How Can I Efficiently Parse Comma-Separated Strings for SQL WHERE Clauses?

Efficiently process comma separated strings to optimize SQL queries

In SQL Server, when using stored procedures, it is often necessary to parse comma-separated strings into value lists for use in the WHERE clause. This allows dynamic filtering of data based on multiple criteria.

Problem description:

Your stored procedure receives a comma separated string as parameter, you need to convert it into an IN clause statement, for example:

WHERE Account IN ('SA', 'A')

Best Practices:

To do this, you can use a user-defined function (UDF) to split a comma-separated string into individual values. Here is an efficient UDF named f_split that accomplishes this task:

CREATE function [dbo].[f_split]
(
@param nvarchar(max), 
@delimiter char(1)
)
returns @t table (val nvarchar(max), seq int)
as
begin
set @param += @delimiter

;with a as
(
select cast(1 as bigint) f, charindex(@delimiter, @param) t, 1 seq
union all
select t + 1, charindex(@delimiter, @param, t + 1), seq + 1
from a
where charindex(@delimiter, @param, t + 1) > 0
)
insert @t
select substring(@param, f, t - f), seq from a
option (maxrecursion 0)
return
end

Usage:

To use the f_split function, you can use the following statement:

SELECT *
FROM yourtable 
WHERE account in (SELECT val FROM dbo.f_split(@account, ','))

Performance comparison:

The

f_split function has significant performance advantages over XML-based segmentation methods. For example, on a dataset with 100,000 records:

• XML-based segmentation: 1 minute 21 seconds
• f_splitFunction: 43 seconds

Conclusion:

Using the f_split function provides an efficient and scalable way to parse comma-delimited strings for use in SQL WHERE clauses. It allows flexible queries based on multiple criteria and improves the performance of stored procedures that handle such inputs.

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