Count the number of employees per department and city.

Problem Statement

<p>Count the number of <code>employees</code> per department and city.</p>

Examples

Input: employees table: +----+---------+------------+------+ | id | name | department | city | +----+---------+------------+------+ | 1 | Alice | IT | NYC | | 2 | Bob | IT | LA | | 3 | Charlie | IT | NYC | | 4 | Dana | HR | NYC | +----+---------+------------+------+

Output: +------------+------+-----------+ | department | city | emp_count | +------------+------+-----------+ | IT | LA | 1 | | HR | NYC | 1 | | IT | NYC | 2 | +------------+------+-----------+

Explanation: The records are grouped by category and the aggregate calculation is applied to produce the summary result.

Complexity

Time Complexity: -

Space Complexity: -

Hints

💡 Hint 1: Identify the grouping dimension(s) and which columns require aggregate functions (such as COUNT, SUM, AVG, MIN, or MAX). 💡 Hint 2: Add the GROUP BY clause for all non-aggregated columns listed in the SELECT projection. 💡 Hint 3: If filtering groups, use HAVING; otherwise use WHERE before grouping: SELECT <group_col>, <AGG>(...) FROM <table> GROUP BY <group_col>;

Editorial & Approach

Problem Overview & Intuition

To solve "GROUP BY Multiple Columns", we query the relational database engine using declarative SQL. The goal is to count the number of employees per department and city. By formulating an optimal execution plan with appropriate projection and filtering, the database engine executes the query with minimal overhead.

Step-by-Step Approach

Analyze Schema: Identify the target tables, necessary foreign keys, and expected output columns.
Construct Filtering & Logic: Apply grouping & aggregates to isolate the requested data.
Format & Order: Ensure columns match the expected project schema in order.

Optimal Implementation (SQL)

SELECT department, city, COUNT(*) AS emp_count FROM employees GROUP BY department, city;

Complexity Analysis

Time Complexity O(N log N) for sorting or partitioning rows.

Space Complexity O(N) for intermediate group hash tables or window buffers.

Key Considerations & Edge Cases

Empty Tables: The query executes safely returning zero rows without syntax error.
NULL Values: Columns containing NULL values are properly handled by standard ANSI SQL semantics.
Case Sensitivity: String comparisons and keywords adhere to PostgreSQL/standard SQL rules.

GROUP BY Multiple Columns

Medium

Count the number of employees per department and city.

Example Scenarios

1Example 1

Input:

employees table

id	name	department	city
1	Alice	IT	NYC
2	Bob	IT	LA
3	Charlie	IT	NYC
4	Dana	HR	NYC

Output:

department	city	emp_count
IT	LA	1
HR	NYC	1
IT	NYC	2

Explanation:

The records are grouped by category and the aggregate calculation is applied to produce the summary result.

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