Applications often present a way to allow a
user to select a number of values. These values are then assembled
in an IN() clause that contains a list of values to be matched, as
in the following example:

SELECT * FROM TableA WHERE SomeColumn IN( 1, 2,

But as the list of items to match grows longer,
it takes SQL more time to perform it. Against a large number of
rows, this can be especially problematic, since there’s no way to
take advantage of the index. The result is a table scan in which
each row is compared to each value in the list.

The values in the IN() clause typically come
from a front-end application whose user makes a run-time selection.
(If that wasn’t the case, we could rewrite the query to optimize

A better approach in such situations is to
build a table from the list of values and join the table to the
target table. This enables SQL to take advantage of the index,
which significantly increases performance.

The question remains: How do we build the
temporary table to hold the values? There are several ways, but the
one I like uses a user-defined function (UDF) that parses a
delimited string and returns a table in which each item in the
string becomes a row in the table. The UDF looks like this:

CREATE FUNCTION fn_StringToTable (@String
RETURNS @Values TABLE (ID int primary key)
DECLARE @pos int
DECLARE @value int
WHILE @string > ”
SET @pos = CHARINDEX(‘,’, @string)
IF @pos > 0
SET @value = SUBSTRING( @string, 1, @pos – 1)
select @string = LTRIM(SUBSTRING( @string, @pos + 1,
INSERT @Values SELECT @value
IF LEN(@string) > 0
SET @value = @string
INSERT @Values SELECT @value
SET @string = ”
SET @string = ”

You would execute this function, passing it a
comma-delimited string like this:

SELECT * FROM fn_StringToTable( ‘100, 200, 333,
444, 555’)

Now you can join this table to any other table,
view, or table UDF, and get maximum performance with minimal disk

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