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 Enter password: [root@localhost sakila-db]# mysql -uroot -p 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) 更多信息请查看IT技术专栏