Top Three Wineries

Top Three Wineries

What is this problem about?

"Top Three Wineries" is a database-centric challenge that involves analytical querying. Typically, you are given tables representing wineries, regions, and perhaps wine reviews or sales. The goal is to identify the three highest-rated or most-productive wineries within each specific region. This problem transitions the "Top K" concept from application-level code to SQL or database logic, requiring the use of window functions, groupings, and rankings.

Why is this asked in interviews?

Google and other data-driven companies use the "Top Three Wineries interview question" to assess a candidate's proficiency with SQL and data modeling. In modern software engineering, many tasks that were previously done in the backend application are now handled more efficiently by the database engine. Understanding how to perform "partitioned" rankings—where you find the top items for each category rather than the top items overall—is a crucial skill for data engineers and full-stack developers alike.

Algorithmic pattern used

The primary pattern here is "Window Functions" (specifically RANK(), DENSE_RANK(), or ROW_NUMBER()). These allow you to perform calculations across a set of table rows that are somehow related to the current row. By using the PARTITION BY clause on the region and ORDER BY on the rating/production, you can assign a rank to each winery within its region. The "Database interview pattern" then involves filtering these results to only include rows where the rank is less than or equal to 3.

Example explanation

Suppose you have a table of Wineries:

• Chateau St. Michelle, Washington, 95 points
• Columbia Crest, Washington, 92 points
• Hedges, Washington, 90 points
• K Vintners, Washington, 88 points
• Silver Oak, California, 98 points
• Opus One, California, 97 points ... and so on. The query would partition the data by state. In Washington, Chateau St. Michelle gets rank 1, Columbia Crest rank 2, and Hedges rank 3. K Vintners gets rank 4 and is excluded. The final result set would list the top 3 for Washington, then the top 3 for California, etc.

Common mistakes candidates make

A common mistake is using a simple GROUP BY and MAX(), which only gives you the top one winery per region, not the top three. Another error is not handling ties correctly—should two wineries with the same score both be included? This is where the choice between RANK() and DENSE_RANK() becomes important. Candidates also sometimes forget to filter the results in an outer query, as window functions cannot usually be used directly in a WHERE clause.

Interview preparation tip

Mastering SQL window functions is the best way to prepare for the "Top Three Wineries coding problem." Practice writing queries that use PARTITION BY and understanding how different ranking functions behave when they encounter identical values. This knowledge is highly transferable to other "Top N per group" problems.