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.
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
Build SQL pivot with lookups and currency conversion
Write SQL: sum values ≤ each row’s value
Write SQL for late-delivery metrics by window
Query conversion and retention with SQL windows
Clean and aggregate factory event data in Pandas
Transform event logs with subscription windows in pandas
Find top-spend categories per customer with ranking
Merge four CSVs locally, robustly and efficiently
Write SQL for hashtag analytics and joins
Write SQL to localize anomaly and funnel
Compute age-band spend and YoY in Georgia
Transform retail data with pandas groupby/merge/concat
Label new vs old users over time in SQL
Calculate posts per DAU by country today
Write SQL window functions for streaks
Write SQL with HAVING and efficient joins
Merge seven tables into one clean DataFrame
Unify 7 tables and impute missing values
Manipulate and merge DataFrames correctly
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 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.