Design an Autocomplete/Type-Ahead Service

To design an autocomplete service for Amazon, I would first clarify that we need sub-50ms latency for millions of concurrent users searching for products. The core component should be a Trie data structure, as it allows O(k) lookup time where k is the query length, which is significantly faster than scanning a database index. Each node in the Trie would store a list of candidate words or product IDs, along with their popularity scores. However, a raw Trie consumes too much memory for billions of products. I would implement a compressed Trie or use a Radix Tree to reduce space overhead. For ranking, since customers want relevant items, not just alphabetical matches, each node would maintain a top-K list of most frequently purchased items associated with that prefix. When a user types 'lapt', the system traverses the Trie and returns the top three laptops from the pre-computed lists. To handle scale, we would shard the Trie based on the first few characters of the search term, distributing load across servers. A read-through cache layer using Redis would store results for common prefixes like 'iPh' to eliminate Trie traversal entirely for hot queries. Finally, we must consider updates; new product listings need asynchronous background jobs to update the Trie nodes without blocking user requests, ensuring the system remains responsive while staying current with inventory changes.