Which of these queries is the faster?
NOT EXISTS:
SELECT ProductID, ProductName FROM Northwind..Products p WHERE NOT EXISTS ( SELECT 1 FROM Northwind..[Order Details] od WHERE p.ProductId = od.ProductId)
Or NOT IN:
SELECT ProductID, ProductName FROM Northwind..Products p WHERE p.ProductID NOT IN ( SELECT ProductID FROM Northwind..[Order Details])
The query execution plan says they both do the same thing. If that is the case, which is the recommended form?
This is based on the NorthWind database.
[Edit]
Just found this helpful article: http://weblogs.sqlteam.com/mladenp/archive/2007/05/18/60210.aspx
I think I'll stick with NOT EXISTS.
The NULL is considered and returned by the NOT IN command as a value. The SQL NOT EXISTS command is used to check for the existence of specific values in the provided subquery. The subquery will not return any data; it returns TRUE or FALSE values depend on the subquery values existence check.
The main difference between them is that IN selects a list of matching values, whereas EXISTS returns the Boolean value TRUE or FALSE.
What is the difference between EXISTS and NOT EXISTS in SQL? Unlike EXISTS, NOT EXISTS returns TRUE if the result of the subquery does not contain any rows. In case a single record in a table matches the subquery, the NOT EXISTS returns FALSE, and the execution of the subquery is stopped.
There is no difference.
I always default to NOT EXISTS
.
The execution plans may be the same at the moment but if either column is altered in the future to allow NULL
s the NOT IN
version will need to do more work (even if no NULL
s are actually present in the data) and the semantics of NOT IN
if NULL
s are present are unlikely to be the ones you want anyway.
When neither Products.ProductID
or [Order Details].ProductID
allow NULL
s the NOT IN
will be treated identically to the following query.
SELECT ProductID, ProductName FROM Products p WHERE NOT EXISTS (SELECT * FROM [Order Details] od WHERE p.ProductId = od.ProductId)
The exact plan may vary but for my example data I get the following.
A reasonably common misconception seems to be that correlated sub queries are always "bad" compared to joins. They certainly can be when they force a nested loops plan (sub query evaluated row by row) but this plan includes an anti semi join logical operator. Anti semi joins are not restricted to nested loops but can use hash or merge (as in this example) joins too.
/*Not valid syntax but better reflects the plan*/ SELECT p.ProductID, p.ProductName FROM Products p LEFT ANTI SEMI JOIN [Order Details] od ON p.ProductId = od.ProductId
If [Order Details].ProductID
is NULL
-able the query then becomes
SELECT ProductID, ProductName FROM Products p WHERE NOT EXISTS (SELECT * FROM [Order Details] od WHERE p.ProductId = od.ProductId) AND NOT EXISTS (SELECT * FROM [Order Details] WHERE ProductId IS NULL)
The reason for this is that the correct semantics if [Order Details]
contains any NULL
ProductId
s is to return no results. See the extra anti semi join and row count spool to verify this that is added to the plan.
If Products.ProductID
is also changed to become NULL
-able the query then becomes
SELECT ProductID, ProductName FROM Products p WHERE NOT EXISTS (SELECT * FROM [Order Details] od WHERE p.ProductId = od.ProductId) AND NOT EXISTS (SELECT * FROM [Order Details] WHERE ProductId IS NULL) AND NOT EXISTS (SELECT * FROM (SELECT TOP 1 * FROM [Order Details]) S WHERE p.ProductID IS NULL)
The reason for that one is because a NULL
Products.ProductId
should not be returned in the results except if the NOT IN
sub query were to return no results at all (i.e. the [Order Details]
table is empty). In which case it should. In the plan for my sample data this is implemented by adding another anti semi join as below.
The effect of this is shown in the blog post already linked by Buckley. In the example there the number of logical reads increase from around 400 to 500,000.
Additionally the fact that a single NULL
can reduce the row count to zero makes cardinality estimation very difficult. If SQL Server assumes that this will happen but in fact there were no NULL
rows in the data the rest of the execution plan may be catastrophically worse, if this is just part of a larger query, with inappropriate nested loops causing repeated execution of an expensive sub tree for example.
This is not the only possible execution plan for a NOT IN
on a NULL
-able column however. This article shows another one for a query against the AdventureWorks2008
database.
For the NOT IN
on a NOT NULL
column or the NOT EXISTS
against either a nullable or non nullable column it gives the following plan.
When the column changes to NULL
-able the NOT IN
plan now looks like
It adds an extra inner join operator to the plan. This apparatus is explained here. It is all there to convert the previous single correlated index seek on Sales.SalesOrderDetail.ProductID = <correlated_product_id>
to two seeks per outer row. The additional one is on WHERE Sales.SalesOrderDetail.ProductID IS NULL
.
As this is under an anti semi join if that one returns any rows the second seek will not occur. However if Sales.SalesOrderDetail
does not contain any NULL
ProductID
s it will double the number of seek operations required.
Also be aware that NOT IN is not equivalent to NOT EXISTS when it comes to null.
This post explains it very well
http://sqlinthewild.co.za/index.php/2010/02/18/not-exists-vs-not-in/
When the subquery returns even one null, NOT IN will not match any rows.
The reason for this can be found by looking at the details of what the NOT IN operation actually means.
Let’s say, for illustration purposes that there are 4 rows in the table called t, there’s a column called ID with values 1..4
WHERE SomeValue NOT IN (SELECT AVal FROM t)
is equivalent to
WHERE SomeValue != (SELECT AVal FROM t WHERE ID=1) AND SomeValue != (SELECT AVal FROM t WHERE ID=2) AND SomeValue != (SELECT AVal FROM t WHERE ID=3) AND SomeValue != (SELECT AVal FROM t WHERE ID=4)
Let’s further say that AVal is NULL where ID = 4. Hence that != comparison returns UNKNOWN. The logical truth table for AND states that UNKNOWN and TRUE is UNKNOWN, UNKNOWN and FALSE is FALSE. There is no value that can be AND’d with UNKNOWN to produce the result TRUE
Hence, if any row of that subquery returns NULL, the entire NOT IN operator will evaluate to either FALSE or NULL and no records will be returned
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