区别一:
<PRE lang=sql>CREATE table #T (s varchar(128))
DECLARE @T table (s varchar(128))
INSERT into #T select 'old value #'
INSERT into @T select 'old value @'
BEGIN transaction
UPDATE #T set s='new value #'
UPDATE @T set s='new value @'
ROLLBACK transaction
SELECT * from #T
SELECT * from @T
s
---------------
old value #
s
---------------
new value @</PRE>
这行代码一目了然,临时表能起到事务回滚的作用,但是table变量不可以.作者解释是table变量不在事务作用范围之内.所以当table变量即使遇到回滚命令,但是也不会真的执行回滚.DECLARE @T table (s varchar(128))
INSERT into #T select 'old value #'
INSERT into @T select 'old value @'
BEGIN transaction
UPDATE #T set s='new value #'
UPDATE @T set s='new value @'
ROLLBACK transaction
SELECT * from #T
SELECT * from @T
s
---------------
old value #
s
---------------
new value @</PRE>
区别二:
任何含有临时表的存储过程是不能被预编译的.这在一个很长的存储过程中,优势会更加凸显.
区别三:
table变量作为变量只能在同范围内存在,不可能跨范围.还有就是table变量在内置的存储过程中或者exec(string)语句中是不可见的还有就是不能被用于INSERT/EXEC statements.
下面的例子我来演示如何对比临时表和table变量在存储过程中预编译的区别.
创建一个测试表:
CREATE table NUM (n int primary key, s varchar(128))
GO
SET nocount on
DECLARE @n int
SET @n=1000000
WHILE @n>0 begin
INSERT into NUM
SELECT @n,'Value: '+convert(varchar,@n)
SET @n=@n-1
END
GO
GO
SET nocount on
DECLARE @n int
SET @n=1000000
WHILE @n>0 begin
INSERT into NUM
SELECT @n,'Value: '+convert(varchar,@n)
SET @n=@n-1
END
GO
然后创建存储过程:T1
CREATE procedure T1
@total int
AS
CREATE table #T (n int, s varchar(128))
INSERT into #T select n,s from NUM
WHERE n%100>0 and n<=@total
DECLARE @res varchar(128)
SELECT @res=max(s) from NUM
WHERE n<=@total and
NOT exists(select * from #T
WHERE #T.n=NUM.n)
GO
这个存储过程的参数@Total给定的越大,那么执行的时间越长.@total int
AS
CREATE table #T (n int, s varchar(128))
INSERT into #T select n,s from NUM
WHERE n%100>0 and n<=@total
DECLARE @res varchar(128)
SELECT @res=max(s) from NUM
WHERE n<=@total and
NOT exists(select * from #T
WHERE #T.n=NUM.n)
GO
为精确测量存储过程执行时间,我使用了以下代码:
DECLARE @t1 datetime, @n int
SET @t1=getdate()
SET @n=100 – (**)
WHILE @n>0 begin
EXEC T1 1000 – (*)
SET @n=@n-1 end
SELECT datediff(ms,@t1,getdate())
GO
(*) 是存储过程参数.SET @t1=getdate()
SET @n=100 – (**)
WHILE @n>0 begin
EXEC T1 1000 – (*)
SET @n=@n-1 end
SELECT datediff(ms,@t1,getdate())
GO
现在我们给这个存储过程来第一次提速:个它加个主键
CREATE procedure T2
@total int
AS
CREATE table #T (n int primary key, s varchar(128))
INSERT into #T select n,s from NUM
WHERE n%100>0 and n<=@total
DECLARE @res varchar(128)
SELECT @res=max(s) from NUM
WHERE n<=@total and
NOT exists(select * from #T
WHERE #T.n=NUM.n)
GO
在下面的对比中你可以发现已经大大的提速了.@total int
AS
CREATE table #T (n int primary key, s varchar(128))
INSERT into #T select n,s from NUM
WHERE n%100>0 and n<=@total
DECLARE @res varchar(128)
SELECT @res=max(s) from NUM
WHERE n<=@total and
NOT exists(select * from #T
WHERE #T.n=NUM.n)
GO
然后再来一次提速:给它加个聚集索引
CREATE procedure T3
@total int
AS
CREATE table #T (n int, s varchar(128))
INSERT into #T select n,s from NUM
WHERE n%100>0 and n<=@total
CREATE clustered index Tind on #T (n)
DECLARE @res varchar(128)
SELECT @res=max(s) from NUM
WHERE n<=@total and
NOT exists(select * from #T
WHERE #T.n=NUM.n)
GO
@total int
AS
CREATE table #T (n int, s varchar(128))
INSERT into #T select n,s from NUM
WHERE n%100>0 and n<=@total
CREATE clustered index Tind on #T (n)
DECLARE @res varchar(128)
SELECT @res=max(s) from NUM
WHERE n<=@total and
NOT exists(select * from #T
WHERE #T.n=NUM.n)
GO
很惊讶速度已经提高了很多!
