Questions Premium Learning CoachingNEW Careers

Master your tech interviews with 6000+ real questions from top companies.

Product

Questions
Learning Tracks
Premium
Careers

Community

Join Discord
Instagram
YouTube

Support

support@prachub.com
(916) 541-4762

Legal

Privacy Policy
Terms of Service
About Us

© 2026 PracHub. All rights reserved.

SQL JOIN Interview Questions (2026)

SQL JOIN Interview Questions

Home
/
Topics
/
SQL Data Manipulation Interview Questions
/
SQL JOIN Interview Questions

SQL JOIN Interview Questions

SQL JOIN questions test whether you can combine data across tables while preserving the right grain and relationships. Expect INNER, LEFT, RIGHT, CROSS, and FULL OUTER JOINs, plus multi-table joins and JOIN + aggregation patterns.

169Questions

43Companies

Easy 0 • Medium 169 • Hard 0Difficulty mix

Common SQL JOIN interview patterns

INNER vs LEFT JOIN logic
Anti-joins (find missing records)
Self-joins for comparisons within a table
JOIN + GROUP BY for aggregated results
Conditional joins with additional predicates
Multi-key joins across composite keys
Deduplication using JOINs

SQL JOIN interview questions

Filter and sort

Sort

All SQL questions

Aggregate exam scores with NULL handling

Data Manipulation (SQL/Python)

October 13, 2025

Exclude free subscribers via anti-join

Data Manipulation (SQL/Python)

October 13, 2025

Compute monthly new subscribers and YoY deltas

Data Manipulation (SQL/Python)

October 13, 2025

Compute 7-day views and reactions by relationship

Data Manipulation (SQL/Python)

October 13, 2025

Assess SQL cleaning, mapping, joins, keys, and DDL/DML

Data Manipulation (SQL/Python)

October 13, 2025

Software Engineer

Write SQL to Join Merchants and Triple Restaurant Points

Data Manipulation (SQL/Python)

September 6, 2025

Software Engineer

Debug a Hive query

Data Manipulation (SQL/Python)

September 6, 2025

Debug a Hive Query for DAU

Data Manipulation (SQL/Python)

September 6, 2025

Calculate and Find Average Contacts and Sync Percentage

Data Manipulation (SQL/Python)

Calculate Net Pay Change for Q1 2023 Decreases

Data Manipulation (SQL/Python)

Create SQL Queries for Sales and Customer Analysis

Data Manipulation (SQL/Python)

Derive Key Business Metrics Using SQL or Python

Data Manipulation (SQL/Python)

Calculate Monthly Revenue from Orders in 2023

Data Manipulation (SQL/Python)

Explain Window Functions and Joins in SQL and Python

Data Manipulation (SQL/Python)

Calculate Average Rate and Cumulative Jobs by State

Data Manipulation (SQL/Python)

Calculate Monthly Conversion Rate and Average Order Value

Data Manipulation (SQL/Python)

Calculate Second-Degree Followers for Each YouTuber

Data Manipulation (SQL/Python)

Calculate Conversion Rate from Ad Clicks to Page Visits

Data Manipulation (SQL/Python)

Calculate Top Countries' Gmail Usage and MoM Change

Data Manipulation (SQL/Python)

Calculate and Compare Survey Response Rates for User Tenure

Data Manipulation (SQL/Python)

PreviousPage 8 of 9Next

Common mistakes with SQL JOINs

JOIN explosion from many-to-many relationships
Filtering in WHERE instead of ON for LEFT JOINs
Incorrect NULL handling on optional joins
COUNT(*) vs COUNT(column) confusion
Duplicate rows after joins

How JOIN questions are evaluated in interviews

Correctness beats performance; the right result set matters most.

Explain your join keys, assumptions, and how NULLs are treated.

Reasoning and clarity matter more than memorized syntax.

Related SQL concepts

SQL window function interview questions
SQL aggregation interview questions
SQL CTE and subquery interview questions
SQL NULL handling interview questions

SQL JOIN Interview FAQs

What is the difference between INNER JOIN and LEFT JOIN in interviews?

INNER JOIN returns only matching rows from both tables, while LEFT JOIN keeps all rows from the left table and fills unmatched right rows with NULLs. Interviewers often test whether you choose the correct join for required vs optional relationships.

When should I use a subquery instead of a JOIN?

Use a subquery when you need to filter or aggregate before joining, or when a correlated condition is clearer. JOINs are better for combining row-level data, while subqueries can simplify multi-step logic.