Presented By O’Reilly and Cloudera
Make Data Work
March 5–6, 2018: Training
March 6–8, 2018: Tutorials & Conference
San Jose, CA
Ritesh Agrawal

Ritesh Agrawal
Data Scientist, Uber

Website

Ritesh Agrawal leads the intelligent infrastructure systems team at Uber, which focuses on scaling data infrastructure for Uber’s growing business needs now and foreseeable in the future. A leading data scientist for optimizing infrastructure, previously, Ritesh specialized in predictive and ranking models at Netflix, AT&T Labs, and Yellow Pages, where he built scalable machine learning infrastructure with technologies such as Docker, Hadoop, and Spark. He holds a PhD in environmental earth science from Pennsylvania State University, where his thesis focused on computational tools and technologies such as concept map ontologies.

Sessions

2:40pm–3:20pm Wednesday, March 7, 2018
Presto query gate: Identifying and stopping rogue queries
Big data and data science in the cloud, Data engineering and architecture
 Location: 230 C
Ritesh Agrawal (Uber), Anirban Deb (Uber)
Presto has emerged as the de facto query engine to quickly process petabytes of data. However, rogue SQL queries can waste a significant amount of critical compute resource and reduce Presto's throughput. Ritesh Agrawal and Anirban Deb explain how Uber uses machine learning to identify and stop rogue queries, saving both computational power and money. Read more.