PARTITION BY for grouping windows in PostgreSQL - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to calculate the total sales for each department.

PostgreSQL

SELECT department, sales, SUM(sales) OVER ([1]) AS dept_total FROM sales_data;

Drag options to blanks, or click blank then click option'

APARTITION BY department ORDER BY date

BPARTITION BY department

CORDER BY department

DGROUP BY department

Attempts:

3 left

💡 Hint

Common Mistakes

Using GROUP BY inside the OVER() clause causes syntax errors.

Omitting PARTITION BY calculates the sum over the entire table, not per department.

The PARTITION BY clause groups rows by department for the window function. Here, SUM(sales) OVER (PARTITION BY department) calculates the total sales per department.

2fill in blank

medium

Complete the code to rank employees by salary within each department.

PostgreSQL

SELECT employee_id, department, salary, RANK() OVER ([1]) AS dept_rank FROM employees;

Drag options to blanks, or click blank then click option'

APARTITION BY department ORDER BY salary DESC

BGROUP BY department ORDER BY salary DESC

CPARTITION BY salary ORDER BY department

DORDER BY department, salary DESC

Attempts:

3 left

💡 Hint

Common Mistakes

Using GROUP BY inside OVER() causes errors.

Omitting ORDER BY inside OVER() results in all ranks being 1.

The PARTITION BY department ORDER BY salary DESC clause ranks employees within each department by descending salary.

3fill in blank

hard

Fix the error in the window function to calculate the average salary per department.

PostgreSQL

SELECT department, employee_id, salary, AVG(salary) OVER ([1]) AS avg_dept_salary FROM employees;

Drag options to blanks, or click blank then click option'

APARTITION BY department

BPARTITION BY department ORDER BY employee_id

CORDER BY department

DGROUP BY department

Attempts:

3 left

💡 Hint

Common Mistakes

Using GROUP BY inside OVER() causes syntax errors.

Including ORDER BY unnecessarily can change window frame behavior.

For average per department, use PARTITION BY department without ORDER BY. ORDER BY is optional and not needed here.

4fill in blank

hard

Fill both blanks to calculate the cumulative sum of sales per region ordered by date.

PostgreSQL

SELECT region, date, sales, SUM(sales) OVER ([1] [2]) AS cumulative_sales FROM sales_records;

Drag options to blanks, or click blank then click option'

APARTITION BY region

BORDER BY date

CGROUP BY region

DPARTITION BY date

Attempts:

3 left

💡 Hint

Common Mistakes

Using GROUP BY inside OVER() causes errors.

Omitting ORDER BY results in total sum, not cumulative.

Use PARTITION BY region to group sales by region and ORDER BY date to calculate cumulative sum in date order.

5fill in blank

hard

Fill all three blanks to calculate the row number partitioned by department and ordered by hire_date.

PostgreSQL

SELECT employee_id, department, hire_date, ROW_NUMBER() OVER ([1] [2]) AS row_num FROM employees WHERE salary > [3];

Drag options to blanks, or click blank then click option'

APARTITION BY department

BORDER BY hire_date

C50000

DGROUP BY department

Attempts:

3 left

💡 Hint

Common Mistakes

Using GROUP BY inside OVER() causes errors.

Putting salary filter inside OVER() is incorrect.

Use PARTITION BY department and ORDER BY hire_date inside OVER() to number rows per department by hire date. The WHERE clause filters salaries above 50000.

Practice

1. What does the PARTITION BY clause do in a window function in PostgreSQL?

easy

A. It filters rows before the window function is applied.

B. It divides the rows into groups to perform calculations within each group.

C. It sorts the entire table before applying the window function.

D. It removes duplicate rows from the result set.

Solution

1. Step 1: Understand the role of PARTITION BY

   PARTITION BY groups rows so window functions calculate results within each group separately.

2. Step 2: Differentiate from filtering and sorting

   Filtering removes rows, sorting orders rows, but PARTITION BY only groups rows without removing or sorting them globally.

3. Final Answer:

   It divides the rows into groups to perform calculations within each group. -> Option B

4. Quick Check:

   PARTITION BY = grouping rows for window functions [OK]

Hint: Remember: PARTITION BY groups rows, it does not filter or sort [OK]

Common Mistakes:

• Confusing PARTITION BY with WHERE filtering
• Thinking PARTITION BY sorts all rows
• Assuming PARTITION BY removes duplicates

2. Which of the following is the correct syntax to use PARTITION BY in a window function?

easy

A. SELECT col, SUM(value) OVER (PARTITION BY col ORDER BY date) FROM table;

B. SELECT col, SUM(value) PARTITION BY col FROM table;

C. SELECT col, SUM(value) OVER PARTITION BY col FROM table;

D. SELECT col, SUM(value) WHERE PARTITION BY col FROM table;

Solution

1. Step 1: Identify correct window function syntax

   The correct syntax uses OVER() with PARTITION BY inside parentheses.

