Memento pattern in LLD - Scalability & System Analysis

Scalability Analysis - Memento pattern

Growth Table: Memento Pattern Scaling

Users / Operations	100	10,000	1,000,000	100,000,000
Number of saved states (mementos)	~100-1,000	~10,000-100,000	~1M-10M	~100M+
Memory/storage usage	Low (MBs)	Moderate (GBs)	High (TBs)	Very High (PBs)
Access latency for restore	Instant	Milliseconds	Seconds	Minutes or more
System complexity	Simple	Moderate (needs indexing)	High (sharding, archiving)	Very High (distributed storage)
Backup and archival needs	Minimal	Required	Critical	Essential with tiered storage

First Bottleneck

The first bottleneck is the storage and memory required to keep all mementos. Each saved state can be large, and as users or operations grow, storing all snapshots becomes expensive and slow. This affects both the system's memory and disk usage, and slows down retrieval times.

Scaling Solutions

• Compression: Compress mementos to reduce storage size.
• Incremental snapshots: Save only changes (deltas) instead of full states.
• Archival storage: Move old mementos to slower, cheaper storage.
• Sharding: Distribute mementos across multiple storage nodes.
• Cache recent states: Keep only recent mementos in fast memory for quick access.
• Limit history depth: Restrict how many states are saved per user or object.

Back-of-Envelope Cost Analysis

Assuming each memento is ~100 KB:

• At 10,000 mementos: ~1 GB storage needed.
• At 1,000,000 mementos: ~1000 GB (1 TB) storage needed.
• At 100,000,000 mementos: ~10 TB storage needed.

Requests per second depend on how often users save or restore states. For 1,000 concurrent users saving every 10 seconds, ~100 QPS write load.

Bandwidth depends on memento size and frequency. For 100 QPS at 100 KB each, ~10 MB/s bandwidth needed.

Interview Tip

Start by explaining what the Memento pattern does: saving and restoring object states. Then discuss how storing many states can grow storage and memory needs. Identify storage as the first bottleneck. Suggest practical solutions like compression, incremental snapshots, and archival. Finally, mention trade-offs like limiting history depth to balance performance and resource use.

Self Check

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

Answer: Implement caching and compression to reduce load, then add horizontal scaling with sharded storage to distribute the increased write traffic.

Key Result

The Memento pattern scales well at small user counts but quickly hits storage and memory bottlenecks as saved states grow. Efficient storage techniques and distribution are key to scaling.

Practice

1. What is the main purpose of the Memento pattern in system design?

easy

A. To create multiple instances of an object efficiently

B. To convert one interface to another compatible interface

C. To manage concurrent access to shared resources

D. To save and restore an object's state without exposing its internal details

Solution

1. Step 1: Understand the role of Memento pattern

   The Memento pattern is designed to capture and externalize an object's internal state so that it can be restored later without exposing the object's implementation details.

2. Step 2: Compare with other design patterns

   Other options describe different patterns: A is about object creation (Factory), C is about synchronization (Mutex), D is about interface compatibility (Adapter).

3. Final Answer:

   To save and restore an object's state without exposing its internal details -> Option D

4. Quick Check:

   Memento = Save & Restore State [OK]

Hint: Memento = save state secretly, no details shown [OK]

Common Mistakes:

• Confusing Memento with Factory or Adapter patterns
• Thinking it manages concurrency
• Assuming it changes object interfaces

2. Which of the following correctly represents the key components of the Memento pattern?

easy

A. Subject, Observer, ConcreteObserver

B. Originator, Memento, Caretaker

C. Client, Proxy, RealSubject

D. Component, Decorator, ConcreteComponent

Solution

1. Step 1: Identify components of Memento pattern

   The Memento pattern consists of three main parts: Originator (the object whose state is saved), Memento (the object storing the state), and Caretaker (manages mementos).

2. Step 2: Eliminate other patterns

   Options B, C, and D correspond to Observer, Proxy, and Decorator patterns respectively, which are unrelated to Memento.

