Abstract: Database system performance heavily depends on data access efficiency on all levels of the memory hierarchy. CPU cache performance depends on in-memory data layout, whereas I/O performance depends on data placement on the disks. Throughout the memory hierarchy, however, the workload behavior is a function of the access patterns the application dictates. On-line transaction processing applications, for instance, tend to access full data records in a random fashion, whereas decision-support systems typically scan large tables sequentially, reading small fractions of the records. Unfortunately, current database storage systems are static and fragile. Low-level system parameters are fully configured by human administrators, whereas there is typically a single data organization used at all levels of the memory hierarchy, and data organization is specialized to a single workload. This results in frequent errors, suboptimal performance, and inability to take advantage of the storage technology at its full potential.

This talk describes Fates, a dynamic, robust, and automated system for database storage management. Borrowing from the Greek mythology, Fates includes three components that establish proper abstractions in the database storage system: Clotho decouples in-memory data layout from on-disk storage layout, providing the opportunity to design efficient data placement at each storage level separately. Lachesis provides device-specific hints and automatically specializes the system to extracted device characteristics. Finally, Atropos provides logical-to-physical volume mapping and arranges storage to offer robust performance across workloads. The talk will describe the Fates system design and implementation, and will demonstrate its efficiency through experimental results with application benchmarks.

Short Bio: Anastassia (Natassa) Ailamaki received a B.Sc. degree in Computer Engineering from the Polytechnic School of the University of Patra, Greece, M.Sc. degrees from the Technical University of Crete, Greece and from the University of Rochester, NY, and a Ph.D. degree in Computer Science from the University of Wisconsin-Madison. In 2001, she joined the Computer Science Department at Carnegie Mellon University as an Assistant Professor. Her research interests are in the broad area of database systems and applications, with emphasis on database system behavior on modern processor hardware and disks. Her projects at Carnegie Mellon (including Staged Database Systems, Cache-Resident Data Bases, and the Fates Storage Manager), aim at building systems to strengthen the interaction between the database software and the underlying hardware and I/O devices. Her other research interests include automated database design for scientific databases, storage device modeling, and internet querying. She has received three best-paper awards (VLDB 2001, Performance 2002, and ICDE 2004), an NSF CAREER award (2002), and IBM Faculty Partnership awards in 2001, 2002, and 2003. She is a member of IEEE and ACM, and has also been a CRA-W mentor.