使用SQL作为美化的ISAM(索引顺序访问方法)包。特别是嵌套游标，而不是将SQL语句组合成一个更大的语句。这也算“滥用优化器”，因为实际上优化器能做的不多。这可以与非准备语句结合使用，以获得最大的效率:

DECLARE c1 CURSOR FOR SELECT Col1, Col2, Col3 FROM Table1

FOREACH c1 INTO a.col1, a.col2, a.col3
    DECLARE c2 CURSOR FOR
        SELECT Item1, Item2, Item3
            FROM Table2
            WHERE Table2.Item1 = a.col2
    FOREACH c2 INTO b.item1, b.item2, b.item3
        ...process data from records a and b...
    END FOREACH
END FOREACH

正确的解决方案(几乎总是)是将两个SELECT语句合并为一个:

DECLARE c1 CURSOR FOR
    SELECT Col1, Col2, Col3, Item1, Item2, Item3
        FROM Table1, Table2
        WHERE Table2.Item1 = Table1.Col2
        -- ORDER BY Table1.Col1, Table2.Item1

FOREACH c1 INTO a.col1, a.col2, a.col3, b.item1, b.item2, b.item3
    ...process data from records a and b...
END FOREACH

双循环版本的唯一优点是，您可以很容易地发现表1中值之间的中断，因为内部循环结束了。这可能是控制中断报告中的一个因素。

此外，应用程序中的排序通常是不允许的。

也许这不是一个反模式，但它惹恼了我，当某些数据库的DBA(好吧，我在这里说的是Oracle)用Oracle风格和代码约定编写SQL Server代码，当它运行如此糟糕时抱怨。受够了游标Oracle的人!SQL是基于设置的。

使用@@IDENTITY代替SCOPE_IDENTITY()

引自以下回答:

@@IDENTITY returns the last identity value generated for any table in the current session, across all scopes. You need to be careful here, since it's across scopes. You could get a value from a trigger, instead of your current statement. SCOPE_IDENTITY returns the last identity value generated for any table in the current session and the current scope. Generally what you want to use. IDENT_CURRENT returns the last identity value generated for a specific table in any session and any scope. This lets you specify which table you want the value from, in case the two above aren't quite what you need (very rare). You could use this if you want to get the current IDENTITY value for a table that you have not inserted a record into.

编写查询的开发人员没有很好地了解SQL应用程序(包括单个查询和多用户系统)的快慢。这包括对以下方面的无知:

physical I/O minimization strategies, given that most queries' bottleneck is I/O not CPU perf impact of different kinds of physical storage access (e.g. lots of sequential I/O will be faster than lots of small random I/O, although less so if your physical storage is an SSD!) how to hand-tune a query if the DBMS produces a poor query plan how to diagnose poor database performance, how to "debug" a slow query, and how to read a query plan (or EXPLAIN, depending on your DBMS of choice) locking strategies to optimize throughput and avoid deadlocks in multi-user applications importance of batching and other tricks to handle processing of data sets table and index design to best balance space and performance (e.g. covering indexes, keeping indexes small where possible, reducing data types to minimum size needed, etc.)

反向观点:过度痴迷于正常化。

大多数SQL/ rbdb系统提供了许多非常有用的特性(事务、复制)，即使对于非标准化的数据也是如此。磁盘空间很便宜，有时操作/过滤/搜索获取的数据比编写1NF模式更简单(更容易的代码，更快的开发时间)，并处理其中的所有麻烦(复杂的连接，讨厌的子选择等)。

我发现过度标准化的系统通常是不成熟的优化，特别是在开发的早期阶段。

(再想想……http://writeonly.wordpress.com/2008/12/05/simple-object-db-using-json-and-python-sqlite/)

同一查询中的相同子查询。