A Driver-Rider Matching service based on Apache Samza

Pan Kong, Zhangfan Dong, and Kaiyue Sun

Design goals• Functionality

Drivers can update their locations to the server periodicallyRiders can sent ride request to find nearest driver

• PerformanceScalable, low latency

Problems• User locations are transitory data, no

need to persistently store in database• Database will become bottleneck

under high workload (Exclusive access, lock)

• Matching engine embedded within Web Server, will hog Server’s computing resources

Data Tier

User Profiles

Presentation Tier

Application Tier

UI on Browsers

Web ServerMatching Engine

Three-tier architecture

Stream processing framework

Stream Processing TierApache Samza

Presentation Tier

Application Tier

UI on Browsers

Web Server

Matching EngineUser Profiles

Desired properties• Samza is partitioned and distributed

at every level, and therefore is inherently scalable

• Samza guarantees low latency in big data processing compared tobatch processing system

Jakob Homan http://www.slideshare.net/blueboxtraveler/apache-samza

Architecture & Implementation

Matching result

HTTP Response

Client UI

SAMZA

Query Server

HTTP Serverkafka

REST Proxy

Input Topics: - Driver Location - Ride Request

Output Topics: - Match

Matching Engine

Matching result

Pull Kafka Msg

HTTP RequestDriver updatesRide requests

Push Kafka MsgDriver updatesRide requests

Push Kafka Msg

Matching result

Driver updatesRide requests

Pull Kafka Msg

User Interface

Driver location updating page Ride requesting page

Home page

Performance Testing

Throughput of driver_update_only workloadThroughput of ride_request_only workload Throughput of mixed workload

Latency of driver_update_only workload Latency of ride_request_only workload Latency of mixed workload

Samza: Implementation based on Apache SamzaMongoDB: Implementation based on three-tier architecture