Yes, JOINs can cause duplicate rows when the relationship between tables is not strictly one-to-one. Any one-to-many or many-to-many relationship will multiply rows, which may appear as duplicates in the result set—especially when joining tables like customers → orders → order_items.

Why JOINs Cause Duplicates

1
One-to-many relationships expand rows (e.g., one order with multiple payments).
2
Duplicate matching values in the joined table multiply rows.
3
Lack of proper join conditions results in unintended row combinations.
4
Joining denormalized tables may bring repeated values that look like duplicates.

Example: JOIN that Produces Duplicates

If a customer has 3 orders, they appear 3 times. These aren't true "duplicates"—they're correct representations of a one-to-many relationship. But sometimes duplicates are accidental and need removal.

How to Eliminate Duplicate Rows

1
Use DISTINCT to return only unique combinations of selected columns.
2
Use GROUP BY to collapse rows (only when grouping makes sense).
3
Refine JOIN conditions to avoid unintended matches.
4
Normalize data to prevent duplicate stored values.
5
Use EXISTS instead of JOIN when only existence needs to be checked.

Using DISTINCT to Remove Duplicates

Using EXISTS to Avoid Join Multiplication

EXISTS is often faster and avoids row-multiplying JOINs when you're only checking whether related data exists.

Best Practices

1
Understand the relationship (one-to-one, one-to-many, many-to-many).
2
Use DISTINCT only when logically correct—it hides problems instead of fixing them.
3
Use GROUP BY when aggregating data, not just to remove duplicates.
4
Avoid unnecessary JOINs when simpler EXISTS queries suffice.

Scenario Questions

0-2 years experience

1You need to list each user with the number of orders they placed. After writing a LEFT JOIN between users and orders, the result shows multiple rows per user. How would you change the query so each user appears only once?
2When joining products with product_tags to show product details and tags, the query returns several rows for the same product because of multiple tags. Which MySQL clause can you add to keep only one row per product while still retrieving tag information?

2-5 years experience

1Our sales report started showing inflated totals after we added a JOIN between the sales and discounts tables. Walk me through how that JOIN could have introduced duplicate rows and what steps you’d take to fix it without losing needed discount data.
2We need a list of customers with their latest order date, joining customers, orders, and order_status tables. The output contains duplicate customers. Explain why the duplicates appear and propose a query rewrite that eliminates them while keeping the query reasonably fast.

5-8 years experience

1Design a data pipeline that aggregates daily active users from multiple sharded MySQL tables. The aggregation uses JOINs across shards and you notice duplicate user counts. How would you architect the pipeline to guarantee unique counts at scale?
2Our read‑replica service composes data from three MySQL services via a complex JOIN. Under high load the query returns duplicate rows and becomes a bottleneck. Discuss strategies—such as DISTINCT, sub‑queries, materialized views, or denormalization—and their trade‑offs for correctness and performance.

8+ years experience

1We are migrating a legacy monolith to a service‑oriented architecture. The legacy reporting queries rely on many multi‑table JOINs that produce duplicate rows, and we need to replace them with API calls. How would you refactor these queries to avoid duplicates while preserving semantics, and what long‑term architectural patterns would you establish to prevent similar issues?
2In a MySQL‑based data warehouse, duplicate rows from JOINs are corrupting KPI calculations across teams. Propose a cross‑team governance model and schema design guidelines that ensure future ETL jobs don’t introduce duplicate rows, considering both technical and process aspects.

Follow-up Questions

What are the performance trade‑offs between DISTINCT and a sub‑query?
How would you test that your change didn’t unintentionally drop needed rows?
When might GROUP BY change the semantics of the result compared to DISTINCT?

Sharethis question

Share via WhatsApp, X, Facebook, LinkedIn or copy link. Open Graph preview enabled.