LEFT JOIN preserving all left rows in SQL - Time & Space Complexity

Time Complexity: LEFT JOIN preserving all left rows

O(n)

Understanding Time Complexity

When using a LEFT JOIN in SQL, we want to keep all rows from the left table, even if there is no matching row in the right table.

We ask: How does the time to run this query grow as the tables get bigger?

Scenario Under Consideration

Analyze the time complexity of the following SQL LEFT JOIN query.

SELECT a.id, a.name, b.order_date
FROM customers a
LEFT JOIN orders b ON a.id = b.customer_id;
    

This query returns all customers and their orders if any, keeping all customers even if they have no orders.

Identify Repeating Operations

Look for repeated work done by the database engine.

• Primary operation: For each row in the left table (customers), the database looks for matching rows in the right table (orders).
• How many times: This matching happens once per left table row, so as many times as there are customers.

How Execution Grows With Input

As the number of customers grows, the database must check more rows to find matches in orders.

Input Size (customers)	Approx. Operations
10	About 10 lookups in orders
100	About 100 lookups in orders
1000	About 1000 lookups in orders

Pattern observation: The work grows roughly in direct proportion to the number of customers.

Final Time Complexity

Time Complexity: O(n)

This means the time to run the query grows linearly with the number of rows in the left table.

Common Mistake

[X] Wrong: "The LEFT JOIN will check every row in both tables against each other, so it's quadratic time."

[OK] Correct: The database uses indexes or efficient lookups on the join column, so it doesn't scan the entire right table for each left row.

Interview Connect

Understanding how LEFT JOIN scales helps you explain query performance clearly and shows you know how databases handle joins efficiently.

Self-Check

"What if the right table has no index on the join column? How would the time complexity change?"

Practice

1. What does a LEFT JOIN do in SQL?

easy

A. Deletes rows from the left table that have no match in the right table.

B. Keeps only rows that have matches in both tables.

C. Keeps all rows from the right table and adds matching rows from the left table.

D. Keeps all rows from the left table and adds matching rows from the right table or NULL if no match.

Solution

1. Step 1: Understand LEFT JOIN behavior

   A LEFT JOIN returns all rows from the left table regardless of matches in the right table.

2. Step 2: Check what happens with unmatched rows

   If there is no matching row in the right table, the result shows NULL for right table columns.

3. Final Answer:

   Keeps all rows from the left table and adds matching rows from the right table or NULL if no match. -> Option D

4. Quick Check:

   LEFT JOIN = all left rows kept [OK]

Hint: Remember: LEFT JOIN keeps all left rows, fills right with NULL if no match [OK]

Common Mistakes:

• Confusing LEFT JOIN with INNER JOIN
• Thinking it keeps all right table rows
• Assuming unmatched rows are dropped

2. Which of the following is the correct syntax for a LEFT JOIN in SQL?

easy

A. SELECT * FROM table1 LEFT ON JOIN table2 WHERE table1.id = table2.id;

B. SELECT * FROM table1 JOIN LEFT table2 ON table1.id = table2.id;

C. SELECT * FROM table1 LEFT JOIN table2 ON table1.id = table2.id;

D. SELECT * FROM table1 LEFT JOIN table2 WHERE table1.id = table2.id;

Solution

1. Step 1: Review correct LEFT JOIN syntax

   The correct syntax is: SELECT columns FROM left_table LEFT JOIN right_table ON condition;

2. Step 2: Identify syntax errors in other options

   Options A, B, and D misuse keywords or omit ON clause, causing syntax errors.

3. Final Answer:

   SELECT * FROM table1 LEFT JOIN table2 ON table1.id = table2.id; -> Option C

4. Quick Check:

   LEFT JOIN syntax = SELECT ... LEFT JOIN ... ON ... [OK]

Hint: LEFT JOIN always uses ON to specify join condition [OK]

Common Mistakes:

• Swapping JOIN and LEFT keywords
• Using WHERE instead of ON for join condition
• Omitting ON clause

3. Given these tables:

Employees
id | name
1 | Alice
2 | Bob
3 | Carol

Sales
emp_id | amount
1 | 100
3 | 200

What is the result of:
SELECT Employees.name, Sales.amount FROM Employees LEFT JOIN Sales ON Employees.id = Sales.emp_id;

medium

A. [('Alice', 100), ('Bob', 0), ('Carol', 200)]

B. [('Alice', 100), ('Bob', NULL), ('Carol', 200)]

C. [('Alice', 100), ('Carol', 200)]

D. [('Bob', NULL)]

Solution

1. Step 1: Match Employees with Sales using LEFT JOIN

   All Employees rows appear. For matching emp_id in Sales, amount is shown; else NULL.

