Scalable Proximity-Based Discovery System

Design a Proximity-Based Discovery System (Yelp)

Design a highly available and scalable system like Yelp that allows users to search for local businesses based on geographical location, category, and keyword. The system must support millions of businesses and high-frequency read traffic. Key requirements include efficient spatial indexing for low-latency search (<200ms), a mechanism for posting and aggregating reviews, and handling high-volume photo uploads. Address the trade-offs between search accuracy and system performance, and explain how you would handle varying business densities across different geographic regions.
PostgreSQLPostGISRedisKafkaS3CDNGeohashCassandraKubernetesElasticsearch
01
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Design a Proximity-Based Discovery Service

Design a high-scale system similar to Yelp or Google Maps Places that allows users to discover businesses 'near me'. The system must support searching millions of businesses with sub-second latency, handling high-volume user reviews, and scaling to tens of thousands of requests per second. Explain your strategy for spatial indexing, how you handle data consistency between search results and reviews, and your approach to sharding a global geographical dataset.
PostgreSQLPostGISRedisKafkaNoSQLGeohashCDNAPI Gateway
00
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Scalable Proximity-Based Discovery System

Design a local discovery and review platform similar to Yelp. The system must support searching for millions of businesses based on real-time geographic location, viewing rich business profiles, and handling high-concurrency user reviews. Focus on the geospatial indexing strategy, data consistency for business ratings, and how to scale the system for global traffic with low-latency search results.
PostgreSQLPostGISRedisKafkaGeohashS2 GeometryCDNKubernetesMicroservices
00
Read
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