Tuning CTEs and Window Functions for High-Volume Records

When tracking merchant transactions across decoupled databases, poorly indexed joins can cause massive reporting bottlenecks.

In optimizing our revenue metrics pipeline, I migrated legacy queries to leverage isolated Common Table Expressions (CTEs) and Window Functions. This separation reduced runtime execution stress drastically.

The Optimization Strategy

WITH regional_revenue AS (
    SELECT 
        merchant_id,
        SUM(amount) OVER(PARTITION BY merchant_id) as total_mrr,
        ROW_NUMBER() OVER(PARTITION BY merchant_id ORDER BY created_at DESC) as rank
    FROM merchant_transactions
    WHERE status = 'settled'
)
SELECT merchant_id, total_mrr
FROM regional_revenue
WHERE rank = 1;