Xingzhong Xu |
Uber senior engineer II
Xingzhong Xu is a senior engineer II at Uber Technologies Inc. He is currently the tech lead of surge pricing at Uber. He has many years experiences on real-time operations research, two-side market optimization, large scale streaming processing etc.
Xingzhong Xu |
Uber
senior engineer II
senior engineer II
即将开始的A2M课程
Scaling Uber Real-time Optimization with Apache Flink
大数据前沿
2019-05-19 14:30--15:30
Uber marketplace connects riders looking for transportation with drivers looking for work at the push of a button. Many marketplace products (e.g. pricing, health, positioning etc.) require intensive real-time optimizations. Such applications help Uber automatically maintain marketplace reliability, generate market insights and improve the network efficiency across more than 600 cities in real-time.
Uber engineers leverage Apache Flink to build a platform that not only runs compute intensive optimization models, but also very quickly reacts to rapid changes in marketplace. In this talk, I will cover the compute platform that leverages Apache Flink to i.) aggregate billions of realtime and forecasted demand and supply level information across the globe. ii.) trigger on-demand optimization models to respond to changes in marketplace and iii.) scale both horizontally and vertically as we expand the platform to onboard new applications and experiences.
Xingzhong Xu is a senior engineer II at Uber Technologies Inc. He is currently the tech lead of surge pricing at Uber. He has many years experiences on real-time operations research, two-side market optimization, large scale streaming processing etc.
即将开始的A2M课程
Scaling Uber Real-time Optimization with Apache Flink
大数据前沿
2019-05-19 14:30--15:30
Uber marketplace connects riders looking for transportation with drivers looking for work at the push of a button. Many marketplace products (e.g. pricing, health, positioning etc.) require intensive real-time optimizations. Such applications help Uber automatically maintain marketplace reliability, generate market insights and improve the network efficiency across more than 600 cities in real-time.
Uber engineers leverage Apache Flink to build a platform that not only runs compute intensive optimization models, but also very quickly reacts to rapid changes in marketplace. In this talk, I will cover the compute platform that leverages Apache Flink to i.) aggregate billions of realtime and forecasted demand and supply level information across the globe. ii.) trigger on-demand optimization models to respond to changes in marketplace and iii.) scale both horizontally and vertically as we expand the platform to onboard new applications and experiences.
