How to improve while loop insert performance in SQL Server?

How to improve while loop insert performance in SQL Server?

As has been said in comments, the loop is completely unnecessary. The way to improve the performance of any loop is to remove it completely. Loops are a last resort in SQL. As far as I can tell your insert can be written with a single statement:

Which is faster in SQL, while loop, stored Proc…?

Speaking of while, it also transfers the programming mindset from a set-based one, to a procedure-based one, so while it’s relatively fast and does not consume lots of resources, can still dramatically increase the number of data manipulation statements you issue to the database itself.

Which is faster, a loop or a recursive stored procedure?

SQL works in SETs, it is not a procedural language, use it how it is intended to be used Recursive stored procedure is likely to be slowest, while loop and cursors are not mutually exclusive. Cursor operations are pretty quick (IME), but I’ve only ever used them from external (non-SQL) code.

When to use while loop in SQL Server?

SQL WHILE Loops can be a convenient way to add various amounts of mock data to a table for testing. But the WHILE Loop itself can also be a good way to test different functionality within SQL Server itself.

What’s the problem with the while loop in SQL?

I’ve got a simple query that creates a daily snapshot that uses a WHILE loop statement in SQL for a range of dates. The problem is the query is taking quite long running at 25-40 mins.

How does TSQL speed up performance of insert?

This prevents page splits (where SQL Server must move data around because an existing page is full) Set the fill factor to 0 or 100 (they are equivalent) so that no space in the table is left empty, reducing the number of pages that the data is spread across.

How to increase insert performance in ADO.NET?

Some suggestions for increasing insert performance: Increase ADO.NET BatchSize Choose the target table’s clustered index wisely, so that inserts won’t lead to clustered index node splits (e.g. autoinc column)