2. Step 2: Map each employee to sales amount or NULL

   Alice (id=1) matches 100, Bob (id=2) no match so NULL, Carol (id=3) matches 200.

3. Final Answer:

   [('Alice', 100), ('Bob', NULL), ('Carol', 200)] -> Option B

4. Quick Check:

   LEFT JOIN keeps all left rows with NULL for no match [OK]

Hint: LEFT JOIN shows NULL for unmatched right rows, not zero [OK]

Common Mistakes:

• Replacing NULL with zero
• Omitting unmatched rows
• Confusing LEFT JOIN with INNER JOIN

4. Consider this query:

SELECT a.id, b.value FROM A LEFT JOIN B ON a.id = b.a_id WHERE b.value > 10;

What is the problem with this query if you want to keep all rows from A?

medium

A. The WHERE clause filters out rows where b.value is NULL, losing some left rows.

B. The ON clause is missing a join condition.

C. LEFT JOIN should be replaced with INNER JOIN for correct results.

D. The SELECT statement is missing table aliases.

Solution

1. Step 1: Understand effect of WHERE on LEFT JOIN

   WHERE filters after join, so rows with NULL b.value are removed, losing left rows.

2. Step 2: Identify how to fix to keep all left rows

   Move condition to ON clause or use WHERE b.value > 10 OR b.value IS NULL to preserve unmatched rows.

3. Final Answer:

   The WHERE clause filters out rows where b.value is NULL, losing some left rows. -> Option A

4. Quick Check:

   WHERE after LEFT JOIN can remove unmatched rows [OK]

Hint: Put filters on right table in ON, not WHERE, to keep all left rows [OK]

Common Mistakes:

• Assuming WHERE doesn't affect LEFT JOIN results
• Confusing ON and WHERE clauses
• Replacing LEFT JOIN with INNER JOIN unnecessarily

5. You have two tables:

Products
product_id | name
1 | Pen
2 | Pencil
3 | Eraser

Sales
product_id | quantity
1 | 10
1 | 5
3 | 7

Write a query using LEFT JOIN to get each product's total sales quantity, showing 0 if no sales exist.

hard

A. SELECT p.name, COALESCE(SUM(s.quantity), 0) AS total FROM Products p LEFT JOIN Sales s ON p.product_id = s.product_id GROUP BY p.name;

B. SELECT p.name, SUM(s.quantity) AS total FROM Products p INNER JOIN Sales s ON p.product_id = s.product_id GROUP BY p.name;

C. SELECT p.name, SUM(s.quantity) AS total FROM Products p LEFT JOIN Sales s ON p.product_id = s.product_id WHERE s.quantity > 0 GROUP BY p.name;

D. SELECT p.name, SUM(s.quantity) AS total FROM Sales s LEFT JOIN Products p ON s.product_id = p.product_id GROUP BY p.name;

Solution

1. Step 1: Use LEFT JOIN to keep all products

   LEFT JOIN ensures all products appear even if no sales exist.

2. Step 2: Use COALESCE with SUM to show 0 for no sales

   SUM returns NULL if no matching rows; COALESCE converts NULL to 0.

3. Final Answer:

   SELECT p.name, COALESCE(SUM(s.quantity), 0) AS total FROM Products p LEFT JOIN Sales s ON p.product_id = s.product_id GROUP BY p.name; -> Option A

4. Quick Check:

   LEFT JOIN + COALESCE(SUM()) = total sales with zeros [OK]

Hint: Use COALESCE(SUM()) with LEFT JOIN to replace NULL totals with zero [OK]

Common Mistakes:

• Using INNER JOIN losing products with no sales
• Not handling NULL sums with COALESCE
• Filtering in WHERE removing unmatched rows