SQL Cursor

What are SQL cursors, and how do they work?

SQL cursors are pointers to rows in a result set. They allow you to process data from a query one row at a time, providing more control over data retrieval than a single SELECT statement. They are particularly useful for situations requiring complex data manipulation or updates based on conditions within the result set.

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Description

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Example H3

Cursors are a powerful tool in SQL, enabling you to traverse a result set row by row. Imagine you have a table of customer orders, and you need to update the status of orders placed before a certain date. A single UPDATE statement wouldn't allow you to check each order individually. A cursor allows you to do exactly that. It acts like a pointer, moving through the result set one row at a time, allowing you to perform actions on each row based on specific conditions. This granular control is crucial for tasks like processing large datasets, implementing complex business logic, or performing updates based on the results of previous operations. Cursors are often used in conjunction with loops to iterate through the rows and execute specific actions for each row. However, they can be resource-intensive, especially for large result sets, so consider alternative approaches like stored procedures or set-based operations when possible.

Why SQL Cursor is important

Cursors provide fine-grained control over data manipulation, enabling complex logic and updates based on the results of previous operations. They are essential for situations requiring iterative processing of data rows, but should be used judiciously, as they can be less efficient than set-based operations for large datasets.

SQL Cursor Example Usage


-- Sample table
CREATE TABLE Customers (
    CustomerID INT,
    CustomerName VARCHAR(50),
    OrderDate DATE
);

INSERT INTO Customers (CustomerID, CustomerName, OrderDate) VALUES
(1, 'John Doe', '2023-10-26'),
(2, 'Jane Smith', '2023-11-15');

-- Converting an integer to a string
SELECT
    CustomerID,
    CAST(CustomerID AS VARCHAR(10)) AS CustomerIDString
FROM
    Customers;

-- Converting a date to a string (using different formats)
SELECT
    CustomerID,
    CustomerName,
    CAST(OrderDate AS VARCHAR) AS OrderDateString,
    CONVERT(VARCHAR, OrderDate, 101) AS OrderDateStringFormatted
FROM
    Customers;

-- Concatenating string representations of different types
SELECT
    CustomerID,
    CustomerName,
    CAST(CustomerID AS VARCHAR(10)) || ' - ' || CustomerName AS CombinedData
FROM
    Customers;

DROP TABLE Customers;

SQL Cursor Syntax

Common Mistakes

Forgetting to declare and open the cursor.
Forgetting to close and deallocate the cursor, leading to resource leaks.
Using cursors for tasks that can be handled more efficiently with set-based operations.
Incorrectly using `FETCH` statements within the loop.

Frequently Asked Questions (FAQs)

When should I reach for a SQL cursor instead of a single UPDATE statement?

Use a cursor when you need fine-grained, row-by-row control—such as validating each order date before changing its status, applying different business rules per row, or chaining updates that depend on the outcome of a previous row. A set-based UPDATE excels at bulk changes, but it can’t evaluate custom logic for every record the way a cursor-driven loop can.

Why are cursors considered resource-intensive, and how can Galaxy help mitigate that overhead?

Cursors create server-side memory structures to hold the result set and maintain a pointer as you iterate. This can lock resources and slow queries on large datasets. Galaxy’s modern SQL editor highlights long-running cursor operations, surfaces execution plans, and uses its AI copilot to suggest set-based rewrites or batch sizes that reduce memory pressure—so you keep the control of a cursor without unnecessary load.

What alternatives exist to looping with a cursor, and does Galaxy support them?

Common alternatives include set-based queries, window functions, Common Table Expressions (CTEs), and stored procedures—all of which execute in bulk and minimize round-trips. Galaxy’s autocomplete, parameterization, and AI copilot help you author these cursor-free patterns quickly. You can experiment in the desktop app, compare runtimes, and share endorsed, performant SQL with your team through Galaxy Collections.