Hoodie: Incremental processing on Hadoop at Uber
Uber relies on making data-driven decisions at every level, and most of these decisions can benefit from faster data processing. Vinoth Chandar and Prasanna Rajaperumal introduce Hoodie, a newly open sourced system at Uber that adds new incremental processing primitives to existing Hadoop technologies to provide near-real-time data at 10x reduced cost.
| Talk Title | Hoodie: Incremental processing on Hadoop at Uber |
| Speakers | Vinoth Chandar (Apache Hudi), Prasanna Rajaperumal (Uber) |
| Conference | Strata + Hadoop World |
| Conf Tag | Big Data Expo |
| Location | San Jose, California |
| Date | March 14-16, 2017 |
| URL | Talk Page |
| Slides | Talk Slides |
| Video | |
Uber’s mission is to provide transportation as reliable as running water, everywhere, for everyone. To fulfill its mission, Uber relies on making data-driven decisions at every level, and most of these decisions can benefit from faster data processing. Vinoth Chandar and Prasanna Rajaperumal explore data processing systems for near-real-time use cases, making the case that adding new incremental processing primitives to existing Hadoop technologies can solve many problems at reduced cost and in a unified manner. Along the way, Vinoth and Prasanna introduce Hoodie, a newly open sourced storage system at Uber that adds new incremental processing primitives to existing Hadoop technologies to provide near-real-time data at 10x reduced cost using Spark and Hadoop and share their production experience.
