Top SQL Join Interview Questions

What is a SQL Join?

Joins in SQL are commands that we can use to pull data or combine data from different tables based on a common column. To join two tables (table_1, table_2) with a common key present as “id” using an SQL Join, we can use the SQL Join Query:

SELECT * FROM table_1, table_2 WHERE table_1.id = table_2.id;

Explain the Importance of SQL Joins in Database Management.

SQL joins are important because:

• They allow us to keep data redundancy low.
• They are a faster alternative to subqueries.
• They allow you to execute faster.
• They allow us to leverage filtering, sorting, etc to enable efficient usage of our database.

What are the different types of SQL Joins?

There are 4 different types of SQL Joins:

• Inner Join
• Left Join
• Right Join
• Full Join

Inner Join would combine two tables based on the common values that are present on both tables. We can run an inner join on the table_1 and table_2 using the common column “id” by: SELECT * FROM table_1 INNER JOIN table_2 ON table_1.id = table_2.id;

Left Join would combine the records of one table (left table) and any matching records that are present on the other table (right table). Here’s how you would run a Left SQL Join on table_1 as left table and table_2 as right table. “id” as the common key.

SELECT * FROM table_1 LEFT JOIN table_2 ON table_1.id = table_2.id;

Right JOIN would do the opposite of what we expected from the Left SQL Join. Based on the common column, only matching values are merged from the left table. Here’s how you would run a Right SQL Join on table_1 as left table and table_2 as right table - with “id” as the common key.

SELECT * FROM table_1 RIGHT JOIN table_2 ON table_1.id = table_2.id;

Full JOIN or a full outer Join returns all the rows from the tables we join. For example, if we merge table_1 and table_2 even with zero matching id values - it will return all rows from table_1 and table_2. Here’s how we can run a Full SQL Join.

SELECT * FROM table_1 FULL OUTER JOIN table_2 ON table_1.id = table_2.id;

Explain Merge Join in SQL?

Merge SQL Joins combine records from different tables and sort them based on the key columns. For example, if we were merging table_1 and table_2 based on the column “id”, the output will be sorted by “id” values.

What is the Difference between Left Join and Right Join? Explain the Difference by Applying them to table_1 and table_2.

Left Join retains the values in the left table, while only pulling matched values from the right table. Right Join, however, retains the values in the right table, while only pulling values from the left table.

table_1

id	values
1	100
2	312
3	157
4	199

table_2

id	values
1	57
2	98
8	357
112	1206

If we Left JOIN table_1 as left table and table_2 as right table with “id” as the key: SELECT * FROM table_1 LEFT JOIN table_2 ON table_1.id = table_2.id;

Our output, in this case, will be:

id	values_L	values_R
1	57	57
2	98	98
3	357
4	1206

If we Right Join table_1 as left table and table_2 as right table with “id” as the key: SELECT * FROM table_1 RIGHT JOIN table_2 ON table_1.id = table_2.id;

Our output, in this case, will be:

id	values_L	values_R
1	57	57
2	98	98
8	357
112	1206

Difference between Joins and Nested Queries

The difference between Joins and Nested queries are:

1. Nested queries are relatively easier to write.
2. Joins are easier to optimize for performance.
3. Query engines use a different query plan for JOINs vs Nested queries - which results in a different performance between them.
4. Nested queries require fewer statements compared to SQL JOINs.

Here’s an example of performance difference between and statement usage between SQL Join and Nested queries:

Example - SQL Join SELECT store.p_name FROM store JOIN pricing ON pricing.p_id = store.id JOIN discount ON discount.p_id = pricing.p_id WHERE year = 2019 GROUP BY pricing.price ORDER BY pricing.price

Example - Nested queries SELECT store.p_name FROM store WHERE store.id IN (SELECT pricing.p_id FROM pricing WHERE pricing.p_id IN (SELECT discount.p_id FROM discount WHERE year = 2004)) ORDER BY pricing.price

The SQL Join syntax took ~ 25 seconds to process, while the nested queries took ~ 2.3 seconds to process.

