Design a distributed tree node counter
Distributed Tree Node Count with Two Messages
You are given an N-ary tree of machines (one process per node). Each node knows its parent (if any) and its list of children. Nodes communicate via asynchronous message passing.
Goal: Design the per-node logic so that when any node initiates a count, exactly two message types (REQUEST_COUNT and REPLY_COUNT) are used to compute the total number of nodes in the entire tree and return it to the initiator. Each node must contribute exactly once; no double counting; protect critical sections.
Assume the runtime invokes call(Node from, Message message) on a node upon message arrival, and the initiator can trigger the protocol locally (e.g., startCount()).
Specify:
(a) Message format and fields.
(b) Per-node state you maintain.
(c) How a node propagates requests to neighbors (parent/children) and aggregates replies.
(d) How you prevent duplicate propagation when a node receives multiple requests for the same traversal.
(e) How the initiator detects termination and returns the global count.
(f) Assumptions about concurrency and delivery (e.g., out-of-order messages, at-most-once vs. at-least-once) and the time/message complexity of your approach.
Constraints & Assumptions
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Preserve the scope, facts, inputs, and requested outputs from the prompt above.
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If the prompt leaves a detail unspecified, state a reasonable assumption before relying on it.
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Keep the answer interview-ready: concise enough to present, but concrete enough to implement or evaluate.
Clarifying Questions to Ask
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Clarify users, core use cases, read/write patterns, scale, latency, availability, and data retention.
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State explicit assumptions before making sizing or architecture decisions.
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Prioritize the functional path first, then address reliability, security, observability, and rollout.
What a Strong Answer Covers
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A scoped requirements summary with concrete non-goals and success metrics.
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API, data model, architecture, consistency, capacity, and operations.
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Reasoned trade-offs among simple and scalable designs, including bottlenecks and failure modes.
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A validation, monitoring, migration, and launch plan appropriate for the risk level.
Follow-up Questions
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What breaks first at 10x traffic or data volume?
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How would you degrade gracefully during dependency failures?
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What metrics and alerts would prove the design is healthy after launch?