Stores ordered by monthly profit including monthly revenue growth

CREATE OR REPLACE FUNCTION get_stores_by_monthly_profit_and_revenue_growth()
RETURNS TABLE (
    store_id INT,
    store_name TEXT,
    month_and_year TEXT,
    monthly_profit NUMERIC,
    previous_month_revenue NUMERIC,
    current_month_revenue NUMERIC,
    revenue_growth NUMERIC
)
LANGUAGE plpgsql
AS $$
BEGIN
    RETURN QUERY
    WITH monthly_revenue AS (
        SELECT
            s.store_id,
            s.name AS store_name,
            DATE_TRUNC('month', o.last_modified_date) AS month_date,
            SUM(
                p.price
                * o.quantity
                * (1 - COALESCE(o.discount, 0) / 100.0)
            ) AS revenue
        FROM store s
        JOIN sells se
            ON s.store_id = se.store_id
        JOIN product p
            ON se.code = p.code
        JOIN includes i
            ON p.code = i.code
        JOIN "order" o
            ON i.order_num = o.order_num
        GROUP BY
            s.store_id,
            s.name,
            DATE_TRUNC('month', o.last_modified_date)
    ),
    revenue_with_previous AS (
        SELECT
            store_id,
            store_name,
            month_date,
            revenue,
            LAG(revenue) OVER (
                PARTITION BY store_id
                ORDER BY month_date
            ) AS previous_month_revenue
        FROM monthly_revenue
    )
    SELECT
        store_id,
        store_name,
        TO_CHAR(month_date, 'YYYY-MM') AS month_and_year,
        revenue AS monthly_profit,
        COALESCE(previous_month_revenue, 0) AS previous_month_revenue,
        revenue AS current_month_revenue,
        revenue - COALESCE(previous_month_revenue, 0) AS revenue_growth
    FROM revenue_with_previous
    ORDER BY
        monthly_profit DESC,
        revenue_growth DESC;
END;
$$;

Relational Algebra

• P(code, price, availability, description, ...)
• O(order_num, quantity, status, last_modified_date, payment_method, discount)
• I(code, order_num)
• S(store_id, name, date_of_founding, physical_address, store_email, rating)
• SE(code, store_id, quantity, discount)

JOIN stores with their products:

• J1 ← S ⨝S.store_id = SE.store_id SE
• J2 ← J1 ⨝SE.code = P.code P

JOIN products with orders:

• J3 ← J2 ⨝P.code = I.code I
• J4 ← J3 ⨝I.order_num = O.order_num O

Calculate revenue for each order and group it by store and month:

• FORMULA: order_revenue = price × quantity × (1 - COALESCE(discount, 0) / 100)
• R1 ← γstore_id, name, YEAR(last_modified_date),

MONTH(last_modified_date); Σ(order_revenue) → monthly_revenue (J4)

Calculate previous month revenue for each store:

• R2 ← γstore_id, name, month;

LAG(monthly_revenue) OVER (PARTITION BY store_id ORDER BY month) → previous_month_revenue (R1)

Calculate monthly revenue growth:

• R3 ← πstore_id, name, month,

monthly_revenue, previous_month_revenue, monthly_revenue - previous_month_revenue → revenue_growth (R2)

Sort by total monthly revenue and growth:

• R_final ← τmonthly_revenue DESC,

revenue_growth DESC(R3)