How Can I Efficiently Retrieve the Maximum Value per Group in a Single SQL Table?

Optimizing SQL Queries for Maximum Value Retrieval per Group

Efficient data retrieval is paramount when working with large SQL tables. A frequent task involves identifying the maximum value within specific groups of rows. This article demonstrates optimized SQL queries to achieve this efficiently, avoiding multiple table scans.

Let's consider a SCORES table with ID, ROUND, and SCORE columns. The objective is to obtain the maximum ROUND for each ID and its corresponding SCORE. Inefficient methods involving iterative processing are unsuitable for large datasets.

The following query uses window functions and DISTINCT for optimal performance:

<code class="language-sql">SELECT DISTINCT
       id
      ,max(round) OVER (PARTITION BY id) AS round
      ,first_value(score) OVER (PARTITION BY id ORDER BY round DESC) AS score
FROM   SCORES
WHERE  id IN (1,2,3)
ORDER  BY id;</code>

This approach employs window functions to compute the maximum ROUND and corresponding SCORE within each ID group. The DISTINCT clause then removes duplicate rows, ensuring only the highest ROUND per ID is returned. This significantly reduces processing time compared to multiple table scans.

An alternative, equally effective method uses FIRST_VALUE twice:

<code class="language-sql">SELECT DISTINCT
       id
      ,first_value(round) OVER (PARTITION BY id ORDER BY round DESC) AS round
      ,first_value(score) OVER (PARTITION BY id ORDER BY round DESC) AS score
FROM   SCORES
WHERE  id IN (1,2,3)
ORDER  BY id;</code>

Both queries yield identical results:

ID	ROUND	SCORE
1	3	2
2	2	12
3	1	6

These optimized queries offer substantial performance improvements over less efficient methods by retrieving the maximum value per group in a single table scan. This is crucial for maintaining responsiveness when dealing with large datasets.

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