What are examples of converting procedural loops into efficient declarative SQL queries?

 Converting procedural loops into efficient declarative SQL queries is a great way to improve performance, readability, and maintainability in your database code. In SQL, you avoid using explicit loops and instead rely on set-based operations, which are generally more efficient than row-by-row operations. Here are a few examples of how you can make this conversion:

1. Sum a Series of Values

Procedural Approach (Using Loop):

DECLARE @total INT = 0;
DECLARE @i INT = 1;

WHILE @i <= 10
BEGIN
    SET @total = @total + @i;
    SET @i = @i + 1;
END
SELECT @total;

Declarative Approach (Using SQL):

SELECT SUM(number) AS total
FROM (VALUES (1), (2), (3), (4), (5), (6), (7), (8), (9), (10)) AS numbers(number);

2. Updating Rows Based on Condition

Procedural Approach (Using Loop):

DECLARE @id INT;
DECLARE @newValue INT;

DECLARE cursor_example CURSOR FOR
SELECT id FROM my_table WHERE status = 'active';

OPEN cursor_example;
FETCH NEXT FROM cursor_example INTO @id;

WHILE @@FETCH_STATUS = 0
BEGIN
    SET @newValue = @id * 10;
    UPDATE my_table
    SET value = @newValue
    WHERE id = @id;
    FETCH NEXT FROM cursor_example INTO @id;
END

CLOSE cursor_example;
DEALLOCATE cursor_example;

Declarative Approach (Using SQL):

UPDATE my_table
SET value = id * 10
WHERE status = 'active';

3. Iterating Over Data to Perform Aggregation

Procedural Approach (Using Loop):

DECLARE @sum INT = 0;
DECLARE @value INT;

DECLARE cursor_example CURSOR FOR
SELECT amount FROM transactions;

OPEN cursor_example;
FETCH NEXT FROM cursor_example INTO @value;

WHILE @@FETCH_STATUS = 0
BEGIN
    SET @sum = @sum + @value;
    FETCH NEXT FROM cursor_example INTO @value;
END

CLOSE cursor_example;
DEALLOCATE cursor_example;

SELECT @sum AS total_sum;

Declarative Approach (Using SQL):

SELECT SUM(amount) AS total_sum
FROM transactions;

4. Inserting Data into Another Table with Transformations

Procedural Approach (Using Loop):

DECLARE @id INT;
DECLARE @value INT;

DECLARE cursor_example CURSOR FOR
SELECT id, value FROM old_table;

OPEN cursor_example;
FETCH NEXT FROM cursor_example INTO @id, @value;

WHILE @@FETCH_STATUS = 0
BEGIN
    INSERT INTO new_table (id, transformed_value)
    VALUES (@id, @value * 2);
    FETCH NEXT FROM cursor_example INTO @id, @value;
END

CLOSE cursor_example;
DEALLOCATE cursor_example;

Declarative Approach (Using SQL):

INSERT INTO new_table (id, transformed_value)
SELECT id, value * 2
FROM old_table;

5. Removing Duplicate Rows

Procedural Approach (Using Loop):

DECLARE @id INT;

DECLARE cursor_example CURSOR FOR
SELECT DISTINCT id FROM my_table;

OPEN cursor_example;
FETCH NEXT FROM cursor_example INTO @id;

WHILE @@FETCH_STATUS = 0
BEGIN
    DELETE FROM my_table
    WHERE id = @id AND row_id NOT IN (
        SELECT MIN(row_id)
        FROM my_table
        WHERE id = @id
        GROUP BY id
    );
    FETCH NEXT FROM cursor_example INTO @id;
END

CLOSE cursor_example;
DEALLOCATE cursor_example;

Declarative Approach (Using SQL):

WITH CTE AS (
    SELECT id, ROW_NUMBER() OVER (PARTITION BY id ORDER BY row_id) AS rn
    FROM my_table
)
DELETE FROM my_table
WHERE row_id IN (SELECT row_id FROM CTE WHERE rn > 1);

Key Takeaways:

• Procedural loops often iterate over rows, one at a time. In SQL, this is inefficient because SQL is optimized for working with sets of data at once.
• The declarative SQL approach leverages set-based operations like UPDATE, INSERT, SELECT, and DELETE that work with entire sets of rows in a single operation.
• By avoiding cursors and loops, declarative SQL can significantly improve performance, especially for large datasets.

By converting your procedural logic into set-based SQL queries, you ensure the code is optimized for the relational database's capabilities, which are designed for set processing rather than row-by-row iteration.