How to Efficiently Retrieve the Top N Items for Each Group Using SQL's GROUP BY?

SQL Group BY: Fetching Top N Items for Each Group

When working with data in SQL, it's often necessary to group records based on common criteria and perform calculations or aggregations within each group. This is where the GROUP BY clause comes into play. This article discusses a powerful technique that combines GROUP BY with the ROW_NUMBER() function to efficiently retrieve the top N items for each group in a single query.

Problem: Top Sold Items Per Store

Consider a scenario where we have a Sales table with columns UPCCode, SaleDate, StoreId, and TotalDollarSales. The task is to identify the top 5 sold items at each store.

Query:

We could approach this problem with multiple individual queries using UNION, but that may not be efficient. Instead, the following query leverages a subquery and the ROW_NUMBER() function:

WITH s AS (
  SELECT StoreID, UPCCode, tds, rn = ROW_NUMBER()
  OVER (PARTITION BY StoreID ORDER BY tds DESC)
  FROM
  (
    SELECT StoreID, UPCCode, tds = SUM(TotalDollarSales)
    FROM Sales
    GROUP BY StoreID, UPCCode
  ) AS s2
)
SELECT StoreID, UPCCode, TotalDollarSales = tds
FROM s
WHERE rn <= 5
ORDER BY StoreID, TotalDollarSales DESC;

Explanation:

1. The nested subquery (s2) groups the Sales data by StoreID and UPCCode and calculates the total sales (tds) for each combination.
2. The main subquery (s) wraps around s2 and introduces the ROW_NUMBER() function. This function assigns a sequential number (rn) to each record within each partition (StoreID).
3. In the final query, we filter for rows where rn is less than or equal to 5 (i.e., the top 5 records for each partition) and extract the StoreID, UPCCode, and TotalDollarSales for each qualified item.

Conclusion:

This advanced SQL query allows you to efficiently gather the top N items for each group, tackling common data processing scenarios elegantly and enhancing your query optimization skills.

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