Trip Analytics & Heatmap Engine

Uber-style city demand heatmaps powered by PostGIS geospatial queries, aggregation pipelines, and pre-computed materialized views.

Features

• Store ride coordinates – Pickup and dropoff lat/lng per trip
• Aggregate trips per region – Grid-based aggregation (500m cells)
• Demand heatmap – Pre-computed materialized view for fast reads
• Geospatial queries – PostGIS ST_SquareGrid, ST_Intersects, GIST indexes

Quick Start

# 1. Start Postgres + PostGIS
docker compose up -d

# 2. Seed demo trips (NYC area)
go run ./cmd/seed

# 3. Start API server
go run ./cmd/server

API

Method	Endpoint	Description
GET	/api/v1/heatmap?min_count=0	Demand heatmap (grid cells with trip counts)
POST	/api/v1/trips	Create trip (pickup/dropoff coordinates)
POST	/api/v1/heatmap/refresh	Re-run aggregation pipeline (refresh MV)
GET	/health	Health check

Create Trip

curl -X POST http://localhost:8080/api/v1/trips \
  -H "Content-Type: application/json" \
  -d '{"pickup_lng":-73.98,"pickup_lat":40.75,"dropoff_lng":-73.99,"dropoff_lat":40.76,"fare_amount":15.50,"passenger_count":2}'

Get Heatmap

curl "http://localhost:8080/api/v1/heatmap?min_count=1"

Response: { "cells": [...], "min_lng", "max_lng", "min_lat", "max_lat", "grid_m": 500 }

Refresh Heatmap

After adding trips, run:

curl -X POST http://localhost:8080/api/v1/heatmap/refresh

Config

Env	Default
DATABASE_URL	postgres://triplytics:triplytics@localhost:5432/triplytics?sslmode=disable
PORT	8080
GRID_SIZE_M	500

Architecture

• PostGIS – geography(POINT) for pickup/dropoff, spatial indexes
• Materialized view demand_heatmap – Grid cells with trip_count, total_fare
• Aggregation pipeline – REFRESH MATERIALIZED VIEW CONCURRENTLY demand_heatmap