非常大的事务，插入/更新大量数据，然后重新加载它。基本上，这是因为没有考虑数据库工作的多用户环境。 过度使用函数，特别是作为select和where子句中的结果，导致函数被反复调用以获取结果。我认为，这符合他们试图以他们更习惯的过程方式工作而不是充分利用SQL的一般情况。

第一个问题?他们只在玩具数据库上测试。因此，他们不知道当数据库变大时，他们的SQL将会爬行，并且稍后必须有人来修复它(您可以听到的声音是我咬牙切齿的声音)。

根据我的经验: 不与有经验的dba沟通。

不了解数据库并发模型以及它如何影响开发。事后添加索引和调整查询很容易。然而，应用程序的设计没有适当考虑热点，资源争用 和正确的操作(假设您刚刚阅读的内容仍然有效!)可能需要在数据库和应用层中进行重大更改，以便稍后纠正。

对于基于sql的数据库:

Not taking advantage of CLUSTERED INDEXES or choosing the wrong column(s) to CLUSTER. Not using a SERIAL (autonumber) datatype as a PRIMARY KEY to join to a FOREIGN KEY (INT) in a parent/child table relationship. Not UPDATING STATISTICS on a table when many records have been INSERTED or DELETED. Not reorganizing (i.e. unloading, droping, re-creating, loading and re-indexing) tables when many rows have been inserted or deleted (some engines physically keep deleted rows in a table with a delete flag.) Not taking advantage of FRAGMENT ON EXPRESSION (if supported) on large tables which have high transaction rates. Choosing the wrong datatype for a column! Not choosing a proper column name. Not adding new columns at the end of the table. Not creating proper indexes to support frequently used queries. creating indexes on columns with few possible values and creating unnecessary indexes. ...more to be added.

我想补充一点: 偏好“优雅”代码而不是高性能代码。在应用程序开发人员看来，对数据库最有效的代码通常是丑陋的。

Believing that nonsense about premature optimization. Databases must consider performance in the original design and in any subsequent development. Performance is 50% of database design (40% is data integrity and the last 10% is security) in my opinion. Databases which are not built from the bottom up to perform will perform badly once real users and real traffic are placed against the database. Premature optimization doesn't mean no optimization! It doesn't mean you should write code that will almost always perform badly because you find it easier (cursors for example which should never be allowed in a production database unless all else has failed). It means you don't need to look at squeezing out that last little bit of performance until you need to. A lot is known about what will perform better on databases, to ignore this in design and development is short-sighted at best.