Geospatial big data analysis at Uber
Uber's geospatial data is increasing exponentially as the company grows. As a result, its big data systems must also grow in scalability, reliability, and performance to support business decisions, user recommendations, and experiments for geospatial data. Zhenxiao Luo and Wei Yan explain how Uber runs geospatial analysis efficiently in its big data systems, including Hadoop, Hive, and Presto.
| Talk Title | Geospatial big data analysis at Uber |
| Speakers | Zhenxiao Luo (Twitter), Wei Yan (Uber) |
| Conference | Strata Data Conference |
| Conf Tag | Make Data Work |
| Location | New York, New York |
| Date | September 26-28, 2017 |
| URL | Talk Page |
| Slides | Talk Slides |
| Video | |
Uber’s geospatial data is increasing exponentially as the company grows. As a result, its big data systems must also grow in scalability, reliability, and performance to support business decisions, user recommendations, and experiments for geospatial data. Zhenxiao Luo and Wei Yan explain how Uber runs geospatial analysis efficiently in its big data systems, including Hadoop, Hive, and Presto. Zhenxiao and Wei start with an overview of Uber’s big data infrastructure before explaining how Uber models geospatial data and outlining its data ingestion pipeline. They then discuss geospatial query performance improvement techniques and experiences, focusing on geospatial data processing in big data systems, including Hadoop and Presto. Zhenxiao and Wei conclude by sharing Uber’s use cases and roadmap.
