Why NATURAL join and its risks in PostgreSQL? - Purpose & Use Cases

The Big Idea

What if a simple automatic join silently breaks your data without you noticing?

The Scenario

Imagine you have two lists of friends from different groups, and you want to find who appears in both lists by matching their names. Doing this by hand means checking each name one by one, which takes forever and is easy to mess up.

The Problem

Manually comparing lists is slow and mistakes happen easily, like missing a name or mixing up details. When tables have many columns, it's hard to remember which ones to match, leading to wrong or incomplete results.

The Solution

The NATURAL join automatically matches columns with the same names in both tables, saving you from writing long conditions. But it can be risky because if new columns with the same name appear, it might join on them unexpectedly, causing confusing results.

Before vs After

✗ Before

SELECT * FROM table1 JOIN table2 ON table1.id = table2.id AND table1.name = table2.name;

✓ After

SELECT * FROM table1 NATURAL JOIN table2;

What It Enables

NATURAL join lets you quickly combine tables by shared columns without extra code, but you must watch out for hidden surprises when table structures change.

Real Life Example

Suppose a store has separate tables for orders and customers, both with a 'customer_id' column. Using NATURAL join can quickly show all orders with customer details, but if a new 'address' column is added to both tables, the join might include it unexpectedly, causing errors.

Key Takeaways

NATURAL join matches tables by all columns with the same names automatically.

This saves time but can cause unexpected results if tables change.

Always check your tables' columns before using NATURAL join to avoid risks.

Practice

1. What does a NATURAL JOIN do in PostgreSQL?

easy

A. It joins tables automatically on all columns with the same names.

B. It joins tables only on the primary key columns.

C. It joins tables using a user-specified condition.

D. It joins tables without any condition, creating a Cartesian product.

Solution

1. Step 1: Understand NATURAL JOIN behavior

   NATURAL JOIN matches columns with the same names in both tables automatically.

2. Step 2: Compare with other join types

   Unlike explicit JOIN ON, NATURAL JOIN does not require specifying join conditions; it uses all common column names.

3. Final Answer:

   It joins tables automatically on all columns with the same names. -> Option A

4. Quick Check:

   NATURAL JOIN = automatic matching columns [OK]

Hint: NATURAL JOIN matches all same-named columns automatically [OK]

Common Mistakes:

• Thinking NATURAL JOIN uses only primary keys
• Confusing NATURAL JOIN with CROSS JOIN
• Assuming NATURAL JOIN requires explicit ON condition

2. Which of the following is the correct syntax for a NATURAL JOIN between tables employees and departments?

easy

A. SELECT * FROM employees NATURAL JOIN departments;

B. SELECT * FROM employees JOIN departments ON employees.id = departments.id;

C. SELECT * FROM employees CROSS JOIN departments;

D. SELECT * FROM employees INNER JOIN departments USING (id);

Solution

1. Step 1: Identify NATURAL JOIN syntax

   The correct syntax uses the keyword NATURAL JOIN directly between table names.

2. Step 2: Compare options

   SELECT * FROM employees NATURAL JOIN departments; uses NATURAL JOIN correctly; others use different join types or explicit conditions.

3. Final Answer:

   SELECT * FROM employees NATURAL JOIN departments; -> Option A

4. Quick Check:

   Correct NATURAL JOIN syntax = SELECT * FROM employees NATURAL JOIN departments; [OK]

Hint: NATURAL JOIN keyword goes directly between table names [OK]

Common Mistakes:

• Using ON clause with NATURAL JOIN
• Confusing NATURAL JOIN with USING clause
• Writing CROSS JOIN instead of NATURAL JOIN

3. Given two tables:
students(id, name, class)
enrollments(id, class, grade)
What will be the result of this query?

SELECT * FROM students NATURAL JOIN enrollments;

medium

A. All rows from students combined with all rows from enrollments.

B. Rows where both id and class match in both tables.

C. Rows where only class matches in both tables.

D. Rows where only id matches in both tables.

Solution

1. Step 1: Identify common columns

   Both tables share columns id and class.

2. Step 2: Understand NATURAL JOIN behavior

   NATURAL JOIN matches on all columns with the same names, so it joins on both id and class.

3. Final Answer:

   Rows where both id and class match in both tables. -> Option B

4. Quick Check:

   NATURAL JOIN matches all common columns [OK]

Hint: NATURAL JOIN uses all same-named columns to join [OK]

Common Mistakes:

• Assuming join on only one common column
• Confusing NATURAL JOIN with JOIN USING
• Expecting Cartesian product instead of filtered rows

4. Consider these tables:
products(id, name, price)
sales(id, product_id, quantity)
What is the problem with this query?

SELECT * FROM products NATURAL JOIN sales;

medium

A. It will return all rows without filtering.

B. It will cause a syntax error because NATURAL JOIN requires USING clause.

C. It will join on id columns, which are different keys, causing incorrect results.

D. It will join correctly on product_id automatically.

Solution

1. Step 1: Identify common columns

   Both tables have a column named id, but they represent different things.

2. Step 2: Understand NATURAL JOIN risk

   NATURAL JOIN joins on all same-named columns, so it joins on id which mismatches keys, causing wrong results.

3. Final Answer:

   It will join on id columns, which are different keys, causing incorrect results. -> Option C

4. Quick Check:

   Unintended column match = wrong join [OK]

Hint: Check if same-named columns mean same data before NATURAL JOIN [OK]

Common Mistakes:

• Assuming NATURAL JOIN always joins correctly
• Expecting NATURAL JOIN to use foreign keys automatically
• Ignoring column name conflicts causing wrong joins

5. You have two tables:
orders(order_id, customer_id, date)
customers(customer_id, name, city)
You want to join them but avoid errors from unexpected columns with the same name. Which is the safest approach?

hard

A. Use NATURAL JOIN only if you are sure about column names and their meaning.

B. Always use NATURAL JOIN for simplicity, ignoring column details.

C. Use CROSS JOIN and filter results manually.

D. Use INNER JOIN with explicit ON condition specifying join columns.

Solution

1. Step 1: Understand risks of NATURAL JOIN

   NATURAL JOIN can cause errors if tables have unintended same-named columns.

2. Step 2: Choose safer join method

   INNER JOIN with explicit ON condition avoids ambiguity by specifying exact join columns.

3. Final Answer:

   Use INNER JOIN with explicit ON condition specifying join columns. -> Option D

4. Quick Check:

   Explicit ON join = safest to avoid NATURAL JOIN risks [OK]

Hint: Use explicit ON join to avoid NATURAL JOIN surprises [OK]

Common Mistakes:

• Blindly using NATURAL JOIN without checking columns
• Using CROSS JOIN expecting filtered results
• Ignoring join conditions leads to wrong data