The anagram part wasn't too bad once I remembered the sorted-character-signature trick.
Start by clarifying requirements and constraints, then propose a solution that integrates anagram indexing with existing exact and prefix search. Discuss data structures, query processing, and trade-offs, and outline how to handle scalability and updates.
Pro tip: Mention that anagrams can be efficiently indexed by sorting the letters of each word to create a canonical key, and that this approach can be extended to support multi-word titles and partial matches. Also, discuss how to combine this with existing indexes to avoid duplication and ensure low-latency lookups.
Ask about expected query volume, latency requirements, update frequency, and whether typos are limited to anagrams or include other errors. Confirm if the anagram match should be case-insensitive and how to handle multi-word queries.
Propose building an inverted index where each word is mapped to its sorted-letter signature (e.g., 'listen' -> 'eilnst'), and store a mapping from signature to list of titles containing that word. Consider using a hash map for O(1) lookups.
Explain how to combine the anagram index with exact and prefix indexes, perhaps by using a unified query processor that checks all indexes and merges results. Discuss how to avoid duplicate results and maintain ranking.
Address how to shard the index for large datasets, use caching for frequent queries, and support dynamic updates (insertions/deletions) without significant downtime. Mention trade-offs between memory usage and query speed.
Compare the anagram index approach with alternatives like using a trie with wildcards or edit-distance automata. Highlight the efficiency of the anagram index for exact anagram matches and its limitations for other typos.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.