ACM SIGMOD is pleased to present the 2017 SIGMOD Jim Gray Doctoral Dissertation Award to Peter Bailis. Peter completed his dissertation titled “Coordination Avoidance in Distributed Databases” at the University of California, Berkeley, under the supervision of Joseph Hellerstein, Ion Stoica, and Ali Ghodsi. The main contribution of Peter’s thesis is the introduction and study of coordination-free execution in modern database systems. In contrast to the classic approach of implementing transaction semantics through coordination, which can be very expensive in modern distributed architectures, a coordination-free approach avoids any type of coordination and can lead to building more efficient systems for a variety of tasks, ranging from ensuring transaction isolation levels to enforcing database constraints and helping with guaranteeing application level invariants. The thesis investigates in depth for which semantic requirements of applications it is possible to achieve coordination-free execution, and identifies a key mathematical property that permits coordination-free execution, called invariant confluence. Detailed experimentation shows that for a variety of practical scenarios, coordination-free execution can achieve orders of magnitude better performance over a coordination-based approach. Peter’s work addresses a practical and challenging problem in distributed data management, proposing fundamentally new ideas in a well-established research area. It combines a simple and elegant theoretical framework with practical system building. The ideas in the thesis will very likely be impactful to both database researchers and practitioners.
Peter Bailis is an assistant professor of Computer Science at Stanford University. Peter’s research in the Future Data Systems group focuses on the design and implementation of next-generation, post-database data-intensive systems. His work spans large-scale data management, distributed protocol design, and architectures for high-volume complex decision support. He is the recipient of an NSF Graduate Research Fellowship, a Berkeley Fellowship for Graduate Study, best-of-conference citations for research appearing in both SIGMOD and VLDB, and the CRA Outstanding Undergraduate Researcher Award. He received a Ph.D. from UC Berkeley in 2015 and an A.B. from Harvard College in 2011, both in Computer Science.
ACM SIGMOD is also pleased to recognize Immanuel Trummer for Honorable Mention for the 2017 SIGMOD Jim Gray Doctoral Dissertation Award. Immanuel completed his dissertation titled “From Massive Parallelization to Quantum Computing: Seven Novel Approaches to Query Optimization” at École Polytechnique Fédérale de Lausanne under the supervision of Christoph Koch.
Immanuel Trummer is assistant professor for computer science at Cornell University. He received his PhD from the Swiss Federal Institute of Technology in Lausanne under supervision of Christoph Koch. His research focuses on databases and data analysis and in particular on optimization problems that arise in that context. Immanuel’s papers were selected for best of VLDB, for the ACM SIGMOD Research Highlight Award, and for publication in CACM as CACM Research Highlight. He received the Google European PhD Fellowship in structured data analysis and is alumnus of the German National Academic Foundation. He is also a recipient of the Google Faculty Research Award 2016.