Asked upfront whether I should do capacity estimation.
Start by clarifying requirements and scale, then propose a high-level architecture with a distributed frontier, fetcher fleet, and storage layer. Dive into deduplication, caching, and network throughput, discussing trade-offs and potential bottlenecks at each stage.
Pro tip: Emphasize that at 10,000 machines, failure is constant, so design for graceful degradation and self-healing. Also, quantify where possible (e.g., 'At 10k machines, we might process X URLs/sec, requiring Y bandwidth') to demonstrate practical scale intuition.
Ask about crawl scope, freshness, politeness, and data volume to bound the problem. Estimate throughput and storage needs based on 10,000 machines.
Outline components: URL frontier, fetcher workers, DNS resolver, content storage, and deduplication service. Explain how they interact in a distributed setup.
Describe URL deduplication using Bloom filters or distributed hash sets, and content deduplication via hashing. Discuss distributed caching for DNS, robots.txt, and fetched content.
Address bandwidth management, connection pooling, and rate limiting per domain. Discuss how to maximize throughput while respecting robots.txt and avoiding overloading sites.
Explain how to handle machine failures, retries, and data consistency. Mention monitoring, logging, and dynamic scaling.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.