I jumped straight into the URL frontier and crawl scheduling before even clarifying scope, which I think hurt me.
Start by clarifying requirements and scale, then outline a high-level architecture covering crawling, parsing, storage, and scheduling. Dive into key components like URL frontier, politeness, and distributed coordination, discussing trade-offs and scalability.
Pro tip: Emphasize politeness and robustness from the start—Google values systems that respect robots.txt and handle failures gracefully. Also, proactively discuss how you'd measure and monitor crawler health and coverage.
Ask questions to understand scope: expected crawl rate, content types, freshness needs, and politeness constraints. Establish scale assumptions (e.g., billions of pages) to guide design decisions.
Sketch main components: URL frontier, fetcher, parser, content store, and link extractor. Explain how they interact and data flows through the system.
Detail the URL frontier (prioritization, politeness), fetcher (distributed, rate limiting), parser (extract links, handle formats), and storage (deduplication, indexing). Discuss algorithms and data structures.
Explain how to scale horizontally, handle failures (retries, dead letter queues), and ensure fault tolerance. Discuss distributed coordination (e.g., consistent hashing, leader election).
Compare design choices (e.g., BFS vs. priority crawling, push vs. pull). Mention optimizations like caching, compression, and incremental crawling.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.