我讨厌开发人员使用嵌套的选择语句，甚至在查询的“select”部分中返回选择语句的结果的函数。

我很惊讶我在其他地方没有看到这个，也许我忽略了它，尽管@adam也有类似的问题。

例子:

SELECT
    (SELECT TOP 1 SomeValue FROM SomeTable WHERE SomeDate = c.Date ORDER BY SomeValue desc) As FirstVal
    ,(SELECT OtherValue FROM SomeOtherTable WHERE SomeOtherCriteria = c.Criteria) As SecondVal
FROM
    MyTable c

在这个场景中，如果MyTable返回10000行，结果就好像查询只运行了20001个查询，因为它必须运行初始查询，并对每一行结果查询一次其他表。

开发人员可以在只返回几行数据且子表通常只有少量数据的开发环境中使用这种查询，但在生产环境中，随着向表中添加更多数据，这种查询的成本可能会呈指数级增长。

一个更好的(不一定完美的)例子是这样的:

SELECT
     s.SomeValue As FirstVal
    ,o.OtherValue As SecondVal
FROM
    MyTable c
    LEFT JOIN (
        SELECT SomeDate, MAX(SomeValue) as SomeValue
        FROM SomeTable 
        GROUP BY SomeDate
     ) s ON c.Date = s.SomeDate
    LEFT JOIN SomeOtherTable o ON c.Criteria = o.SomeOtherCriteria

这允许数据库优化器将数据混合在一起，而不是从主表中重新查询每条记录，我通常发现，当我必须修复产生这个问题的代码时，我通常会将查询速度提高100%或更多，同时减少CPU和内存使用。

I think the biggest mistakes that all developers and DBAs do is believing too much on conventions. What I mean by that is that convention are only guide lines that for most cases will work but not necessarily always. I great example is normalization and foreign keys, I know most people wont like this, but normalization can cause complexity and cause loss of performance as well, so if there is no reason to move a phone number to a phones table, don't do it. On the foreign keys, they are great for most cases, but if you are trying to create something that can work by it self when needed the foreign key will be a problem in the future, and also you loose performance. Anyways, as I sad rules and conventions are there to guide, and they should always be though of but not necessarily implemented, analysis of each case is what should always be done.

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.

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。

a)在字符串中硬编码查询值 b)将数据库查询代码放在Windows窗体应用程序的“OnButtonPress”操作中

两者我都见过。

开发人员所犯的关键数据库设计和编程错误

Selfish database design and usage. Developers often treat the database as their personal persistent object store without considering the needs of other stakeholders in the data. This also applies to application architects. Poor database design and data integrity makes it hard for third parties working with the data and can substantially increase the system's life cycle costs. Reporting and MIS tends to be a poor cousin in application design and only done as an afterthought. Abusing denormalised data. Overdoing denormalised data and trying to maintain it within the application is a recipe for data integrity issues. Use denormalisation sparingly. Not wanting to add a join to a query is not an excuse for denormalising. Scared of writing SQL. SQL isn't rocket science and is actually quite good at doing its job. O/R mapping layers are quite good at doing the 95% of queries that are simple and fit well into that model. Sometimes SQL is the best way to do the job. Dogmatic 'No Stored Procedures' policies. Regardless of whether you believe stored procedures are evil, this sort of dogmatic attitude has no place on a software project. Not understanding database design. Normalisation is your friend and it's not rocket science. Joining and cardinality are fairly simple concepts - if you're involved in database application development there's really no excuse for not understanding them.