Horizontal vs vertical partitioning in HLD - Practice Questions

Challenge - 5 Problems

🧠 Conceptual

intermediate

Understanding Horizontal Partitioning

Which of the following best describes horizontal partitioning in database design?

A Dividing a table into multiple tables each containing a subset of columns

B Merging multiple tables into one large table to improve query speed

C Creating a backup of the entire database on multiple servers

D Splitting a table into multiple tables each containing a subset of rows based on a key

💡 Hint

Think about dividing data by rows rather than columns.

Horizontal partitioning splits data by rows, distributing subsets of records across tables or servers.

🧠 Conceptual

intermediate

Understanding Vertical Partitioning

Which option correctly explains vertical partitioning in database systems?

A Combining multiple tables into one to reduce joins

B Splitting a table into smaller tables each containing a subset of columns

C Creating multiple copies of the same table for redundancy

D Distributing rows of a table across multiple servers

💡 Hint

Focus on dividing data by columns instead of rows.

Vertical partitioning divides a table by columns, storing different columns in separate tables.

❓ scaling

advanced

Choosing Partitioning for Large User Data

You have a user database with millions of records and many columns. You want to improve query speed for user profile info and reduce server load. Which partitioning strategy is best?

A Vertical partitioning by splitting frequently accessed profile columns from less used columns

B No partitioning, keep all data in one table for simplicity

C Horizontal partitioning by user region to distribute rows across servers

D Create multiple full copies of the user table on different servers

💡 Hint

Consider which data is accessed most often and how to reduce data scanned per query.

Vertical partitioning helps by separating frequently accessed columns, reducing data scanned and improving query speed.

❓ tradeoff

advanced

Tradeoffs Between Horizontal and Vertical Partitioning

Which statement correctly describes a tradeoff when choosing between horizontal and vertical partitioning?

A Vertical partitioning eliminates the need for database normalization

B Vertical partitioning reduces the number of rows but increases the number of columns in each table

C Horizontal partitioning improves write scalability but can increase complexity in queries joining multiple partitions

D Horizontal partitioning always reduces the need for indexes on tables

💡 Hint

Think about how data is split and how queries might be affected.

Horizontal partitioning splits rows, improving write scalability but may require complex joins across partitions.

❓ estimation

expert

Estimating Storage Savings with Vertical Partitioning

A table has 1 million rows and 50 columns. 10 columns are accessed frequently and 40 rarely. Each row is 1 KB total. If vertical partitioning splits the table into two tables (10 columns and 40 columns), approximately how much storage is saved when querying only the frequently accessed columns?

A About 80% storage saved per query by scanning only 10 columns

B No storage saved because all data is still stored together

C About 20% storage saved because 10 columns are smaller than 40

D About 50% storage saved because half the columns are separated

💡 Hint

Consider the proportion of columns accessed and data scanned per query.

Since 10 out of 50 columns are accessed, scanning only those saves about 80% of data scanned per query.

Practice

1. Which of the following best describes horizontal partitioning in system design?

easy

A. Combining multiple tables into one large table

B. Splitting a database table into multiple tables by columns

C. Splitting a database table into multiple tables by rows

D. Duplicating the entire database for backup

Solution

1. Step 1: Understand horizontal partitioning

   Horizontal partitioning means dividing data by rows, so each partition holds a subset of rows.

2. Step 2: Compare with other options

   Vertical partitioning splits by columns, combining tables merges data, and duplication is for backup, not partitioning.

3. Final Answer:

   Splitting a database table into multiple tables by rows -> Option C

4. Quick Check:

   Horizontal partitioning = splitting by rows [OK]

Hint: Rows split = horizontal, columns split = vertical [OK]

Common Mistakes:

• Confusing horizontal with vertical partitioning
• Thinking partitioning means duplicating data
• Mixing partitioning with database backup

2. Which syntax correctly describes vertical partitioning?

easy

A. Splitting data by rows into multiple tables

B. Splitting data by columns into multiple tables

C. Merging rows from different tables

D. Backing up the entire database

Solution

1. Step 1: Define vertical partitioning

   Vertical partitioning splits a table by columns, separating attributes into different tables.

