Partitioning best practices in PostgreSQL - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to create a partitioned table by range on the column 'created_date'.

PostgreSQL

CREATE TABLE orders (id SERIAL PRIMARY KEY, created_date DATE, amount NUMERIC) PARTITION BY [1] (created_date);

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

Arange

Blist

Chash

Dcolumn

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'list' instead of 'range' for date ranges.

Using 'hash' which is for distributing data evenly but not by ranges.

The range partitioning method is used to divide data based on ranges of values, such as dates.

2fill in blank

medium

Complete the code to create a partition for the 'orders' table for dates before 2023-01-01.

PostgreSQL

CREATE TABLE orders_2022 PARTITION OF orders FOR VALUES [1] ('2023-01-01');

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AFROM

BBEFORE

CTO

DIN

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'FROM' instead of 'TO' for the upper bound.

Using 'IN' which is for list partitions.

The TO keyword defines the upper bound for a range partition.

3fill in blank

hard

Fix the error in the partition creation statement by choosing the correct partition method.

PostgreSQL

CREATE TABLE sales PARTITION BY [1] (region);

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

Alist

Brange

Chash

Dpartition

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'range' for categorical data like regions.

Using invalid partition method names.

The list partitioning method is used to divide data by discrete values like regions.

4fill in blank

hard

Fill both blanks to create a hash partitioned table with 4 partitions.

PostgreSQL

CREATE TABLE logs (id SERIAL, event_time TIMESTAMP) PARTITION BY [1] (id);

CREATE TABLE logs_part_1 PARTITION OF logs FOR VALUES WITH ([2] 4, REMAINDER 0);

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Ahash

Blist

CMODULUS

DRANGE

Attempts:

3 left

💡 Hint

Common Mistakes

Using RANGE or LIST keywords with hash partitioning.

Mixing partition methods and partition value clauses.

Hash partitioning uses the MODULUS keyword to specify partitions based on hash values.

5fill in blank

hard

Fill all three blanks to create a range partition for the 'events' table for dates from 2023-01-01 to 2023-06-30.

PostgreSQL

CREATE TABLE events (id SERIAL, event_date DATE) PARTITION BY [1] (event_date);

CREATE TABLE events_h1_2023 PARTITION OF events FOR VALUES FROM ([2]) TO ([3]);

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

Arange

B'2023-01-01'

C'2023-06-30'

Dlist

Attempts:

3 left

💡 Hint

Common Mistakes

Using list partitioning instead of range.

Forgetting quotes around date literals.

Range partitioning uses FROM and TO with date values to define partitions.

Practice

1. What is the main benefit of using table partitioning in PostgreSQL?

easy

A. It breaks a large table into smaller, manageable parts to improve performance.

B. It automatically creates backups of the table data.

C. It encrypts the table data for security.

D. It merges multiple tables into one large table.

Solution

1. Step 1: Understand what partitioning does

   Partitioning divides a big table into smaller pieces called partitions.

2. Step 2: Identify the benefit of smaller parts

   Smaller parts make queries faster and data easier to manage.

3. Final Answer:

   It breaks a large table into smaller, manageable parts to improve performance. -> Option A

4. Quick Check:

   Partitioning = smaller parts for performance [OK]

Hint: Partitioning splits big tables for easier handling [OK]

Common Mistakes:

• Thinking partitioning creates backups
• Confusing partitioning with encryption
• Believing partitioning merges tables

2. Which of the following is the correct syntax to create a range partitioned table in PostgreSQL?

easy

A. CREATE TABLE sales (id INT, sale_date DATE) PARTITION BY LIST (sale_date);

B. CREATE TABLE sales PARTITION BY RANGE (sale_date) (id INT, sale_date DATE);

C. CREATE TABLE sales (id INT, sale_date DATE) PARTITION ON RANGE sale_date;

D. CREATE TABLE sales (id INT, sale_date DATE) PARTITION BY RANGE (sale_date);

Solution

1. Step 1: Recall correct partition syntax

   PostgreSQL uses PARTITION BY RANGE (column) after table columns.