2. Step 2: Check each option

   SELECT col, SUM(value) OVER (PARTITION BY col ORDER BY date) FROM table; correctly uses SUM(value) OVER (PARTITION BY col ORDER BY date). Others misuse PARTITION BY outside OVER or with WHERE.

3. Final Answer:

   SELECT col, SUM(value) OVER (PARTITION BY col ORDER BY date) FROM table; -> Option A

4. Quick Check:

   Window functions use OVER() with PARTITION BY inside [OK]

Hint: PARTITION BY must be inside OVER() parentheses [OK]

Common Mistakes:

• Placing PARTITION BY outside OVER()
• Using WHERE instead of PARTITION BY
• Omitting OVER() entirely

3. Given the table sales with columns region, month, and amount, what will this query return?

SELECT region, month, amount, SUM(amount) OVER (PARTITION BY region ORDER BY month) AS running_total FROM sales ORDER BY region, month;

medium

A. Monthly sales amount without any cumulative calculation.

B. Total sales amount for all regions combined.

C. An error because PARTITION BY cannot be combined with ORDER BY.

D. A running total of sales amount per region ordered by month.

Solution

1. Step 1: Understand SUM() OVER with PARTITION BY and ORDER BY

   SUM() OVER (PARTITION BY region ORDER BY month) calculates a running total per region ordered by month.

2. Step 2: Analyze the output

   Each row shows the cumulative sum of amount for that region up to the current month.

3. Final Answer:

   A running total of sales amount per region ordered by month. -> Option D

4. Quick Check:

   PARTITION BY groups, ORDER BY defines running total order [OK]

Hint: Running totals use PARTITION BY with ORDER BY inside OVER() [OK]

Common Mistakes:

• Thinking it sums all regions together
• Ignoring ORDER BY for running total
• Assuming syntax error with ORDER BY in window

4. Identify the error in this query:

SELECT employee_id, department, RANK() OVER PARTITION BY department ORDER BY salary DESC FROM employees;

medium

A. Missing parentheses around PARTITION BY and ORDER BY clauses.

B. RANK() cannot be used with PARTITION BY.

C. ORDER BY cannot be used inside window functions.

D. employee_id must be included in PARTITION BY.

Solution

1. Step 1: Check window function syntax

   Window functions require OVER() with parentheses enclosing PARTITION BY and ORDER BY.

2. Step 2: Identify missing parentheses

   The query misses parentheses after OVER, causing syntax error.

3. Final Answer:

   Missing parentheses around PARTITION BY and ORDER BY clauses. -> Option A

4. Quick Check:

   OVER() must enclose PARTITION BY and ORDER BY [OK]

Hint: Always use parentheses after OVER() for window clauses [OK]

Common Mistakes:

• Omitting parentheses after OVER
• Thinking ORDER BY is not allowed in window functions
• Assuming all columns must be in PARTITION BY

5. You want to calculate the average sales per product category and also show each sale's rank within its category by sale date. Which query correctly uses PARTITION BY to achieve this?

hard

A. SELECT product, category, sale_date, amount, AVG(amount) OVER (PARTITION BY sale_date), RANK() OVER (PARTITION BY product ORDER BY category) FROM sales;

B. SELECT product, category, sale_date, amount, AVG(amount) PARTITION BY category, RANK() PARTITION BY category ORDER BY sale_date FROM sales;

C. SELECT product, category, sale_date, amount, AVG(amount) OVER (PARTITION BY category), RANK() OVER (PARTITION BY category ORDER BY sale_date) FROM sales;

D. SELECT product, category, sale_date, amount, AVG(amount) OVER (ORDER BY category), RANK() OVER (ORDER BY sale_date) FROM sales;

Solution

1. Step 1: Use AVG() with PARTITION BY category

   AVG(amount) OVER (PARTITION BY category) calculates average sales per category.

2. Step 2: Use RANK() with PARTITION BY category ordered by sale_date

   RANK() OVER (PARTITION BY category ORDER BY sale_date) ranks sales within each category by date.

3. Step 3: Verify syntax correctness

   SELECT product, category, sale_date, amount, AVG(amount) OVER (PARTITION BY category), RANK() OVER (PARTITION BY category ORDER BY sale_date) FROM sales; uses correct OVER() syntax with PARTITION BY and ORDER BY clauses for both functions.

4. Final Answer:

   SELECT product, category, sale_date, amount, AVG(amount) OVER (PARTITION BY category), RANK() OVER (PARTITION BY category ORDER BY sale_date) FROM sales; -> Option C

5. Quick Check:

   Use PARTITION BY category inside OVER() for grouping [OK]

Hint: Use OVER(PARTITION BY category) for grouping in window functions [OK]

Common Mistakes:

• Omitting OVER() or PARTITION BY
• Mixing PARTITION BY columns incorrectly
• Using PARTITION BY without parentheses