Remove Duplicates — Solution & ExplanationProblems / Remove Duplicates / EditorialApproachThe key insight is that duplicates share the same customer_name, product, quantity, and order_date. By grouping on these columns and taking MIN(order_id), we keep only the first occurrence.SQL```sqlSELECT MIN(order_id) AS order_id, customer_name, product, quantity, order_dateFROM ordersGROUP BY customer_name, product, quantity, order_date```An alternative approach uses ROW_NUMBER() with a window function, but the GROUP BY approach is simpler for this case since we only need the minimum order_id.Hints

Think about which columns define a 'unique' order — everything except order_id.

GROUP BY the duplicate-defining columns and use an aggregate function on order_id to pick the first one.

In PySpark, .groupBy().agg() lets you aggregate one column while grouping by others.

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