2. Step 2: Check each option

   CREATE TABLE sales (id INT, sale_date DATE) PARTITION BY RANGE (sale_date); matches syntax: columns first, then PARTITION BY RANGE.

3. Final Answer:

   CREATE TABLE sales (id INT, sale_date DATE) PARTITION BY RANGE (sale_date); -> Option D

4. Quick Check:

   PARTITION BY RANGE after columns = correct syntax [OK]

Hint: Partition type follows column definitions in CREATE TABLE [OK]

Common Mistakes:

• Placing PARTITION BY before columns
• Using PARTITION ON instead of PARTITION BY
• Confusing RANGE with LIST partition type

3. Given the following partition setup:

CREATE TABLE orders (id INT, region TEXT, order_date DATE) PARTITION BY LIST (region);
CREATE TABLE orders_us PARTITION OF orders FOR VALUES IN ('US');
CREATE TABLE orders_eu PARTITION OF orders FOR VALUES IN ('EU');

What will be the result of this query?

INSERT INTO orders VALUES (1, 'US', '2024-01-01');
SELECT * FROM orders WHERE region = 'US';

medium

A. Returns the row with id 1, region 'US', and date '2024-01-01'.

B. Returns no rows because the partition is missing.

C. Causes a syntax error due to missing partition key.

D. Returns rows from all partitions regardless of region.

Solution

1. Step 1: Understand LIST partitioning by region

   Rows with region 'US' go to orders_us partition.

2. Step 2: Insert and select behavior

   Insert puts row in orders_us; select filters region='US', so row is returned.

3. Final Answer:

   Returns the row with id 1, region 'US', and date '2024-01-01'. -> Option A

4. Quick Check:

   List partition returns matching rows [OK]

Hint: Rows go to partition matching partition key value [OK]

Common Mistakes:

• Assuming insert fails without default partition
• Expecting syntax error on insert
• Thinking select ignores partition keys

4. You have this partitioned table:

CREATE TABLE logs (id SERIAL, log_date DATE) PARTITION BY RANGE (log_date);
CREATE TABLE logs_2023 PARTITION OF logs FOR VALUES FROM ('2023-01-01') TO ('2024-01-01');

Which error will occur if you run this?

INSERT INTO logs (log_date) VALUES ('2022-12-31');

medium

A. ERROR: syntax error near VALUES

B. ERROR: no partition found for row

C. The row is inserted into logs_2023 partition

D. The row is inserted into a default partition automatically

Solution

1. Step 1: Check partition ranges

   logs_2023 covers dates from 2023-01-01 to 2024-01-01 only.

2. Step 2: Insert date outside partition range

   2022-12-31 is before 2023-01-01, so no matching partition exists.

3. Final Answer:

   ERROR: no partition found for row -> Option B

4. Quick Check:

   Insert outside range = no partition error [OK]

Hint: Insert date must fit partition range or error occurs [OK]

Common Mistakes:

• Expecting automatic default partition
• Thinking syntax error occurs
• Assuming row goes to nearest partition

5. You want to optimize queries filtering by user_id and created_at date on a large table. Which partitioning strategy is best practice?

hard

A. Use HASH partitioning on created_at only.

B. Use LIST partitioning on user_id only.

C. Use RANGE partitioning on created_at and subpartition by HASH on user_id.

D. Do not partition; use a single large table with indexes.

Solution

1. Step 1: Analyze query filters

   Queries filter by user_id and created_at, so both should guide partitioning.

2. Step 2: Choose partitioning methods

   RANGE on created_at handles date ranges well; HASH subpartitioning on user_id balances data.

3. Step 3: Evaluate other options

   LIST on user_id alone is inefficient for many users; HASH on created_at is unusual; no partitioning misses benefits.

4. Final Answer:

   Use RANGE partitioning on created_at and subpartition by HASH on user_id. -> Option C

5. Quick Check:

   Combine RANGE and HASH for multi-column filtering [OK]

Hint: Combine RANGE for dates and HASH for IDs for best performance [OK]

Common Mistakes:

• Using LIST for high-cardinality user_id
• Hash partitioning on date column only
• Skipping partitioning on large tables