How to Efficiently Parse Comma-Separated Strings for SQL WHERE IN Clauses?

Optimizing SQL WHERE IN Clauses with Comma-Separated Strings

Stored procedures often receive comma-separated string parameters. Efficiently converting these strings for use within WHERE IN clauses is crucial for performance. This article details best practices for this conversion.

Leveraging User-Defined Functions (UDFs)

A robust solution involves creating a UDF to parse the comma-separated string. A high-performing UDF for SQL Server 2005 and later versions is f_split, shown below:

<code class="language-sql">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</code>

Query Integration

This UDF simplifies filtering with the IN clause:

<code class="language-sql">SELECT *
FROM yourtable 
WHERE account IN (SELECT val FROM dbo.f_split(@account, ','))</code>

Performance Comparison: UDF vs. XML

While STRING_SPLIT (XML-based splitting) is an alternative, f_split consistently demonstrates superior performance, especially with large datasets. Benchmark tests confirm this advantage.

Summary

The f_split UDF offers a reliable and efficient method for processing comma-separated strings in WHERE IN clauses. Its performance benefits make it the recommended approach.

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