Explain Consistent Hashing
Explain the concept of Consistent Hashing, its purpose in distributed systems, and how it minimizes data movement during scaling (node addition/removal).
Why Interviewers Ask This
Stripe interviewers ask this to evaluate your ability to design scalable, fault-tolerant distributed systems. They specifically want to see if you understand how to minimize data migration during cluster scaling while maintaining high availability and low latency for payment processing workloads.
How to Answer This Question
1. Define the problem: Start by explaining why standard modulo hashing fails when nodes change, causing massive data reshuffling.
2. Introduce the solution: Describe Consistent Hashing as a ring-based topology where both keys and nodes map to points on a circle using a hash function.
3. Explain the mechanism: Detail how data is stored on the next node clockwise from its hash position.
4. Discuss scaling dynamics: Clearly articulate that adding or removing a node only affects keys between that node and its predecessor, leaving the rest of the cluster untouched.
5. Address edge cases: Mention virtual nodes (vnodes) to handle uneven distribution and ensure load balancing across the ring.
Key Points to Cover
- Standard modulo hashing causes O(N) data movement when scaling, whereas consistent hashing limits movement to O(1/N).
- The concept relies on mapping keys and nodes to a logical ring using a deterministic hash function.
- Data placement follows a clockwise rule, assigning a key to the first node found after its hash value.
- Virtual nodes are essential to mitigate data skew and ensure even load distribution across the cluster.
- The primary benefit is minimal data redistribution during node addition or removal, ensuring high availability.
Sample Answer
Consistent Hashing is a distributed hashing scheme designed to solve the scalability issues inherent in standard modulo hashing. In traditional approaches, if we have N nodes, a key hashes to i = hash(key) % N. If we add…
Common Mistakes to Avoid
- Focusing only on the definition without explaining the specific advantage over modulo hashing regarding data migration costs.
- Forgetting to mention virtual nodes, which leads to an incomplete understanding of how real-world systems handle load balancing.
- Confusing the direction of data assignment (clockwise vs counter-clockwise) which can lead to logic errors in implementation scenarios.
- Neglecting to discuss failure handling, specifically how the system redistributes data when a node goes offline.
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