Compute Top-K word frequencies under a path
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Compute Top-K word frequencies under a path evaluates algorithm design, data structures, correctness, complexity, edge cases, and implementation details in a realistic interview setting. A strong answer states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.
Given a filesystem path that may contain nested subdirectories and files, compute the top K most frequent words across all files. Describe an in-memory solution and its complexity. Follow-up: when the corpus is too large to fit in memory, propose scalable approaches (e.g., external sorting/partitioning, MapReduce-style sharding and merge) and an approximate heavy-hitters approach (e.g., Count–Min Sketch with Space-Saving), including accuracy/latency/storage trade-offs.
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