TABLESAMPLE for random sampling in PostgreSQL - Mini Project: Build & Apply

Using TABLESAMPLE for Random Sampling in PostgreSQL

📖 Scenario: You work for a bookstore that wants to analyze a small random sample of its sales data to understand customer preferences without scanning the entire large sales table.

🎯 Goal: Build a SQL query using TABLESAMPLE SYSTEM to randomly select approximately 10% of the rows from the sales table.

📋 What You'll Learn

Create a sales table with columns sale_id, book_title, and price.

Insert exactly 5 rows into the sales table with specified values.

Write a query using TABLESAMPLE SYSTEM (10) to randomly sample about 10% of the rows.

Add an ORDER BY sale_id clause to the sampling query.

💡 Why This Matters

🌍 Real World

Random sampling helps businesses analyze a manageable subset of large data quickly, saving time and resources.

💼 Career

Data analysts and database administrators often use TABLESAMPLE to perform quick exploratory data analysis on big datasets.

1

Create the sales table and insert data

Create a table called sales with columns sale_id (integer), book_title (text), and price (numeric). Then insert these exact rows: (1, 'The Hobbit', 15.99), (2, '1984', 12.50), (3, 'Dune', 18.00), (4, 'Pride and Prejudice', 9.99), (5, 'The Catcher in the Rye', 14.00).

PostgreSQL

-- Create the sales table and insert 5 rows
-- Your code here

Hint

Use CREATE TABLE to define the table and INSERT INTO with multiple rows to add data.

2

Set the sampling percentage

Create a variable or comment to indicate the sampling percentage as 10 for the TABLESAMPLE SYSTEM clause.

PostgreSQL

CREATE TABLE sales (
    sale_id INTEGER,
    book_title TEXT,
    price NUMERIC
);

INSERT INTO sales (sale_id, book_title, price) VALUES
(1, 'The Hobbit', 15.99),
(2, '1984', 12.50),
(3, 'Dune', 18.00),
(4, 'Pride and Prejudice', 9.99),
(5, 'The Catcher in the Rye', 14.00);

-- Set sampling percentage to 10
-- Your code here

Hint

Use a comment or variable to note the sampling percentage 10 for clarity.

3

Write the sampling query using TABLESAMPLE SYSTEM (10)

Write a SQL query to select all columns from sales using TABLESAMPLE SYSTEM (10) to randomly sample about 10% of the rows.

PostgreSQL

CREATE TABLE sales (
    sale_id INTEGER,
    book_title TEXT,
    price NUMERIC
);

INSERT INTO sales (sale_id, book_title, price) VALUES
(1, 'The Hobbit', 15.99),
(2, '1984', 12.50),
(3, 'Dune', 18.00),
(4, 'Pride and Prejudice', 9.99),
(5, 'The Catcher in the Rye', 14.00);

-- Sampling percentage
-- 10

SELECT * FROM sales TABLESAMPLE SYSTEM (10);
-- Your code here

Hint

Use TABLESAMPLE SYSTEM (10) right after the table name in the FROM clause.

4

Add ORDER BY sale_id to the sampling query

Modify the sampling query to add ORDER BY sale_id at the end to sort the sampled rows by sale_id.

PostgreSQL

CREATE TABLE sales (
    sale_id INTEGER,
    book_title TEXT,
    price NUMERIC
);

INSERT INTO sales (sale_id, book_title, price) VALUES
(1, 'The Hobbit', 15.99),
(2, '1984', 12.50),
(3, 'Dune', 18.00),
(4, 'Pride and Prejudice', 9.99),
(5, 'The Catcher in the Rye', 14.00);

-- Sampling percentage
-- 10

SELECT * FROM sales TABLESAMPLE SYSTEM (10)
ORDER BY sale_id;
-- Your code here

Hint

Add ORDER BY sale_id after the sampling clause to sort the results.

Practice

1.

What is the main purpose of using TABLESAMPLE in a PostgreSQL query?

easy

A. To retrieve a random subset of rows from a table

B. To sort the table rows in random order

C. To permanently delete random rows from a table

D. To create a backup of the table

Solution

1. Step 1: Understand the purpose of TABLESAMPLE

   TABLESAMPLE is used to get a random sample of rows from a table without scanning the entire table.

2. Step 2: Compare options with TABLESAMPLE usage

   Only To retrieve a random subset of rows from a table describes retrieving a random subset of rows, which matches TABLESAMPLE's purpose.

3. Final Answer:

   To retrieve a random subset of rows from a table -> Option A

4. Quick Check:

   TABLESAMPLE = random subset retrieval [OK]

Hint: TABLESAMPLE returns random rows, not sorting or deleting [OK]

Common Mistakes:

• Confusing TABLESAMPLE with ORDER BY RANDOM()
• Thinking TABLESAMPLE deletes rows
• Assuming TABLESAMPLE creates backups

2.

