Consistent Hashing medium
In a multi-region Cassandra setup using Consistent Hashing, how does the ring topology typically work?
- A Each physical data center maintains its own independent, isolated ring that is logically invisible to nodes in other regions.
- B There is typically one global ring comprising all nodes, with a specific 'Replication Strategy' used to ensure cross-region safety.
- C Rings are fundamentally incompatible with multi-region deployments and are replaced by a hierarchical consensus tree.
- D The ring topology only exists within the designated 'Primary' region, while 'Secondary' regions utilize simple round-robin routing.
Answer: B. There is typically one global ring comprising all nodes, with a specific 'Replication Strategy' used to ensure cross-region safety.
In multi-region setups (like Cassandra), all nodes from all data centers usually belong to the same global ring. The key is in the 'Placement Strategy'. Instead of just picking the next N nodes on the ring, the system 'walks' the ring until it has identified the required number of replicas for each specific data center. This ensures that a copy exists in US-East even if the key initially hashes to a node in EU-West.
One system design question a day, with spaced repetition so the ones you miss come back.
Get the appRelated questions
- In a 'Smart Client' architecture (e.g., modern Cassandra drivers), how does the client find the right node?
- When a new node (Node X) joins the ring, where does it acquire its initial data from?
- Google's Maglev hashing algorithm (used in their Network Load Balancers) differs from standard Consistent Hashing rings. How does it generate the lookup table?
- Virtual Nodes improve balance but increase metadata size (Memory). How does 'Multi-Probe Consistent Hashing' achieve good balance without VNodes?
- In the Chord DHT protocol (a P2P consistent hashing implementation), naive lookups are O(N). How does Chord optimize this to O(log N)?
- Which of these systems is a famous user of Consistent Hashing?