2. Step 2: Eliminate incorrect options

   Options about rows, merging, or backup do not describe vertical partitioning.

3. Final Answer:

   Splitting data by columns into multiple tables -> Option B

4. Quick Check:

   Vertical partitioning = splitting by columns [OK]

Hint: Columns split = vertical partitioning [OK]

Common Mistakes:

• Confusing vertical with horizontal partitioning
• Assuming partitioning means merging tables
• Mixing partitioning with backup processes

3. Consider a user database table with columns: id, name, email, password, address. If we apply vertical partitioning by splitting sensitive data into a separate table, which of the following is a valid partition?

medium

A. Table 1: id, password; Table 2: name, email, address

B. Table 1: id, name; Table 2: email, password, address

C. Table 1: id, name, password; Table 2: email, address

D. Table 1: id, name, email; Table 2: id, password, address

Solution

1. Step 1: Identify sensitive data columns

   Password and address are sensitive, so they should be separated from general info.

2. Step 2: Check partitioning by columns

   Table 1: id, name, email; Table 2: id, password, address separates password and address into one table, and id, name, email into another, matching vertical partitioning.

3. Final Answer:

   Table 1: id, name, email; Table 2: id, password, address -> Option D

4. Quick Check:

   Vertical partitioning splits columns, sensitive data separated [OK]

Hint: Sensitive columns go to separate table in vertical partitioning [OK]

Common Mistakes:

• Mixing rows and columns in partitioning
• Not separating sensitive data properly
• Splitting columns unevenly without reason

4. A system uses horizontal partitioning by user region but experiences slow queries on user emails. What is the likely cause and fix?

medium

A. Cause: Partitioning by rows only; Fix: Add vertical partitioning to separate email column

B. Cause: Partitioning by columns only; Fix: Add horizontal partitioning by region

C. Cause: No partitioning; Fix: Add horizontal partitioning by email

D. Cause: Too many partitions; Fix: Merge all partitions into one

Solution

1. Step 1: Analyze the problem

   Horizontal partitioning splits by rows (region), but email queries are slow because email column is not separated.

2. Step 2: Suggest fix

   Adding vertical partitioning to separate email column improves query speed on emails.

3. Final Answer:

   Cause: Partitioning by rows only; Fix: Add vertical partitioning to separate email column -> Option A

4. Quick Check:

   Slow email queries fixed by vertical partitioning [OK]

Hint: Slow column queries? Add vertical partitioning [OK]

Common Mistakes:

• Confusing cause with partition type
• Suggesting wrong partitioning fix
• Ignoring query patterns in design

5. You design a large e-commerce database with millions of orders. You want to improve performance by splitting data. Which approach is best and why?

hard

A. Use horizontal partitioning by customer ID and vertical partitioning by payment info for balanced load

B. Use vertical partitioning by splitting order details and customer info into separate tables to reduce row size

C. Use no partitioning and rely on caching for performance

D. Use horizontal partitioning by order date to distribute rows across servers, improving query speed on recent orders

Solution

1. Step 1: Understand data and query patterns

   Orders have many rows and columns; splitting by customer ID (horizontal) balances load; splitting payment info (vertical) reduces row size.

2. Step 2: Evaluate options

   Use horizontal partitioning by customer ID and vertical partitioning by payment info for balanced load combines horizontal and vertical partitioning for scalability and performance, better than single approach or no partitioning.

3. Final Answer:

   Use horizontal partitioning by customer ID and vertical partitioning by payment info for balanced load -> Option A

4. Quick Check:

   Combine horizontal and vertical partitioning for large data [OK]

Hint: Combine horizontal and vertical for big, complex data [OK]

Common Mistakes:

• Using only one partitioning type for complex data
• Ignoring query patterns and data distribution
• Relying solely on caching without partitioning