March 20, 2022 6:00 PM PDT
This document summarizes the discussion from a mock system design interview focused on creating an in-memory key-value store. The interview covered functional and non-functional requirements, system design considerations, and specific technical challenges related to memory management, data consistency, and scaling.
Requirements
Functional Requirements
- Store key-value pairs
- Implement expiry without causing memory crashes
- Support key sizes in megabytes
Non-Functional Requirements
- Initial scaling with a single server
- High availability
- Low latency
- High throughput
- Optional consistency
- Optional security
System Design
External APIs
- get(key)
- put(key, value, TTL)
System Design Considerations
- Utilize a hash table for storage.
- Each key is processed through a hash function to generate a hash code.
- The hash code maps to a storage address in memory.
Memory Management
- Allocate memory for storing key-value pairs.
- Use a list in memory with a size determined by the hash code modulo the list size.
- Address hash collisions by changing the hash function or comparing keys.
Scaling the Design
- To scale beyond a single node, partition data across multiple cache nodes.
- Use consistent hashing to determine the node location on a hash ring.
- Address hotspots by implementing virtual nodes for even distribution and adding replicas for read-heavy scenarios.
Consistency and Replication
- Implement a master-follower cluster for data replication.
- Use a two-phase commit protocol to ensure consistency between master and followers.
- Monitor node health using heartbeat and timeout mechanisms.
Expiry Implementation
- Implement a background process to check and manage TTL for key-value pairs.
Data Structure Organization
- Segment large keys and utilize a Merkle Tree for efficient hashing.
- The Merkle Tree structure allows for verification of data integrity through root hash codes.
Interviewer and Audience Feedback
Interviewer Insights
- The candidate did not demonstrate sufficient knowledge of the internals of hash tables.
- There was a lack of emphasis on consistent hashing and memory management strategies.
- The candidate's approach was more high-level, lacking depth in lower-level design considerations.
Audience Insights
- Emphasized the importance of understanding hash table structures and collision resolution.
- Suggested the need for knowledge of slab memory management and memory preallocation strategies.
- Discussed the implications of multi-threading in handling larger key-value stores and the importance of read-write locks.
Key Takeaways for Candidates
- Understand the basic structure of hash tables and how to resolve collisions.
- Be able to write pseudo code for storing key-value pairs.
- Familiarize yourself with slab memory management and memory allocation strategies.
- Know how to implement expiration mechanisms and manage data consistency in distributed systems.
- Be prepared to discuss the implications of multi-threading and locking mechanisms in system design.