Understanding Cursors in SQL Server: Examples, Performance, and Best Practices

Cursors in SQL Server are a powerful feature that allows developers to process database rows one at a time. While they offer flexibility for certain tasks, understanding their performance implications and best practices is crucial. This article will delve into cursor examples, performance considerations, and when to effectively utilize them in SQL Server.

What is a Cursor in SQL Server?

In SQL Server, a cursor is a database object that enables you to traverse through the records in a result set, one row at a time. Think of it as a pointer that moves through the rows returned by a query. This row-by-row processing is fundamentally different from set-based operations, where SQL Server works on entire sets of data simultaneously.

Cursors are often employed when you need to perform operations on each individual row of a result set, such as:

Row-level calculations or transformations: When you need to apply complex logic or calculations that depend on the values within each specific row.
Procedural logic within SQL: Implementing iterative processes or workflows directly within your database code.
Integration with external systems: Processing data row by row to interact with external applications or services.

However, it’s important to recognize that cursors are not always the most efficient solution, especially when dealing with large datasets.

Cursor Example in SQL Server (T-SQL)

Let’s look at a basic example of a cursor in Transact-SQL (T-SQL) that iterates through a table named MyTable and retrieves MyID and MyString from each row.

/* Set up variables to hold the current record we're working on */
DECLARE @CurrentID INT, @CurrentString VARCHAR(100);

DECLARE cursor_results CURSOR FOR
SELECT MyID, MyString
FROM dbo.MyTable;

OPEN cursor_results
FETCH NEXT FROM cursor_results INTO @CurrentID, @CurrentString

WHILE @@FETCH_STATUS = 0
BEGIN
    /* Do something with your ID and string */
    EXEC dbo.MyStoredProcedure @CurrentID, @CurrentString;

    FETCH NEXT FROM cursor_results INTO @CurrentID, @CurrentString
END

/* Clean up our work */
CLOSE cursor_results;
DEALLOCATE cursor_results;

Explanation of the code:

Variable Declaration: @CurrentID and @CurrentString are declared to store the values fetched from each row during cursor iteration.
Cursor Declaration: DECLARE cursor_results CURSOR FOR SELECT MyID,MyString FROM dbo.MyTable; This line declares a cursor named cursor_results. It is associated with a SELECT statement that defines the result set the cursor will work on.
Opening the Cursor: OPEN cursor_results initializes the cursor and makes it ready to be used.
Fetching the First Row: FETCH NEXT FROM cursor_results INTO @CurrentID, @CurrentString retrieves the first row from the result set and populates the @CurrentID and @CurrentString variables. @@FETCH_STATUS is a system function that returns 0 if the fetch was successful, and a non-zero value if it failed (e.g., no more rows).
Looping Through Rows: WHILE @@FETCH_STATUS = 0 BEGIN ... END initiates a loop that continues as long as @@FETCH_STATUS is 0 (meaning rows are being successfully fetched).
Processing Each Row: EXEC dbo.MyStoredProcedure @CurrentID, @CurrentString; Inside the loop, this line represents the operation performed on each row. In this example, it executes a stored procedure MyStoredProcedure with the current @CurrentID and @CurrentString as parameters. You would replace this with your desired row-level processing logic.
Fetching the Next Row: FETCH NEXT FROM cursor_results INTO @CurrentID, @CurrentString fetches the next row in the result set, preparing for the next iteration of the loop.
Closing and Deallocating: CLOSE cursor_results; DEALLOCATE cursor_results; These lines are crucial for releasing resources. CLOSE closes the cursor, and DEALLOCATE removes the cursor object entirely. Failing to close and deallocate cursors can lead to resource leaks and performance issues.

Performance Implications of Cursors

Cursors, due to their row-by-row nature, are generally less performant than set-based operations in SQL Server. This is because:

Row-by-Row Processing (RBAR – Row By Agonizing Row): As Jeff Moden famously coined, cursors often lead to “Row By Agonizing Row” processing. SQL Server is optimized for set-based operations, where it can efficiently process large chunks of data at once. Cursors bypass this optimization, forcing the database engine to work much harder for each individual row.
Increased CPU Usage: Iterating through rows and performing operations within a cursor loop consumes more CPU cycles compared to set-based approaches that leverage SQL Server’s optimized query processing.
Lock Escalation and Blocking: Cursors can hold locks on database resources for longer durations because they process data sequentially. This can lead to lock escalation (converting row locks to table locks) and blocking other concurrent operations, especially in high-transaction environments.

Brent Ozar humorously criticizing cursors with a picture of himself.

