查询地球:Uber的地理空间大数据分析(Query the planet: Geospatial big data analytics at Uber)

此演讲使用中文 (This will be presented in Chinese)

Zhenxiao Luo (Twitter)
14:5015:30 Friday, June 21, 2019
实施人工智能 (Implementing AI)
Location: 报告厅(Auditorium)
Average rating: *****
(5.00, 2 ratings)

必要预备知识 (Prerequisite Knowledge)

  • A basic understanding of big data and machine learning

您将学到什么 (What you'll learn)

  • Learn how to run big data and machine learning systems at scale

描述 (Description)

Analyzing geospatial data is one of Uber’s distinct challenges; city locations, trips, and event information, for instance, provide insights that can improve business decisions and better serve users. Geospatial data analysis is particularly challenging, especially in a big data scenario, such as computing how many rides start at a transit location, how many drivers are crossing state lines, and so on. For these analytical requests, Uber must achieve efficiency, usability, and scalability in order to meet user needs and business requirements.

From determining the most convenient rider pickup points to predicting the fastest routes, Uber aims to use data-driven analytics to create seamless trip experiences. Within engineering, analytics inform decision-making processes across the board. Zhenxiao Luo explains how Uber uses artificial intelligence in its production environment to process the big data powering its interactive SQL engine.

Photo of Zhenxiao Luo

Zhenxiao Luo


Zhenxiao Luo is leading Interactive Query Engines team at Twitter, where he focuses on Druid, Presto, Spark, and Hive. Before joining Twitter, Zhenxiao was running Interactive Analytics team at Uber. He has big data experience at Netflix, Facebook, Cloudera, and Vertica. Zhenxiao is Committer and Technical Steering Committee(TSC) member of Presto. He holds a master’s degree from the University of Wisconsin-Madison and a bachelor’s degree from Fudan University.