Google BigQuery is a serverless, scalable, and cost effective cloud data warehouse. In this talk, we give an overview of distributed query execution in BigQuery and present various query optimization techniques used. In particular, we will discuss the dynamic query execution primitives built into BigQuery.

This talk is part of the Vaccination Database Tech Talk Seminar Series.

Bio:
Hossein Ahmadi is currently a senior staff engineer at Google and the overall technical lead for Google BigQuery. He joined Google and BigQuery in 2011 and has been one of the architects working on data transfer, distributed query processing, storage, and machine learning infrastructure. He received his PhD from University of Illinois at Urbana Champaign in 2011 where he focused on data processing methods for embedded and IoT systems. Aleksandras Surna is currently one of the technical leads on the Google BigQuery team focusing on the development of the distributed query processing engine. He has contributed to the design and implementation of the columnar store, query optimizer, query processing runtime, and other components of BigQuery. Before joining Google, Aleksandras worked on the development of the Microsoft SQL Server database engine.

More Info: https://db.cs.cmu.edu/seminar2021/#db10