User, Group, Expense classes in LLD - Scalability & System Analysis

Scalability Analysis - User, Group, Expense classes

Growth Table

Scale	Users	Groups	Expenses	Key Changes
Small	100	20	500	Simple in-memory or single database instance, no caching needed
Medium	10,000	2,000	50,000	Database load increases, need read replicas and caching for frequent queries
Large	1,000,000	200,000	5,000,000	Database sharding, horizontal scaling of app servers, caching layers, async processing
Very Large	100,000,000	20,000,000	500,000,000	Multi-region deployment, advanced sharding, CDN for static data, event-driven architecture

First Bottleneck

At small scale, the database is the first bottleneck because it handles all user, group, and expense data. As users and expenses grow, the database query load and write volume increase beyond a single instance's capacity.

Scaling Solutions

• Database: Add read replicas to handle read-heavy queries like fetching user groups and expenses.
• Caching: Use in-memory caches (e.g., Redis) for frequently accessed data like user profiles and group memberships.
• Sharding: Partition the database by user ID or group ID to distribute write and read load across multiple servers.
• Horizontal Scaling: Add more application servers behind a load balancer to handle increased traffic.
• Async Processing: Use message queues for expense processing to reduce synchronous load.
• CDN: For static assets related to users or groups, use CDN to reduce bandwidth and latency.

Cost Analysis

• At 1M users, assuming each user generates 5 expense requests per day, total requests per second ~ 60 (5M requests/day ÷ 86400 seconds).
• Database needs to handle ~100 QPS for reads and writes combined, requiring multiple replicas and sharding.
• Storage: Each expense record ~1 KB, so 5M expenses ~5 GB storage, manageable but grows linearly.
• Network bandwidth: Assuming 1 KB per request, 60 QPS ~ 60 KB/s, low but grows with user base.

Interview Tip

Start by identifying key entities (User, Group, Expense) and their relationships. Discuss expected load and data growth. Identify the first bottleneck (usually database). Propose scaling solutions step-by-step: caching, read replicas, sharding, horizontal scaling. Mention trade-offs and monitoring.

Self Check

Your database handles 1000 QPS. Traffic grows 10x to 10,000 QPS. What do you do first?

Answer: Add read replicas to distribute read load and implement caching for frequent queries. Then consider sharding the database to handle increased write volume.

Key Result

The database is the first bottleneck as users and expenses grow; scaling requires caching, read replicas, and sharding combined with horizontal app server scaling.

Practice

1. Which class is primarily responsible for storing information about individual people in a shared expense system?

easy

A. Payment

B. User

C. Expense

D. Group

Solution

1. Step 1: Understand the role of each class

   User class represents individual people, Group holds multiple users, Expense tracks costs.

2. Step 2: Identify which class stores individual info

   User class stores personal details like name and ID for each person.

3. Final Answer:

   User -> Option B

4. Quick Check:

   User = Individual person [OK]

Hint: User class = individual person info [OK]

Common Mistakes:

• Confusing Group with User
• Thinking Expense stores user details
• Assuming Payment is a class here

2. Which of the following is the correct way to define a Group class that holds multiple User objects in Python?

easy

A. class Group:
def __init__(self):
self.users = []

B. class Group:
def __init__(self):
self.user = {}

C. class Group:
def __init__(self):
self.expenses = []

D. class Group:
def __init__(self):
self.members = None

Solution

1. Step 1: Identify correct attribute for multiple users

   A list is suitable to hold multiple User objects, so self.users = [] is correct.

2. Step 2: Check other options for correctness

   class Group: def __init__(self): self.user = {} uses a dict named user which is not typical for holding users; class Group: def __init__(self): self.expenses = [] uses expenses which belongs to Expense class; class Group: def __init__(self): self.members = None sets members to None which is not a collection.

3. Final Answer:

   class Group: def __init__(self): self.users = [] -> Option A

4. Quick Check:

   Group holds list of users = self.users = [] [OK]

Hint: Group holds list of users with self.users = [] [OK]

Common Mistakes:

• Using dict instead of list for users
• Confusing expenses with users
• Initializing members as None instead of a list

3. Given the following code snippet, what will be the output?

class Expense:
    def __init__(self, amount, paid_by, split_between):
        self.amount = amount
        self.paid_by = paid_by
        self.split_between = split_between

    def split_amount(self):
        return self.amount / len(self.split_between)

expense = Expense(120, 'Alice', ['Alice', 'Bob', 'Charlie'])
print(expense.split_amount())

medium

A. Error

B. 60

C. 120

D. 40.0

Solution

1. Step 1: Understand the split_amount method

   It divides total amount by number of people in split_between list.

2. Step 2: Calculate the split

   Amount = 120, split_between has 3 people, so 120 / 3 = 40.0.

3. Final Answer:

   40.0 -> Option D

4. Quick Check:

   120 divided by 3 = 40.0 [OK]

Hint: Divide amount by count of split_between list [OK]

Common Mistakes:

• Forgetting to divide by number of people
• Dividing by 2 instead of 3
• Assuming paid_by affects split amount

4. Identify the bug in this Expense class method that calculates each user's share:

class Expense:
    def __init__(self, amount, paid_by, split_between):
        self.amount = amount
        self.paid_by = paid_by
        self.split_between = split_between

    def split_amount(self):
        return self.amount // len(self.split_between)

medium

A. Using integer division (//) may lose cents in split

B. split_between should be a dictionary, not a list

C. paid_by should be a list, not a single user

D. amount should be a string, not a number

Solution

1. Step 1: Analyze the division operator used

   The method uses integer division (//) which truncates decimals.

2. Step 2: Understand impact on money split

   Using // can lose fractional cents, causing inaccurate splits.

3. Final Answer:

   Using integer division (//) may lose cents in split -> Option A

4. Quick Check:

   Integer division truncates decimals, causing loss [OK]

Hint: Use float division (/) for accurate money splits [OK]

Common Mistakes:

• Ignoring decimal loss from integer division
• Confusing data types for paid_by or split_between
• Thinking amount should be string

5. You want to design a system where multiple users in a group can add expenses, and the system automatically calculates how much each user owes or is owed. Which design approach best supports scalability and clear responsibility?

hard

A. Make User class handle all expense calculations and group management to centralize logic

B. Use only a single Expense class that stores all users and groups inside it to simplify design

C. Create User, Group, and Expense classes where Group manages users and expenses; Expense tracks amount and split; User tracks individual balances updated by Group

D. Store all data in a flat file and calculate splits manually each time without classes

Solution

1. Step 1: Identify responsibilities for each class

   User holds personal info and balances, Group manages users and expenses, Expense tracks costs and splits.

2. Step 2: Evaluate design for scalability and clarity

   Create User, Group, and Expense classes where Group manages users and expenses; Expense tracks amount and split; User tracks individual balances updated by Group cleanly separates concerns, making it easier to maintain and scale.

3. Final Answer:

   Create User, Group, and Expense classes where Group manages users and expenses; Expense tracks amount and split; User tracks individual balances updated by Group -> Option C

4. Quick Check:

   Clear class roles = scalable design [OK]

Hint: Separate concerns: User, Group, Expense each handle distinct roles [OK]

Common Mistakes:

• Putting all logic in one class
• Ignoring separation of concerns
• Using flat files for complex data