SELECT FirstName + ' ' + LastName as "Full Name", case UserRole when 2 then "Admin" when 1 then "Moderator" else "User" end as "User's Role", case SignedIn when 0 then "Logged in" else "Logged out" end as "User signed in?", Convert(varchar(100), LastSignOn, 101) as "Last Sign On", DateDiff('d', LastSignOn, getDate()) as "Days since last sign on", AddrLine1 + ' ' + AddrLine2 + ' ' + AddrLine3 + ' ' + City + ', ' + State + ' ' + Zip as "Address", 'XXX-XX-' + Substring(Convert(varchar(9), SSN), 6, 4) as "Social Security #" FROM Users

或者，把所有内容都塞进一行。

以下是我的前3名。

1号。指定字段列表失败。(编辑:为了防止混淆:这是一个生产代码规则。它不适用于一次性分析脚本——除非我是作者。)

SELECT *
Insert Into blah SELECT *

应该是

SELECT fieldlist
Insert Into blah (fieldlist) SELECT fieldlist

2号。使用游标和while循环，当while循环和循环变量就可以了。

DECLARE @LoopVar int

SET @LoopVar = (SELECT MIN(TheKey) FROM TheTable)
WHILE @LoopVar is not null
BEGIN
  -- Do Stuff with current value of @LoopVar
  ...
  --Ok, done, now get the next value
  SET @LoopVar = (SELECT MIN(TheKey) FROM TheTable
    WHERE @LoopVar < TheKey)
END

3号。DateLogic通过字符串类型。

--Trim the time
Convert(Convert(theDate, varchar(10), 121), datetime)

应该是

--Trim the time
DateAdd(dd, DateDiff(dd, 0, theDate), 0)

我最近看到了一个高峰“一个问题总比两个好，对吧?”

SELECT *
FROM blah
WHERE (blah.Name = @name OR @name is null)
  AND (blah.Purpose = @Purpose OR @Purpose is null)

这个查询需要两个或三个不同的执行计划，具体取决于参数的值。对于这个SQL文本，只生成一个执行计划并保存在缓存中。无论参数的值是多少，都将使用该计划。这会导致间歇性的性能不佳。最好编写两个查询(每个预期的执行计划一个查询)。

同一查询中的相同子查询。

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 If your shop has a DBA you probably can't change views but all your views will be outdated and or useless in that case.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

我最担心的是450列的访问表，这些表是由总经理最好的朋友狗美容师的8岁儿子整理的，还有那个不可靠的查找表，它之所以存在，是因为有人不知道如何正确地规范化数据结构。

通常，这个查找表是这样的:

ID INT,
Name NVARCHAR(132),
IntValue1 INT,
IntValue2 INT,
CharValue1 NVARCHAR(255),
CharValue2 NVARCHAR(255),
Date1 DATETIME,
Date2 DATETIME

我已经记不清有多少客户的系统依赖于这种可恶的东西了。

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.)