Write a SQL Query to Join these Three Tables

table_1

id	sales
1	57
2	98
3	58
4	79

table_2

id	pricing
1	10
2	4
3	15
4	12

table_3

id	discount
1	57
2	98
3	35
4	12

To join these tables, we can run this SQL Join query:

SELECT t1.id, t1.sales, t2.pricing, t3.discount FROM table_1 as t1 JOIN table_2 as t2 ON t2.id = t1.id JOIN table_3 as t3 ON t3.id = t2.id;

How Can You Join a Table to Itself?

We can use a Self Join to join a table to itself. We can use table_1 to understand how we can use SQL Self Join to get the category of the product with the table.

id	office_location	code	hq
1	Houston	12	1
2	Dallas	14	1
3	New Jersey	20	3

SELECT office.id, office.office_location, office.code, hq.hq as hqName FROM table_1 office JOIN table_1 hq ON employee.ManagerId = manager.Id

The output of this self SQL Join is:

id	office_location	code	hq
1	Houston	12	Houston
2	Dallas	14	Houston
3	New Jersey	20	New Jersey

How to Structure Data to Support Join Operations in a One-To-Many Relationship?

Define a foreign key in your tables that you can use to perform SELECT operations with SQL Joins.

How to Structure Data to Support Join Operations in a Many-To-Many Relationship?

To best structure data to support many-to-many relationships focus on the classic design pattern of separating entities with relations.

Relational databases are designed to support join or query overhead so separating by entities serves as the best starting point.

What is a Natural Join?

A Natural SQL Join is join that creates a table by using the common column and data type. Here’s an example of what will happen if we run Natural Join on table_1 and table_2

table_1

month	size
Aug	1223
Sep	997

table_2

month	cost
Aug	80
Sep	46

Natural Join query on table_1 and table_2: SELECT * FROM table_1 NATURAL JOIN table_2;

The output

month	size	cost
Aug	1223	80
Sep	997	46

If you are Joining a Lot of Tables, How Would you Know if you are Getting the Correct Results?

If you are ever asked this question in an interview, make sure to keep in mind that the interviewer is trying to understand how you would deal with complex SQL queries. The interviewer is trying to understand how you would deal with potential failure points.

In an ideal scenario, a candidate would start by stating that they would test as they write the query. This would help the interviewer understand that the candidate is carefully looking for SQL Join expansion, making sure that the Join works as intended and that there are unaccounted exclusions.

How to Deal With Expensive Joins?

Denormalization improves the issue with expensive joins. We can apply these 3 different types of denormalization:

1. Pre-calculate any expensive calculations so that you don’t have to use complex expressions or use other queries.
2. You can avoid Joins altogether by joining rows from different tables.
3. Avoid GROUP BY with aggregated calculations using MAX(), COUNT(), etc.

Improve the Readability of this Nested SQL Join

To review your code quality, you may be asked to improve the readability of an existing SQL Join query.

Here’s an example SQL Join query - our goal is to make it a bit more readable. FROM price s INNER JOIN stock C INNER JOIN location A ON C.a_Id = A.a_Id ON s.p_Id = C.c_Id AND s.s_code<>A.a_code

Readable SQL Join query: FROM price s INNER JOIN (SELECT * FROM stock C INNER JOIN location A ON C.a_Id = A.a_Id ) ca ON s.c_Id = ca.c_Id AND s.s_code<>ca.a_code

Note that the difference between both SQL Joins isn’t too big, but to write maintainable SQL, we recommend that you creatively think about how to improve the readability of your SQL joins.

When to Use a Right SQL Join?

Right SQL Joins are rarely used. And, even when used they are generally written when there’s an existing SQL Join query written in order to avoid reordering an existing SQL Join query.

Out of These Two SQL Joins - Which One Should be Used?

To experience professionals, you might be judged on how you select SQL Join operations. Here’s an example from MAANG SQL interviews. The candidate was asked to select one out of these two Joins:

1. RIGHT JOIN stock ON stock.p_id = price.p_id
2. WHERE stock.p_id = price.p_id (+)

The choice here should be purely based on the modern syntax. The first one is an “explicit Join” and it naturally leads to a lower number of mistakes.