How to implement batch processing with cursors in SQL Server

19 Sep 2023

Batch processing is an essential technique for handling large datasets efficiently in SQL Server. One way to achieve batch processing is by using cursors, which enable you to iterate over a result set and perform operations on each row. In this blog post, we will explore how to implement batch processing with cursors in SQL Server.

Prerequisites

To follow along with the examples in this post, you will need:

A working installation of SQL Server
Basic knowledge of SQL syntax and concepts

Step 1: Create a Cursor

The first step is to create a cursor that will allow us to fetch a batch of rows from a result set. We can achieve this by using the DECLARE CURSOR statement, specifying the FORWARD_ONLY, STATIC, and READ_ONLY options for improved performance.

DECLARE myCursor CURSOR FORWARD_ONLY STATIC READ_ONLY
FOR
SELECT * FROM Your_Table
ORDER BY Column_Name

Step 2: Configure Cursor Options

Next, we need to configure the cursor options to define the batch size and enable optimistic concurrency control. We can achieve this by using the SET statement.

SET ROWCOUNT 100000 -- Set the batch size

SET CURSOR_CLOSE_ON_COMMIT OFF -- Preserve the cursor after a commit

SET TRANSACTION ISOLATION LEVEL READ COMMITTED -- Enable optimistic concurrency control

Step 3: Fetch Rows in a Loop

We can now fetch the rows from the result set using a loop. In each iteration, we can perform operations on the current row, such as updating or deleting data.

DECLARE @variable1 DATATYPE
DECLARE @variable2 DATATYPE

OPEN myCursor

FETCH NEXT FROM myCursor INTO @variable1, @variable2

WHILE @@FETCH_STATUS = 0
BEGIN
    -- Perform operations on the current row
    
    FETCH NEXT FROM myCursor INTO @variable1, @variable2
END

CLOSE myCursor
DEALLOCATE myCursor

Step 4: Commit or Rollback Changes

After processing each batch, we need to commit or rollback the changes made to the database to ensure data integrity.

COMMIT -- or ROLLBACK

Step 5: Handle Cursor Errors

It’s important to handle any errors that may occur during the batch processing. One way to achieve this is by using a TRY...CATCH block.

BEGIN TRY
    -- Batch processing code here
END TRY
BEGIN CATCH
    -- Handle errors here
END CATCH

Conclusion

Implementing batch processing with cursors in SQL Server can significantly improve the performance and efficiency of handling large datasets. By using cursors, you can process data in batch sizes, optimize concurrency control, and handle errors effectively. Remember to carefully consider the performance implications and use cursors judiciously.

#SQLServer #BatchProcessing