例如,我想获取应用了特定标签的所有项目的列表.我可以执行以下任一操作:
As an example, I want to get the list of all items with certain tags applied to them. I could do either of the following:
SELECT Item.ID, Item.Name
FROM Item
WHERE Item.ID IN (
SELECT ItemTag.ItemID
FROM ItemTag
WHERE ItemTag.TagID = 57 OR ItemTag.TagID = 55)
或
SELECT Item.ID, Item.Name
FROM Item
LEFT JOIN ItemTag ON ItemTag.ItemID = Item.ID
WHERE ItemTag.TagID = 57 OR ItemTag.TagID = 55
GROUP BY Item.ID, Item.Name
或者完全不同的东西.
总的来说(假设有一个通用规则),什么是更有效的方法?
In general (assuming there is a general rule), what's a more efficient approach?
SELECT Item.ID, Item.Name
FROM Item
WHERE Item.ID IN (
SELECT ItemTag.ItemID
FROM ItemTag
WHERE ItemTag.TagID = 57 OR ItemTag.TagID = 55)
或
SELECT Item.ID, Item.Name
FROM Item
LEFT JOIN ItemTag ON ItemTag.ItemID = Item.ID
WHERE ItemTag.TagID = 57 OR ItemTag.TagID = 55
GROUP BY Item.ID
您的第二个查询将无法编译,因为它引用了 Item.Name
而没有对其进行分组或聚合.
Your second query won't compile, since it references Item.Name
without either grouping or aggregating on it.
如果我们从查询中删除 GROUP BY
:
If we remove GROUP BY
from the query:
SELECT Item.ID, Item.Name
FROM Item
JOIN ItemTag
ON ItemTag.ItemID = Item.ID
WHERE ItemTag.TagID = 57 OR ItemTag.TagID = 55
这些仍然是不同的查询,除非 ItemTag.ItemId
是一个 UNIQUE
键并被标记为这样.
these are still different queries, unless ItemTag.ItemId
is a UNIQUE
key and marked as such.
SQL Server
能够检测 UNIQUE
列上的 IN
条件,并且只会转换 IN
> 条件转换为 JOIN
.
SQL Server
is able to detect an IN
condition on a UNIQUE
column, and will just transform the IN
condition into a JOIN
.
如果ItemTag.ItemID
不是UNIQUE
,第一个查询会使用一种SEMI JOIN
算法,这种算法在SQL Server
.
If ItemTag.ItemID
is not UNIQUE
, the first query will use a kind of a SEMI JOIN
algorithm, which are quite efficient in SQL Server
.
您可以将第二个查询转换为 JOIN
:
You can trasform the second query into a JOIN
:
SELECT Item.ID, Item.Name
FROM Item
JOIN (
SELECT DISTINCT ItemID
FROMT ItemTag
WHERE ItemTag.TagID = 57 OR ItemTag.TagID = 55
) tags
ON tags.ItemID = Item.ID
但是这个比 IN
或 EXISTS
效率低一点.
but this one is a trifle less efficient than IN
or EXISTS
.
有关更详细的性能比较,请参阅我博客中的这篇文章:
See this article in my blog for a more detailed performance comparison:
IN
vs. JOIN
vs. EXISTS
IN
vs. JOIN
vs. EXISTS
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