NATURAL join and its risks in PostgreSQL - Step-by-Step Execution

Concept Flow - NATURAL join and its risks

Start with two tables

↓

Identify columns with same names

↓

Match rows where these columns have equal values

↓

Combine matched rows into one result row

↓

Return combined result set

↓

Beware: unintended columns matched

↓

Risk: wrong or missing data in output

NATURAL JOIN automatically matches columns with the same names in two tables and combines rows where these columns have equal values. This can cause risks if unintended columns are matched.

Execution Sample

PostgreSQL

SELECT * FROM employees NATURAL JOIN departments;

This query joins employees and departments tables by all columns with the same names, returning combined rows where those columns match.

Execution Table

Step	Action	Columns Matched	Rows Matched	Resulting Row Example
1	Identify common columns	department_id	-	-
2	Compare rows where department_id matches	department_id	employees.department_id=10 and departments.department_id=10	Combine employee and department info for department_id=10
3	Combine matched rows into one	department_id	Same as above	{employee_id: 101, name: 'Alice', department_id: 10, department_name: 'Sales'}
4	Repeat for all matching rows	department_id	Multiple rows matched	Multiple combined rows
5	Return final result set	department_id	All matched rows	All combined rows
6	Risk: If another column named 'location' exists in both tables but not intended for join	department_id, location (unintended)	Rows matched on location too	Wrong combined rows or missing data

💡 All rows matched on all common columns are combined; execution stops after processing all rows.

Variable Tracker

Variable	Start	After Step 1	After Step 2	After Step 3	Final
Common Columns	None	['department_id']	['department_id']	['department_id']	['department_id']
Matched Rows Count	0	0	3	3	3
Result Rows	Empty	Empty	Partial combined rows	Full combined rows	Full combined rows

Key Moments - 2 Insights

Why does NATURAL JOIN sometimes produce unexpected results?

Because it automatically joins on all columns with the same name, it may include columns you did not intend to join on, causing wrong or missing data as shown in execution_table step 6.

What happens if two tables have multiple columns with the same name?

NATURAL JOIN uses all those columns to match rows, so rows must match on every common column to be combined, which can reduce matched rows unexpectedly (see execution_table steps 1-4).

Visual Quiz - 3 Questions

Look at the execution_table, which column is used to match rows in the example?

A employee_id

B department_id

C name

D location

💡 Hint

Check the 'Columns Matched' column in execution_table rows 1-5.

At which step does the risk of unintended columns causing wrong results appear?

A Step 6

B Step 4

C Step 2

D Step 3

💡 Hint

Look for the step mentioning 'Risk' in the execution_table.

If the tables had no columns with the same name, what would NATURAL JOIN do?

A Return an error

B Return all rows combined without matching

C Return an empty result set

D Join on primary keys automatically

💡 Hint

Think about how NATURAL JOIN matches rows only on common columns (see concept_flow).

Concept Snapshot

NATURAL JOIN automatically joins tables on all columns with the same names.
It matches rows where these columns have equal values.
Result rows combine matched columns only once.
Risk: unintended columns with same names cause wrong matches.
Use with caution; explicit JOIN ON is safer.

Full Transcript

NATURAL JOIN in SQL automatically finds columns with the same names in two tables and joins rows where these columns have equal values. This means it combines data from both tables based on all shared column names. The execution flow starts by identifying these common columns, then matching rows where these columns are equal, and finally combining those rows into one result row. However, this automatic matching can cause risks if there are columns with the same name that you did not intend to join on. This can lead to wrong or missing data in the output. For example, if both tables have a 'location' column but you only wanted to join on 'department_id', NATURAL JOIN will still use 'location' to match rows, which may cause unexpected results. Therefore, while NATURAL JOIN can be convenient, it is safer to use explicit JOIN conditions to avoid these risks.