Design trending queries ranking system

You are designing a system to power the **Top Trending Queries** section on the home page of an AI search/Q&A platform (similar to Perplexity). The product shows a list of trending user queries (search prompts) to visitors. Initially this list can be global, but over time you may want to **personalize** it (e.g., by country, language, or user interests). **Requirements and goals**: - Continuously identify queries that are "trending" (rising in popularity) in near real time. - Rank top K trending queries for the **home page**. - Support: - Global trending queries. - Trending queries per region or segment (e.g., country, language, topic). - Eventually allow **personalization**: show trending queries that are more relevant to a specific user or user segment. - Handle very high query volume (e.g., tens of thousands of QPS). - Keep results fresh (updated within a few seconds to a few minutes). **Design task**: Describe how you would design this trending queries system, including: 1. How you collect and process raw query events. 2. How you define and compute "trending" (not just absolute popularity but spikes/velocity). 3. The data architecture for real-time or near-real-time aggregation (streaming vs batch). 4. How you store and serve the top K trending queries globally and by segment. 5. How you might add personalization over time (per user or per user group). 6. Key metrics, scaling considerations, and how to handle spam/abuse. You do not need to provide code, but you should describe main components, data flows, and algorithms or approximations (e.g., for top-K) that you would use.