Which of the following is the correct syntax to sample approximately 10% of rows from a table named employees using the BERNOULLI method?

easy

A. SELECT * FROM employees TABLESAMPLE BERNOULLI(10);

B. SELECT * FROM employees TABLESAMPLE SYSTEM(10);

C. SELECT * FROM employees SAMPLE BERNOULLI(10);

D. SELECT * FROM employees TABLESAMPLE BERNOULLI 10;

Solution

1. Step 1: Recall correct TABLESAMPLE syntax

   The correct syntax uses TABLESAMPLE followed by the method name and percentage in parentheses.

2. Step 2: Check each option

   SELECT * FROM employees TABLESAMPLE BERNOULLI(10); matches the correct syntax exactly. SELECT * FROM employees TABLESAMPLE SYSTEM(10); uses SYSTEM instead of BERNOULLI. SELECT * FROM employees SAMPLE BERNOULLI(10); misses TABLESAMPLE keyword. SELECT * FROM employees TABLESAMPLE BERNOULLI 10; misses parentheses around 10.

3. Final Answer:

   SELECT * FROM employees TABLESAMPLE BERNOULLI(10); -> Option A

4. Quick Check:

   Correct TABLESAMPLE syntax = SELECT * FROM employees TABLESAMPLE BERNOULLI(10); [OK]

Hint: Use TABLESAMPLE METHOD(percentage) with parentheses [OK]

Common Mistakes:

• Omitting TABLESAMPLE keyword
• Using wrong method name
• Missing parentheses around percentage

3.

Given a table products with 1000 rows, what is the expected approximate number of rows returned by this query?

SELECT * FROM products TABLESAMPLE SYSTEM(5);

medium

A. Exactly 5 rows

B. About 50 rows

C. About 500 rows

D. All 1000 rows

Solution

1. Step 1: Understand SYSTEM sampling percentage

   SYSTEM(5) means approximately 5% of rows are sampled.

2. Step 2: Calculate expected rows from 1000 total

   5% of 1000 is 0.05 * 1000 = 50 rows approximately.

3. Final Answer:

   About 50 rows -> Option B

4. Quick Check:

   5% of 1000 = 50 [OK]

Hint: Percentage in TABLESAMPLE is approximate row count percent [OK]

Common Mistakes:

• Confusing percentage with exact row count
• Assuming SYSTEM returns fewer rows than BERNOULLI always
• Thinking TABLESAMPLE returns all rows

4.

Identify the error in this query that tries to sample 20% of rows using BERNOULLI:

SELECT * FROM orders TABLESAMPLE BERNOULLI 20;

medium

A. TABLESAMPLE keyword is misspelled

B. BERNOULLI method cannot be used with TABLESAMPLE

C. Percentage value must be between 0 and 1

D. Missing parentheses around the percentage value

Solution

1. Step 1: Check TABLESAMPLE BERNOULLI syntax

   The percentage must be inside parentheses, like BERNOULLI(20).

2. Step 2: Identify the error in the query

   The query misses parentheses around 20, causing syntax error.

3. Final Answer:

   Missing parentheses around the percentage value -> Option D

4. Quick Check:

   Percentage needs parentheses in TABLESAMPLE [OK]

Hint: Always put percentage in parentheses after method name [OK]

Common Mistakes:

• Omitting parentheses around percentage
• Using invalid percentage range
• Misspelling TABLESAMPLE keyword

5.

You want to quickly test a query on a large table sales but need a random sample that is more uniformly random than SYSTEM sampling. Which query is best?

Options:
A) SELECT * FROM sales TABLESAMPLE SYSTEM(10);
B) SELECT * FROM sales TABLESAMPLE BERNOULLI(10);
C) SELECT * FROM sales ORDER BY RANDOM() LIMIT 100;
D) SELECT * FROM sales TABLESAMPLE SYSTEM(100);

hard

A. Use SYSTEM sampling for speed but less randomness

B. Use ORDER BY RANDOM() for perfect randomness but slower

C. Use BERNOULLI sampling for better randomness

D. Use SYSTEM sampling with 100% to get all rows

Solution

1. Step 1: Compare randomness and speed of methods

   SYSTEM is faster but less random; BERNOULLI is slower but more uniformly random.

2. Step 2: Choose best method for uniform randomness and speed

   BERNOULLI(10) gives a good balance of randomness and reasonable speed for sampling.

3. Final Answer:

   Use BERNOULLI sampling for better randomness -> Option C

4. Quick Check:

   BERNOULLI = better randomness than SYSTEM [OK]

Hint: BERNOULLI is more random; SYSTEM is faster [OK]

Common Mistakes:

• Choosing SYSTEM when better randomness is needed
• Using ORDER BY RANDOM() on large tables (slow)
• Misunderstanding 100% SYSTEM returns all rows