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通常情況下對于一個全新的MySQL服務器，沒有任何數據供我們測試和使用。對此，MySQL為我們提供了一些樣本數據庫，我們可以基于這些數據庫作基本的操作以及壓力測試等等。本文描述的是安裝sakila數據庫。該數據庫需要安裝在MySQL 5.0以上的版本。以下是其描述。

1、下載種子數據庫

下載位置：>

2、安裝種子數據庫sakila

代碼如下:

[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、驗證安裝結果

代碼如下:

[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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