Set-Based Alternatives

Whenever possible, it is highly recommended to replace cursor-based logic with set-based operations. Set-based operations utilize SQL Server’s ability to work with entire datasets at once, leading to significantly better performance. Common set-based techniques include:

UPDATE, DELETE, INSERT with WHERE clauses: These statements can efficiently modify or retrieve sets of rows based on conditions, eliminating the need for row-by-row iteration.
JOIN operations: Combining data from multiple tables in a single query using joins is far more efficient than using cursors to loop through tables and perform lookups.
Window Functions: For calculations that involve related rows (e.g., running totals, rankings), window functions provide a set-based and performant alternative to cursors.
Common Table Expressions (CTEs) and Derived Tables: Structuring complex queries into logical steps using CTEs or derived tables can often achieve the same results as cursors in a set-based manner.

For example, if the cursor in the example above was intended to update a table based on MyStoredProcedure, you could likely achieve the same outcome with a set-based UPDATE statement joining MyTable with another table or using a more efficient stored procedure that works on sets.

When to Use Cursors (and When to Avoid Them)

While set-based operations are generally preferred, there are still scenarios where cursors might be considered appropriate:

Appropriate Use Cases:

One-time administrative tasks or scripts: For infrequent tasks like database maintenance routines or data migration scripts that are not performance-critical and require row-level logic, cursors might be acceptable for simplicity.
Operations on small datasets: If you are working with a very small number of rows, the performance overhead of a cursor might be negligible.
Situations where set-based logic is extremely complex or impractical: In rare cases, translating complex procedural logic into set-based operations might become overly convoluted. Cursors can sometimes offer a more straightforward, albeit less performant, solution in such situations.

When to Avoid Cursors:

Transactional operations in high-volume systems: Avoid cursors in online transaction processing (OLTP) environments or any system where performance and concurrency are critical.
Batch processing of large datasets: For processing large volumes of data, set-based operations will always be significantly faster and more efficient than cursors.
Any situation where a set-based alternative exists: Always explore and prioritize set-based solutions before resorting to cursors.

Cursor Types (Briefly)

SQL Server offers different types of cursors, each with varying characteristics and performance implications. Some common cursor types include:

FAST_FORWARD cursors: These are the most performant type, optimized for forward-only, read-only access. They are generally a better choice than other cursor types if you need to use a cursor.
STATIC cursors: These cursors take a snapshot of the data when they are opened. Changes made to the underlying data after the cursor is opened are not reflected in the cursor result set.
DYNAMIC cursors: Dynamic cursors reflect changes made to the underlying data while the cursor is open. This makes them more resource-intensive but provides up-to-date data.
KEYSET cursors: These are a compromise between static and dynamic cursors. They are aware of row insertions and deletions but might not reflect all updates to data values.

Choosing the appropriate cursor type can impact performance, but even FAST_FORWARD cursors are generally less efficient than set-based operations.

Best Practices for Using Cursors (If Necessary)

If you must use cursors, follow these best practices to mitigate performance issues:

Use FAST_FORWARD cursors whenever possible: They offer the best performance among cursor types.
Minimize operations within the cursor loop: Keep the code inside the WHILE loop as lean and efficient as possible.
Fetch only necessary columns: Select only the columns you actually need in the cursor’s SELECT statement to reduce data retrieval overhead.
Close and deallocate cursors promptly: Always ensure you CLOSE and DEALLOCATE cursors to release resources.
Consider temporary tables or table variables: In some cases, using temporary tables or table variables in conjunction with set-based operations can provide a more performant alternative to cursors.

Conclusion

Cursors in SQL Server provide row-by-row processing capabilities, which can be useful in specific scenarios. However, they are generally less performant than set-based operations and should be used judiciously. Prioritize set-based alternatives whenever possible for optimal database performance. Understanding the performance implications and best practices associated with cursors is essential for writing efficient and scalable SQL Server code.

More Cursor Resources

ReBAR – Row By Agonizing Row by Jeff Moden – A classic article highlighting the performance pitfalls of row-by-row processing.
Stack Overflow answer on converting a cursor to set-based operation – Practical examples of converting cursor-based logic to set-based solutions.
The Truth About Cursors: Part 1, Part 2, Part 3 by Brad Schulz – In-depth articles exploring different aspects of cursor performance and behavior.

Cursor Training Videos

[Date Table Explanation by Doug Lane](Link to video if available) – (Note: The original article mentions a 16-minute video but doesn’t provide a link. If you have the link, include it here.) This video explains how to use date tables, which can help avoid cursors when dealing with date ranges.