Design a Proximity Service (Yelp / Places Nearby)

1. Problem Statement & Scope

System Mission

Design a high-scale location-based proximity service allowing users to discover nearby businesses and points of interest (POI) within a given radius (e.g. 5 km) with sub-100 millisecond response times.

Functional Requirements

1. Add / Update POI: Create or update business profiles and GPS coordinates.
2. Search Nearby POIs: Query nearby businesses given user GPS coordinates and radius.
3. Filter & Rank: Filter by category, star ratings, and sort by distance.

Non-Functional Requirements (SLAs/SLOs)

• High Read Throughput: $1,000:1$ read-to-write ratio.
• Latency: P99 search latency $< 50\text{ ms}$.
• Availability: $99.999\%$ uptime SLA.

2. Capacity & Scale Estimation

• Total Registered POIs: 200 Million ($2\times 10^8$).
• Search QPS: Average: $50,000\text{ QPS}$ (Peak: $\mathbf{125,000\text{ QPS}}$).
• POI Raw Storage: $\approx \mathbf{200\text{ GB}}$ (Fits entirely in memory or small database cluster).

3. AWS-First High-Level Architecture

Interactive Architecture Diagram
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4. API Interface Design

httpCopy
GET /v1/places/nearby?lat=37.7749&lon=-122.4194&radius_m=5000&category=coffee&limit=20
Host: places.production.aws.internal

Response: 200 OK
{
  "places": [
    {"business_id": "biz_101", "name": "Blue Bottle Coffee", "distance_meters": 340.5, "rating": 4.7}
  ]
}

5. Data Models & Storage Architecture

Amazon Aurora PostgreSQL PostGIS Schema

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CREATE EXTENSION IF NOT EXISTS postgis;

CREATE TABLE businesses (
    business_id UUID PRIMARY KEY DEFAULT gen_random_uuid(),
    name VARCHAR(255) NOT NULL,
    category VARCHAR(64) NOT NULL,
    geohash_code VARCHAR(12) NOT NULL,
    location GEOGRAPHY(Point, 4326) NOT NULL,
    rating NUMERIC(2, 1) DEFAULT 0.0
);
CREATE INDEX idx_businesses_spatial ON businesses USING GIST (location);

6. Component Deep Dives & Workflows

1. 9-Cell Geohash Expansion Query Sequence

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