3. Final Answer:

   Originator, Memento, Caretaker -> Option B

4. Quick Check:

   Components = Originator + Memento + Caretaker [OK]

Hint: Remember 3 parts: Originator, Memento, Caretaker [OK]

Common Mistakes:

• Mixing Memento components with Observer or Proxy
• Forgetting the Caretaker role
• Confusing Memento with Decorator pattern

3. Consider this simplified Python code using the Memento pattern:

class Memento:
    def __init__(self, state):
        self._state = state

class Originator:
    def __init__(self):
        self._state = ""
    def set_state(self, state):
        self._state = state
    def save(self):
        return Memento(self._state)
    def restore(self, memento):
        self._state = memento._state

originator = Originator()
originator.set_state("State1")
memento = originator.save()
originator.set_state("State2")
originator.restore(memento)
print(originator._state)

What will be printed?

medium

A. None

B. State2

C. State1

D. Error

Solution

1. Step 1: Trace state changes in Originator

   Initially, Originator's state is set to "State1". Then a Memento is saved capturing "State1". Next, state changes to "State2".

2. Step 2: Restore state from Memento

   Calling restore with the saved Memento sets the state back to "State1". The print statement outputs the restored state.

3. Final Answer:

   State1 -> Option C

4. Quick Check:

   Restore resets state to saved value [OK]

Hint: Restore sets state back to saved snapshot [OK]

Common Mistakes:

• Assuming print shows latest state before restore
• Confusing save and restore methods
• Expecting error due to private variable access

4. In the following code snippet, what is the main issue that breaks the Memento pattern?

class Originator:
    def __init__(self):
        self._state = ""
    def set_state(self, state):
        self._state = state
    def save(self):
        return self._state  # returns state directly
    def restore(self, memento):
        self._state = memento

originator = Originator()
originator.set_state("State1")
memento = originator.save()
originator.set_state("State2")
originator.restore(memento)
print(originator._state)

medium

A. The save method returns state directly, exposing internal details

B. The restore method does not update the state

C. The Originator class lacks a Memento class

D. The set_state method is missing

Solution

1. Step 1: Analyze the save method

   The save method returns the internal state directly instead of encapsulating it in a Memento object, exposing internal details.

2. Step 2: Understand Memento pattern principle

   The pattern requires hiding the internal state inside a Memento object to prevent external access. Returning raw state breaks encapsulation.

3. Final Answer:

   The save method returns state directly, exposing internal details -> Option A

4. Quick Check:

   Save must hide state in Memento [OK]

Hint: Save must return Memento, not raw state [OK]

Common Mistakes:

• Thinking restore method is faulty
• Believing Memento class is mandatory in code
• Ignoring encapsulation principle

5. You are designing a text editor with undo functionality using the Memento pattern. Which approach best balances memory usage and undo capability?

hard

A. Store a Memento only after significant changes or at checkpoints

B. Store a Memento after every single character change

C. Store all changes as raw text snapshots without Memento objects

D. Do not store any state; rely on user to retype

Solution

1. Step 1: Consider memory and undo tradeoff

   Storing a Memento after every character change (Store a Memento after every single character change) uses excessive memory and is inefficient.

2. Step 2: Evaluate checkpoint strategy

   Storing Mementos after significant changes or checkpoints (Store a Memento only after significant changes or at checkpoints) reduces memory use while allowing meaningful undo steps.

3. Step 3: Assess other options

   Store all changes as raw text snapshots without Memento objects wastes memory by storing raw snapshots without encapsulation; Do not store any state; rely on user to retype removes undo capability.

4. Final Answer:

   Store a Memento only after significant changes or at checkpoints -> Option A

5. Quick Check:

   Checkpoint Mementos balance memory and undo [OK]

Hint: Save states at checkpoints, not every keystroke [OK]

Common Mistakes:

• Saving state too frequently causing memory bloat
• Ignoring encapsulation by storing raw snapshots
• Not implementing undo at all