SQL Questions for an Interview: Why Most Candidates Fail the Live Coding Test

You've spent weeks mastering Python, tweaking your portfolio, and polishing your resume until it shines. Then the recruiter calls. They mention a technical screening involving sql questions for an interview, and suddenly, your stomach drops. It’s funny, honestly. SQL is the "old reliable" of the tech world, yet it’s the exact place where brilliant data scientists and developers trip over their own feet.

Most people treat SQL like a syntax memory game. They memorize SELECT, FROM, and WHERE, thinking they’re ready for the big leagues. But here’s the reality: interviewers don't actually care if you remember every niche string function. They want to see if you can think in sets. They want to know if you understand how data moves through a pipeline.

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The JOIN Trap Everyone Falls Into

Most sql questions for an interview start with something simple. "Join these two tables." Easy, right? You write a standard INNER JOIN and call it a day. But an expert interviewer is watching for the edge cases. They want to see if you ask about nulls.

If you join a Sales table to a Product table and some products haven't sold yet, an INNER JOIN wipes them from existence. You’ve just lost data. A senior engineer will look for you to use a LEFT JOIN to preserve that integrity. It’s a tiny distinction that separates juniors from people who can be trusted with a production database.

I once saw a candidate breeze through complex subqueries only to fail because they didn't realize a many-to-many join would cause a Cartesian product, effectively blowing up the tempdb. That’s the kind of mistake that costs companies money.

Why Window Functions Are the New Minimum Bar

Ten years ago, you could get a job just knowing how to use GROUP BY. Those days are gone. If you can't use RANK(), LEAD(), or LAG(), you're basically bringing a knife to a gunfight.

Window functions allow you to perform calculations across a set of table rows that are somehow related to the current row. Think of it like this: GROUP BY collapses your data into a summary. Window functions keep the individual rows but let you peek at their neighbors.

Take the "Running Total" problem. It’s a classic. You’re asked to find the cumulative sum of sales over time.
$$\text{Running Total}t = \sum{i=1}^{t} \text{Sales}_i$$
You could try some messy self-join, but that's slow and unreadable. The pro move is:
SUM(amount) OVER (ORDER BY date)
It’s clean. It’s efficient. It shows you know how the engine actually processes data.

The Performance Nuance Nobody Talks About

We need to talk about "SARGability." It sounds like a made-up word, but it stands for Search ARGumentable. Basically, it means writing queries that allow the SQL Server to actually use its indexes.

If you put a function on a column in your WHERE clause—something like WHERE YEAR(order_date) = 2023—you’ve just killed performance. The database has to calculate that function for every single row before it can compare it. It’s a full table scan. Instead, you should use a range: WHERE order_date >= '2023-01-01' AND order_date < '2024-01-01'.

Small change. Massive impact.

Interviewers love to give you a query that works but runs slowly and ask you to fix it. They aren't looking for a magic "go fast" button. They are looking for an understanding of B-Tree indexes and execution plans. They want to see if you can explain the difference between a Hash Match and a Nested Loop.

Complex Scenarios: The "Gaps and Islands" Problem

This is the boss fight of sql questions for an interview.

Imagine a table of user logins. You need to find the longest "streak" of consecutive days a user logged in. This isn't just a simple filter. You have to identify groups of continuous data (islands) separated by missing data (gaps).

There are a few ways to solve this, but the most elegant involves using ROW_NUMBER(). By subtracting a sequential row number from the date, all dates in a streak will result in the same constant value. It’s a bit of "math magic" that proves you aren't just a script kiddie.

Common Pitfalls in Logic

• Handling NULLs: In SQL, NULL = NULL is false. Use IS NULL.
• Distinct vs. Group By: Using DISTINCT is often a lazy way to hide a bad join.
• Union vs. Union All: UNION removes duplicates, which requires an expensive sort operation. If you know the data is unique, always use UNION ALL.
• Subqueries vs. CTEs: Common Table Expressions (CTEs) are generally preferred for readability, though performance is usually identical in modern optimizers like PostgreSQL or SQL Server.

Honestly, the "right" answer often depends on the flavor of SQL you're using. T-SQL (Microsoft) handles certain things differently than PL/pgSQL (Postgres) or BigQuery’s GoogleSQL. Mentioning these platform-specific quirks shows you’ve actually worked in the trenches.

Strategic Preparation for the Technical Round

Don't just stare at LeetCode.

Start by building a mental "query order of operations." You write SELECT first, but the database processes FROM and JOIN long before it ever looks at your column list. Understanding this flow—FROM -> WHERE -> GROUP BY -> HAVING -> SELECT -> ORDER BY—is the key to debugging your own logic on the fly.

When you're hit with a question you don't know, talk through your logic. "I'm thinking I need to group these by user ID, but I need to filter the aggregates, so I'll use a HAVING clause instead of WHERE." This tells the interviewer how you solve problems. Often, the process matters more than the semicolon.

Actionable Next Steps for Success

1. Practice the "Big Three" Patterns: Master the "Top N per Group" (using ROW_NUMBER()), the "Running Total" (using SUM() OVER), and the "Gaps and Islands" logic.
2. Learn to Read Execution Plans: Download a sample database like Northwind or AdventureWorks. Run a query and look at the "Actual Execution Plan." Look for "Scans" vs. "Seeks."
3. Audit Your Old Projects: Go back to a SQL script you wrote six months ago. Can you make it SARGable? Can you replace a correlated subquery with a CTE or a cross apply?
4. Mock Your Coding: Open a plain text editor—no autocomplete, no syntax highlighting—and write a query that joins three tables with a conditional aggregation. If you can do it there, you can do it on a whiteboard.

Focus on the "why" behind the data relationships. Databases are just digital representations of real-world messy logic. If you can translate a business problem into a set of relational operations, the syntax will eventually become second nature. Master the set-based mindset, and the interview becomes just another conversation about solving problems.