Big Countries

Big Countries

What is this problem about?

The "Big Countries interview question" is a fundamental SQL challenge. You are given a table World with columns name, continent, area, population, and gdp. A country is considered "big" if it meets at least one of two criteria: it has an area of at least 3 million $km^2$, OR it has a population of at least 25 million. Your task is to write a query that returns the name, population, and area of all big countries.

Why is this asked in interviews?

Companies like Microsoft and Google use the "Big Countries coding problem" as a basic competency check for SQL. It tests whether a candidate knows how to use the WHERE clause with the OR operator and how to select specific columns. It's an "entry-level" database question but essential for any developer role.

Algorithmic pattern used

This problem uses the SQL Selection and Filtering pattern.

1. Columns: Use SELECT name, population, area.
2. Condition: Use WHERE area >= 3000000 OR population >= 25000000. Note: In some database optimization contexts, using UNION of two separate queries (one for area, one for population) can sometimes be faster than an OR clause if the columns are indexed, though for this simple problem, OR is the standard answer.

Example explanation

Table World:

• Afghanistan, Asia, 652230, 25500100, 20364000
• Albania, Europe, 28748, 2831741, 12960000
• Algeria, Africa, 2381741, 37100000, 188681000 Result:
• Afghanistan (Population is > 25M)
• Algeria (Population is > 25M) Albania is not included because it fails both criteria.

Common mistakes candidates make

• Selecting all columns: Using SELECT * instead of the specific columns requested.
• Incorrect logic: Using AND instead of OR. A country only needs to meet one of the criteria.
• Number format: Adding commas to the numbers in the SQL query (e.g., 3,000,000), which causes a syntax error.

Interview preparation tip

For SQL interviews, always pay close attention to the specific columns requested in the output. Also, understand that OR can sometimes be inefficient on massive datasets; mentioning UNION as an alternative optimization shows the interviewer you have "Database interview pattern" depth.