Cursor In SQL

What are cursors in SQL, and how do they work?

Cursors in SQL are a way to process data from a result set one row at a time. They provide a powerful mechanism for handling complex operations on retrieved data, but they are often less efficient than set-based operations.

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Description

Example H2

Example H3

Cursors are a fundamental concept in SQL, particularly when dealing with data manipulation that requires iterative processing. Imagine you need to update multiple rows in a table based on specific conditions. A cursor allows you to fetch each row individually, perform actions on it, and then move to the next. This is different from set-based operations, which process all rows at once. Cursors are particularly useful when you need to perform actions that aren't easily expressed using standard SQL statements. For instance, you might need to update a row based on the value of another row, or perform a complex calculation on each row. However, cursors can be less efficient than set-based operations, especially for large result sets, as they involve multiple round trips to the database. Therefore, it's crucial to consider the performance implications before using cursors.

Why Cursor In SQL is important

Cursors provide a way to handle complex data manipulation tasks that are not easily achievable using standard SQL statements. They are essential for situations requiring row-by-row processing, but their use should be carefully considered due to potential performance implications.

Cursor In SQL Example Usage


-- Create a sample table
CREATE TABLE Employees (
    EmployeeID INT PRIMARY KEY,
    FirstName VARCHAR(50),
    Salary DECIMAL(10, 2)
);

-- Insert some sample data
INSERT INTO Employees (EmployeeID, FirstName, Salary)
VALUES
(1, 'John', 50000),
(2, 'Jane', 60000),
(3, 'Peter', 70000);

-- Declare a cursor to iterate through the Employees table
DECLARE EmployeeCursor CURSOR FOR
SELECT EmployeeID, Salary
FROM Employees
WHERE Salary < 60000;

-- Declare a variable to hold the employee ID
DECLARE @EmployeeID INT;

-- Declare a variable to hold the salary
DECLARE @Salary DECIMAL(10, 2);

-- Open the cursor
OPEN EmployeeCursor;

-- Fetch the first row
FETCH NEXT FROM EmployeeCursor INTO @EmployeeID, @Salary;

-- Process the row
WHILE @@FETCH_STATUS = 0
BEGIN
    UPDATE Employees SET Salary = Salary * 1.1 WHERE EmployeeID = @EmployeeID;
    FETCH NEXT FROM EmployeeCursor INTO @EmployeeID, @Salary;
END;

-- Close and deallocate the cursor
CLOSE EmployeeCursor;
DEALLOCATE EmployeeCursor;

-- Verify the changes
SELECT * FROM Employees;

Cursor In SQL Syntax

Common Mistakes

Forgetting to close and deallocate the cursor, leading to resource leaks.
Using cursors when set-based operations are more efficient.
Incorrectly handling the `FETCH` statement, leading to errors or incomplete processing.
Not properly declaring and initializing variables used within the cursor.

Frequently Asked Questions (FAQs)

When is a SQL cursor preferable to a set-based UPDATE?

A cursor makes sense when each row needs individualized logic that can’t be expressed in a single declarative statement—for example, updating a row based on a value found in a different row, performing step-by-step calculations, or calling stored procedures per row. In these cases the row-by-row control a cursor gives outweighs the extra complexity.

What performance penalties should I expect from using cursors on large datasets?

Because a cursor processes one row at a time, it generates many round trips between your client and the database engine. This consumes more I/O, locks rows longer, and prevents the optimizer from applying set-level efficiencies. On very large result sets the overhead can be orders of magnitude slower than a single set-based UPDATE or MERGE.

How can Galaxy help me avoid or optimize cursor-based logic?

Galaxy’s context-aware AI copilot can analyze your cursor implementation, suggest equivalent set-based queries, or automatically refactor loops into window functions, CTEs, or MERGE statements. If a cursor is truly required, Galaxy surfaces performance tips—such as using FAST_FORWARD or LOCAL STATIC options—and lets you benchmark alternative queries without leaving the editor.