← Warner Bros Discovery Interview Insights
Start by clarifying requirements: file size, memory constraints, keyword matching rules (case sensitivity, whole word), and output format. For a single keyword, stream the file line by line, tracking line numbers and character offsets, using an efficient string search like KMP or built-in find. For multiple keywords, build an Aho-Corasick automaton to scan the file in one pass, recording all matches with their positions.
Pro tip: Mention that you would first ask about the expected file size and memory limits—this shows you think about real-world constraints and can choose between in-memory and streaming approaches. Also, discuss trade-offs between simplicity (regex) and performance (Aho-Corasick) for multiple keywords.
Ask about file size, memory limits, keyword matching rules (case sensitivity, whole word, overlapping matches), and output format (line numbers, character positions). This ensures you design the right solution.
Propose a streaming approach: read the file line by line, maintain a global character offset, and for each line, use an efficient substring search (e.g., KMP or built-in find) to locate all occurrences, recording line number and absolute character position.
Introduce Aho-Corasick automaton: build a trie of all keywords with failure links, then scan the text in one pass, reporting all matches. This avoids rescanning the file for each keyword.
Compare approaches: naive multiple searches O(k*n) vs. Aho-Corasick O(n + m + z) where n is text length, m total pattern length, z number of matches. Discuss memory vs. speed, and when simpler approaches suffice.
Address overlapping matches, case insensitivity, very large files (external sorting or chunking), and potential memory issues. Mention using memory-mapped files or parallel processing if needed.
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