You can get something similar to Oracle's CARDINALITY
hint by strategically using TOP
and a user defined function called MANY()
developed by Adam Machanic. Let's work through a few examples. I'm using the freely available AdventureWorks database. Suppose that I really need to control the number of rows returned by the th
derived table in the following query:
SELECT
p.Name
, th.ProductId
, th.Quantity
, th.ActualCost
FROM Production.Product p
INNER JOIN (
SELECT ProductId, Quantity, ActualCost
FROM Production.TransactionHistory
) th ON p.ProductID = th.ProductID;
As is, I get an estimate of 113443 rows:

If I need to lower the estimate from th
I can use TOP
along with the OPTIMIZE FOR
query hint to set a row goal. Here's one way to do it:
DECLARE @row_goal BIGINT = 9223372036854775807;
SELECT
p.Name
, th.ProductId
, th.Quantity
, th.ActualCost
FROM Production.Product p
INNER JOIN (
SELECT TOP (@row_goal) ProductId, Quantity, ActualCost
FROM Production.TransactionHistory
) th ON p.ProductID = th.ProductID
OPTION (OPTIMIZE FOR (@row_goal = 1));
We can see that the estimate is just 1 row:

I set @row_goal
to the largest possible BIGINT
value to avoid changing the results. The OPTIMIZE FOR
query hint instructs the optimizer to optimizer the query as if @row_goal
is equal to 1. I will get the same results but the query will be optimized differently.
Increasing a cardinality estimate is trickier. We can't just increase the value for TOP
because the optimizer will realize that it won't return enough rows. However, we can use the MANY()
function to add rows to the estimate. Note that the MANY()
function will always return 0 rows but the row estimate from it changes with the input parameter. Suppose that you need to increase the row estimate from the derived table by 10X. One way to accomplish that:
SELECT
p.Name
, th.ProductId
, th.Quantity
, th.ActualCost
FROM Production.Product p
INNER JOIN (
SELECT TOP (9223372036854775807) ProductId, Quantity, ActualCost
FROM Production.TransactionHistory
LEFT OUTER JOIN dbo.Many(10) AS m ON 1=1
) th ON p.ProductID = th.ProductID;
We can see that the estimate is 10X the base table:

The superfluous TOP
was added to prevent the optimizer from moving the tables around. Without it the MANY()
function can be applied to the wrong place in the plan.
It is possible to combine the two techniques if you want a precise overestimate instead of just multiplying the number of rows by a factor. For example, let's suppose that you really need the estimate of the derived table to be exactly 1000000 rows. One way to accomplish that:
DECLARE @row_goal BIGINT = 9223372036854775807;
SELECT
p.Name
, th.ProductId
, th.Quantity
, th.ActualCost
FROM Production.Product p
INNER JOIN (
SELECT TOP (@row_goal) ProductId, Quantity, ActualCost
FROM Production.TransactionHistory
LEFT OUTER JOIN dbo.Many(10) AS m ON
1=1
) th ON p.ProductID = th.ProductID
OPTION (OPTIMIZE FOR (@row_goal = 1000000));
We can see that the estimate is 1000000 rows:

I need to caution you that these are advanced techniques which often aren't needed for query optimization. If you'd like to learn more I recommend watching Clash of the Row Goals presented by Adam Machanic.
dbo.Many function
-- By Adam Machanic, reproduced with permission
IF EXISTS (SELECT * FROM sys.objects WHERE name = 'Many' AND OBJECT_SCHEMA_NAME(object_id) = 'dbo')
DROP FUNCTION dbo.Many
GO
CREATE FUNCTION dbo.Many(@n INT)
RETURNS TABLE AS
RETURN
(
WITH
a(x) AS
(
SELECT
*
FROM
(
VALUES
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(1), (1), (1), (1), (1), (1), (1), (1), (1), (1), (1), (1), (1), (1), (1), (1),
(1), (1), (1), (1), (1), (1), (1), (1), (1), (1), (1), (1), (1), (1), (1), (1),
(1), (1), (1), (1), (1), (1), (1), (1), (1), (1), (1), (1), (1), (1), (1), (1),
(1), (1), (1), (1), (1), (1), (1), (1), (1), (1), (1), (1), (1), (1), (1), (1)
) AS x0(x)
)
SELECT TOP(@n)
1 AS x
FROM
a AS a1,
a AS a2
WHERE
a1.x % 2 = 0
)
GO