以下为示例代码：
set statistics profile offDECLARE @t TABLE(id1 INT,c VARCHAR(10))INSERT INTO @t VALUES(1,'ab')INSERT INTO @t VALUES(2,'abc')INSERT INTO @t VALUES(3,'abcd')INSERT INTO @t VALUES(4,'abcde')DECLARE @tt TABLE(id1 INT,c VARCHAR(10))INSERT INTO @tt VALUES(9,'s1')INSERT INTO @tt VALUES(2,'s2')INSERT INTO @tt VALUES(3,'s3')INSERT INTO @tt VALUES(5,'s4')DECLARE @ttt TABLE(id1 INT,c VARCHAR(10))INSERT INTO @ttt VALUES(2,'r2')INSERT INTO @ttt VALUES(3,'r3')INSERT INTO @ttt VALUES(6,'r2')INSERT INTO @ttt VALUES(8,'r1')set statistics profile onSELECT *FROM @t t left JOIN @tt tt ON t.id1 = tt.id1inner JOIN @ttt ttt ON t.id1 = ttt.id1
产生了如下的执行计划：
SELECT * FROM @t t left JOIN @tt tt ON t.id1 = tt.id1 inner JOIN @ttt ttt ON t.id1 = ttt.id1 |--Nested Loops(Left Outer Join, WHERE:(@t.[id1] as [t].[id1]=@tt.[id1] as [tt].[id1])) |--Hash Match(Inner Join, HASH:([ttt].[id1])=([t].[id1]), RESIDUAL:(@t.[id1] as [t].[id1]=@ttt.[id1] as [ttt].[id1])) | |--Table Scan(OBJECT:(@ttt AS [ttt])) | |--Table Scan(OBJECT:(@t AS [t])) |--Table Scan(OBJECT:(@tt AS [tt]))
这里会先把@t与@ttt进行inner join，这里SQL Server自动优化了连接顺序，先进行inner join可能会产生更小的结果集，然后把结果与@tt 进行 left outer join。
把上面最后的sql语句改为：
SELECT *FROM @t t left JOIN @tt tt ON t.id1 = tt.id1inner JOIN @ttt ttt ON tt.id1 = ttt.id1执行计划为：
SELECT * FROM @t t left JOIN @tt tt ON t.id1 = tt.id1 inner JOIN @ttt ttt ON tt.id1 = ttt.id1 |--Hash Match(Inner Join, HASH:([ttt].[id1])=([tt].[id1]), RESIDUAL:(@tt.[id1] as [tt].[id1]=@ttt.[id1] as [ttt].[id1])) |--Table Scan(OBJECT:(@ttt AS [ttt])) |--Hash Match(Inner Join, HASH:([t].[id1])=([tt].[id1]), RESIDUAL:(@t.[id1] as [t].[id1]=@tt.[id1] as [tt].[id1])) |--Table Scan(OBJECT:(@t AS [t])) |--Table Scan(OBJECT:(@tt AS [tt]))发现内部，@t与@tt进行inner join，然后@ttt与上述结果进行inner join，操作都成了inner join。
为什么呢？我原来想，应该先是@t与@tt进行left join呀，怎么是inner join，仔细想想整个操作是这样的，@t与@tt进行left join，产生了如下结果集：
@t.id1 @tt.id1
1 null
2 2
3 3
4 null
然后再把这个结果和@ttt进行 inner join，连接条件是 @tt.id1 = @ttt.id1，那么这样最后结果一定会把@tt.id1为null的记录给过滤掉了，所以结果只会出来两条。这样的结果，与一开始@t与@tt就进行inner join是一样的，换句话说结果取决于后面的inner join。
结论：
left outer join和inner join是两种不同的逻辑操作，单纯的操作可能会产生不同的结果集，但是当这两个操作叠加在一起的时候， SQL Server考虑到结果集是一样，所以优化了表的连接顺序和逻辑操作，目的当然是为了提高效率。