背景
我是计算机科学一年级的学生，我在我爸爸的小公司兼职。我没有任何实际应用程序开发的经验。我用Python写过脚本，用C写过一些课程，但没有像这样的。
我爸爸有一家小型培训公司，目前所有的课程都是通过外部网络应用程序安排、录制和跟踪的。有一个导出/“报告”功能，但它是非常通用的，我们需要特定的报告。我们无法访问实际的数据库来运行查询。我被要求建立一个自定义报告系统。
我的想法是每天晚上创建通用的CSV导出，并将它们导入(可能使用Python)到办公室托管的MySQL数据库中，从那里我可以运行所需的特定查询。我没有数据库方面的经验，但了解最基本的知识。我读了一些关于数据库创建和标准表单的知识。
我们可能很快就会有国际客户，所以我希望数据库不会爆炸，如果/当这种情况发生时。我们目前也有一些大公司作为客户，他们有不同的部门(例如ACME母公司、ACME医疗保健部门、ACME身体护理部门)。
我想到的模式如下:
From the client perspective:
Clients is the main table
Clients are linked to the department they work for
Departments can be scattered around a country: HR in London, Marketing in Swansea, etc.
Departments are linked to the division of a company
Divisions are linked to the parent company
From the classes perspective:
Sessions is the main table
A teacher is linked to each session
A statusid is given to each session. E.g. 0 - Completed, 1 - Cancelled
Sessions are grouped into "packs" of an arbitrary size
Each packs is assigned to a client
我在一张纸上“设计”(更像是乱写)模式，试图将其正常化到第三种形式。然后我把它插入MySQL工作台，它使它对我来说都很漂亮:(点击这里查看全尺寸图形)
(来源:maian.org)
我将运行的示例查询
哪些仍有信用的客户是不活跃的(未来没有安排课程的客户)
每个客户/部门/部门的出勤率是多少(以每次会议的状态id来衡量)
一个老师一个月上几节课
标记出勤率低的客户
人力资源部门的自定义报告，包括其部门人员的出勤率
问题(s)
这是设计过度还是我的方向正确?
对于大多数查询，需要连接多个表是否会导致很大的性能损失?
我给客户端添加了一个“lastsession”列，因为这可能是一个常见的查询。这是一个好主意，还是我应该保持数据库严格规范化?
谢谢你的宝贵时间
我想到了几件事:
The tables seemed geared to reporting, but not really running the business. I would think when a client signs up, there's essentially an order being placed for the client attending a list of sessions, and that order might be for multiple employees in one company. It would seem an "order" table would really be at the center of your system and driving your data capture and eventual reporting. (Compare the paper documents you've been using to run the business with your database design to see if there's a logical match.)
Companies often don't have divisions. Employees sometimes change divisions/departments, maybe even mid-session. Companies sometimes add/delete/rename divisions/departments. Make sure the possible realtime changing contents of your tables doesn't make subsequent reporting/grouping difficult. With so much contact data split over so many tables, you might have to enforce very strict data entry validation to keep your reports meaningful and inclusive. Eg, when a new client is added, making sure his company/division/department/city match the same values as his coworkers.
The "packs" concept isn't clear at all.
Since you indicate it's a small business, it would be surprising if performance would be an issue, considering the speed and capacity of current machines.
以下是关于你问题的更多答案:
1)对于第一次遇到这种问题的人来说，你说得很对。我认为到目前为止，其他人在这个问题上的建议几乎涵盖了这个问题。好工作!
2 & 3)性能的下降很大程度上取决于为特定的查询/过程设置和优化正确的索引，更重要的是记录的数量。除非您的主表中有超过一百万条记录，否则您似乎已经走上了一条足够主流的设计道路，在合理的硬件上，性能不会成为问题。
That said, and this relates to your question 3, with the start you have you probably shouldn't really be overly worried about performance or hyper-sensitivity to normalization orthodoxy here. This is a reporting server you are building, not a transaction based application backend, which would have a much different profile with respect to the importance of performance or normalization. A database backing a live signup and scheduling application has to be mindful of queries that take seconds to return data. Not only does a report server function have more tolerance for complex and lengthy queries, but the strategies to improve performance are much different.
For example, in a transaction based application environment your performance improvement options might include refactoring your stored procedures and table structures to the nth degree, or developing a caching strategy for small amounts of commonly requested data. In a reporting environment you can certainly do this but you can have an even greater impact on performance by introducing a snapshot mechanism where a scheduled process runs and stores pre-configured reports and your users access the snapshot data with no stress on your db tier on a per request basis.
所有这些都是为了说明根据所创建的db的角色不同，所采用的设计原则和技巧可能会有所不同。我希望这对你们有帮助。
以下是基于商业智能/报告专家和战略/规划经理角色的评论:
I agree with Larry's direction above. IMHO, It's not so much over engineered, some things just look a little out of place. To keep it simple, I would tag client directly to a Company ID, Department Description, Division Description, Department Type ID, Division Type ID. Use Department Type ID and Division Type ID as references to lookup tables and internal reporting/analysis fields for long term consistency.
Packs table contains "Credit" column, shouldn't that actually be tied to the Client base table so if they many packs you can see how much credit owed is left for future classes? The application can take care of the calc and store it centrally in the Client table.
Company info could use many more fields, including the obvious address/phone/etc. information. I'd also be prepared to add in D&B "DUNs" columns (Site/Branch/Ultimate) long term, Dun and Bradstreet (D&B) has a huge catalog of companies and you'll find later down the road their information is very helpful for reporting/analysis. This will take care of the multiple division issue you mention, and allow you to roll up their hierarchy for sub/division/branches/etc. of large corps.
You don't mention how many records you'll be working with which could imply setting yourself up for a large development initiative which could have been done quicker and far fewer headaches with prepackaged "reporting" software. If your not dealing with a large database (< 65000) rows, make sure MS-Access, OpenOffice (Base) or related report/app dev solutions couldn't do the trick. I use Oracle's free APEX software quite a bit myself, it comes with their free database Oracle XE just download it from their site.
FYI - Reporting insight: for large databases, you typically have two database instances a) transaction database for recording each detailed record. b) reporting database (data mart/data warehouse) housed on a separate machine. For more information search google both Star Schema and Snowflake Schema.
的问候。
