Stratos Idreos's talk on DB Seminar

Title: Database Cracking and the Path Towards Auto-tuning Database Kernels

Abstract

Database cracking targets dynamic and exploratory environments where there is no sufficient workload knowledge and idle time to invest in physical design preparations and tuning. With DB cracking indexes are built incrementally, adaptively and on demand; each query is seen as an advice on how data should be stored. With each incoming query, data is reorganized on-the-fly as part of the query operators, while future queries exploit and continuously enhance this knowledge. Autonomously, adaptively and without any external human administration, the system quickly adapts to a new workload and reaches optimal performance when the workload stabilizes. We will talk about the basics of DB cracking including selection cracking, partial and sideways cracking, updates, workload robustness and concurrency control. We will also talk about important open and on going research issues such as disk based cracking and integration of cracking with offline and online index analysis.

 

Bio

Stratos Idreos holds a tenure track senior researcher position with CWI, the Dutch National Research Center for Mathematics and Computer Science. The main focus of his research is on adaptive query processing and database architectures, mainly in the context of column-stores. He also works on stream processing, distributed query processing and scientific databases. Stratos obtained his PhD from CWI and University of Amsterdam. In the past he has also been with the Technical University of Crete, Greece, and held research internship positions with Microsoft Research, Redmond USA, with EPFL, Switzerland and with IBM Almaden USA. Stratos won the 2011 ACM SIGMOD Jim Gray Doctoral Dissertation award for his thesis on database cracking, and the 2011 ERCIM Cor Baayen award  as a "most promising European young researcher in computer science and applied mathematics". In 2010 he was awarded with the IBM zEnterpise System Recognition Award by IBM research, while in 2011 he also won the VLDB 2011 Challenges and Visions best paper award.