那好了,咱们再来测试一下table变量的速度吧
CREARE procedure V1
@total int
AS
DECLARE @V table (n int, s varchar(128))
INSERT into @V select n,s from NUM
WHERE n%100>0 and n<=@total
DECLARE @res varchar(128)
SELECT @res=max(s) from NUM
WHERE n<=@total and
NOT exists(select * from @V V
WHERE V.n=NUM.n)
GO
@total int
AS
DECLARE @V table (n int, s varchar(128))
INSERT into @V select n,s from NUM
WHERE n%100>0 and n<=@total
DECLARE @res varchar(128)
SELECT @res=max(s) from NUM
WHERE n<=@total and
NOT exists(select * from @V V
WHERE V.n=NUM.n)
GO
然后再来创建一个有主键的:
CREATE procedure V2
@total int
AS
DECLARE @V table (n int primary key, s varchar(128))
INSERT into @V select n,s from NUM
WHERE n%100>0 and n<=@total
DECLARE @res varchar(128)
SELECT @res=max(s) from NUM
WHERE n<=@total and
NOT exists(select * from @V V
WHEREre V.n=NUM.n)
GO<
@total int
AS
DECLARE @V table (n int primary key, s varchar(128))
INSERT into @V select n,s from NUM
WHERE n%100>0 and n<=@total
DECLARE @res varchar(128)
SELECT @res=max(s) from NUM
WHERE n<=@total and
NOT exists(select * from @V V
WHEREre V.n=NUM.n)
GO<
然后咱们来看看我测试的结果吧!
Records |
T1 | T2 | T3 | V1 | V2 |
10 | 0.7 | 1 | 13.5 | 0.6 | 0.8 |
100 | 1.2 | 1.7 | 14.2 | 1.2 | 1.3 |
1000 | 7.1 | 5.5 | 27 | 7 | 5.3 |
10000 | 72 | 57 | 82 | 71 | 48 |
100000 | 883 | 480 | 580 | 840 | 510 |
1000000 | 45056 | 6090 | 15220 | 20240 | 12010 |
But the real shock is when you try the same on SQL Server 2005:
N |
T1 | T2 | T3 | V1 | V2 |
10 | 0.5 | 0.5 | 5.3 | 0.2 | 0.2 |
100 | 2 | 1.2 | 6.4 | 61.8 | 2.5 |
1000 | 9.3 | 8.5 | 13.5 | 168 | 140 |
10000 | 67.4 | 79.2 | 71.3 | 17133 | 13910 |
100000 | 700 | 794 | 659 |
Too long! |
Too long! |
1000000 | 10556 | 8673 | 6440 |
Too long! |
Too long! |
发现对比在某些情况下sql2000的速度要比2005的要快上很多!
结论:
没有通用的规则指导你什么时候用临时表什么时候用table变量.
将复杂逻辑的存储过程移植到sql2005的时候,要格外小心!他可能比2000的效率要慢上好几十倍的!
在你的实际测试中,请测试两个极端:销量数据和超大量数据.
此文章翻译自codeproject:http://www.codeproject.com/cs/database/SQP_performance.asp