同一查询中的相同子查询。

FROM TableA, TableB WHERE语法用于连接而不是FROM TableA内部连接TableB上 假设查询将以某种方式返回，而不放入ORDER BY子句，因为这是在查询工具中测试时显示的方式。

没有使用With子句或适当的连接并依赖子查询。

反模式:

select 
 ...
from data
where RECORD.STATE IN (
          SELECT STATEID
            FROM STATE
           WHERE NAME IN
                    ('Published to test',
                     'Approved for public',
                     'Published to public',
                     'Archived'
                    ))

好: 我喜欢使用with子句使我的意图更易于阅读。

with valid_states as (
          SELECT STATEID
            FROM STATE
           WHERE NAME IN
                    ('Published to test',
                     'Approved for public',
                     'Published to public',
                     'Archived'
                    )
select  ... from data, valid_states
where data.state = valid_states.state

最好的:

select 
  ... 
from data join states using (state)
where 
states.state in  ('Published to test',
                     'Approved for public',
                     'Published to public',
                     'Archived'
                    )

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.)

Human readable password fields, egad. Self explanatory. Using LIKE against indexed columns, and I'm almost tempted to just say LIKE in general. Recycling SQL-generated PK values. Surprise nobody mentioned the god-table yet. Nothing says "organic" like 100 columns of bit flags, large strings and integers. Then there's the "I miss .ini files" pattern: storing CSVs, pipe delimited strings or other parse required data in large text fields. And for MS SQL server the use of cursors at all. There's a better way to do any given cursor task.

编辑是因为有太多了!

The Altered View - A view that is altered too often and without notice or reason. The change will either be noticed at the most inappropriate time or worse be wrong and never noticed. Maybe your application will break because someone thought of a better name for that column. As a rule views should extend the usefulness of base tables while maintaining a contract with consumers. Fix problems but don't add features or worse change behavior, for that create a new view. To mitigate do not share views with other projects and, use CTEs when platforms allow. If your shop has a DBA you probably can't change views but all your views will be outdated and or useless in that case. The !Paramed - Can a query have more than one purpose? Probably but the next person who reads it won't know until deep meditation. Even if you don't need them right now chances are you will, even if it's "just" to debug. Adding parameters lowers maintenance time and keep things DRY. If you have a where clause you should have parameters. The case for no CASE - SELECT CASE @problem WHEN 'Need to replace column A with this medium to large collection of strings hanging out in my code.' THEN 'Create a table for lookup and add to your from clause.' WHEN 'Scrubbing values in the result set based on some business rules.' THEN 'Fix the data in the database' WHEN 'Formating dates or numbers.' THEN 'Apply formating in the presentation layer.' WHEN 'Createing a cross tab' THEN 'Good, but in reporting you should probably be using cross tab, matrix or pivot templates' ELSE 'You probably found another case for no CASE but now I have to edit my code instead of enriching the data...' END