UBER Architecture System design | Ride Hailing Platform

Summary

This script outlines the architecture of a ride-hailing service, focusing on the backend's technical components and communication flow between drivers, riders, and the server. Key aspects include location tracking, driver-rider matching, trip progress tracking, and real-time updates. The system is built using microservices, including location, dispatch, trip tracking, ETA, billing, and notification services. It employs geospatial indexing (Geohash/S2) for efficient driver location searches, horizontal scaling with region-based caching, and WebSockets for real-time communication. The architecture ensures scalability, efficiency, and an enhanced user experience in a ride-hailing system.

Takeaways

• 😀 Efficient driver-rider matching relies on geospatial algorithms like Geohash or S2 to divide the geographical area into cells for faster searches.
• 😀 Microservices architecture is used, with services like location tracking, dispatch, ETA, billing, and notifications each running independently for scalability and flexibility.
• 😀 Drivers send location updates every few seconds, and this information is stored in a memory cache (e.g., Redis) for real-time access and fast updates.
• 😀 Rider trip requests are processed by the Dispatch Service, which queries the Location Service to find nearby drivers and offer trips to them.
• 😀 Trip status updates (e.g., progress, changes) are handled by the Trip Tracker Service, which stores this data in a scalable NoSQL database like Cassandra.
• 😀 The system can calculate ETAs using external APIs like Google Maps, factoring in traffic conditions and offering real-time travel time predictions.
• 😀 The Billing Service processes trip data and calculates fares, which are then communicated to both the driver and rider via a Notification Service.
• 😀 Horizontal scaling is achieved by partitioning the data across multiple region-based cache servers to handle large-scale location tracking efficiently.
• 😀 To handle driver location changes when crossing cells, either a driver sends both previous and current locations, or the system queries the current cell first to update the data.
• 😀 WebSocket Gateway enables real-time two-way communication for trip updates, location changes, and other notifications between the backend and client applications.
• 😀 AWS services like Lambda functions and API Gateway are ideal for implementing microservices, offering serverless scalability and easy integration of analytics.

Q & A

What are the key services needed for a ride-hailing service?

The key services needed include location tracking, trip tracking, dispatch, ETA calculation, billing, and notifications. Each of these services is implemented as a microservice to ensure scalability and efficiency.

How does the system track the location of drivers and riders?

The location of drivers is tracked by receiving updates every few seconds from the driver's app. The system uses geohash or S2 libraries to divide geographical areas into cells, making it easier to find drivers in proximity to a rider.

What method is used to find the nearest drivers to a rider?

The geographical area is divided into cells using geohash or S2. The system maps the rider's location to a cell and looks for nearby drivers within the same cell or adjacent cells to efficiently match a driver to a rider.

What role do geohash and S2 geometry play in location tracking?

Geohash and S2 geometry divide the Earth's surface into cells, allowing for efficient tracking of locations. Geohash treats the surface as flat, while S2 can account for the spherical nature of the Earth, providing more accurate location tracking.

How is the location data for drivers stored and managed?

The location data for drivers is stored in a cache, like Redis, where each cell ID is mapped to a list of drivers. This allows for fast storage and retrieval of driver location information. The system can scale by distributing this data across multiple servers based on regions.

What happens when a driver moves from one cell to another?

When a driver moves between cells, the system needs to update the driver's new location. This can be done by sending both the current and previous location, or by looking up the driver's current cell before processing the update.

How does the system handle horizontal scaling for location data?

The location data is divided into regions, and each region is managed by a separate cache server. This horizontal scaling approach allows the system to handle large volumes of driver and rider location data efficiently.

What database technologies are used for storing trip status updates?

Trip status updates are stored in a NoSQL database like Cassandra. This allows for efficient handling of real-time updates and scalability. The system may also store trip data as JSON documents to accommodate flexible data models.

How is the ETA (Estimated Time of Arrival) calculated in the system?

The system calculates ETA using services like Google Maps' Distance Matrix API. This API takes two locations (from and to) and calculates the time needed to travel between them, factoring in traffic conditions and other variables.

How does the ride-hailing service manage communication between drivers, riders, and the server?

Communication between drivers, riders, and the server happens over WebSockets, a real-time asynchronous protocol. A messaging server abstracts the interaction between the WebSocket Gateway and microservices, ensuring that updates and notifications are sent promptly.