff |
| staff_list |
| store |
+----------------------------+
23 rows in set (0.00 sec)
]> select count(*) from customer;
+----------+
| count(*) |
+----------+
| 599 |
+----------+
1 row in set (0.01 sec)
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