应用程序开发人员常见的数据库开发错误有哪些?


当前回答

使用ORM进行批量更新 选择多于需要的数据。同样,这通常在使用ORM时完成 在循环中触发sql。 没有良好的测试数据,只在实时数据上注意到性能下降。

其他回答

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)。

因为“它太神奇了”或“不在我的数据库中”这样的原因,而放弃像Hibernate这样的ORM。 过度依赖像Hibernate这样的ORM,并试图将它硬塞到不合适的地方。

使用一些疯狂的构造和应用逻辑,而不是简单的COALESCE。

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.

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.