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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