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Sean Quinlan

Sean Quinlan

Authored Publications
Google Publications
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    Spanner: Google's Globally Distributed Database
    Michael Epstein
    Andrew Fikes
    Christopher Frost
    J. J. Furman
    Andrey Gubarev
    Christopher Heiser
    Sebastian Kanthak
    Eugene Kogan
    Hongyi Li
    Sergey Melnik
    David Mwaura
    David Nagle
    Rajesh Rao
    Lindsay Rolig
    Yasushi Saito
    Michal Szymaniak
    Christopher Taylor
    Ruth Wang
    Dale Woodford
    ACM Trans. Comput. Syst., vol. 31 (2013), pp. 8
    Preview
    Spanner: Google's Globally-Distributed Database
    Michael Epstein
    Andrew Fikes
    Christopher Frost
    JJ Furman
    Andrey Gubarev
    Christopher Heiser
    Peter Hochschild
    Sebastian Kanthak
    Eugene Kogan
    Hongyi Li
    Sergey Melnik
    David Mwaura
    David Nagle
    Rajesh Rao
    Lindsay Rolig
    Dale Woodford
    Yasushi Saito
    Christopher Taylor
    Michal Szymaniak
    Ruth Wang
    OSDI (2012)
    Preview abstract Spanner is Google's scalable, multi-version, globally-distributed, and synchronously-replicated database. It is the first system to distribute data at global scale and support externally-consistent distributed transactions. This paper describes how Spanner is structured, its feature set, the rationale underlying various design decisions, and a novel time API that exposes clock uncertainty. This API and its implementation are critical to supporting external consistency and a variety of powerful features: non-blocking reads in the past, lock-free read-only transactions, and atomic schema changes, across all of Spanner. View details
    Availability in Globally Distributed Storage Systems
    Daniel Ford
    Francois Labelle
    Florentina Popovici
    Murray Stokely
    Van-Anh Truong
    Proceedings of the 9th USENIX Symposium on Operating Systems Design and Implementation, USENIX (2010)
    Preview abstract Highly available cloud storage is often implemented with complex, multi-tiered distributed systems built on top of clusters of commodity servers and disk drives. Sophisticated management, load balancing and recovery techniques are needed to achieve high performance and availability amidst an abundance of failure sources that include software, hardware, network connectivity, and power issues. While there is a relative wealth of failure studies of individual components of storage systems, such as disk drives, relatively little has been reported so far on the overall availability behavior of large cloud-based storage services. We characterize the availability properties of cloud storage systems based on an extensive one year study of Google's main storage infrastructure and present statistical models that enable further insight into the impact of multiple design choices, such as data placement and replication strategies. With these models we compare data availability under a variety of system parameters given the real patterns of failures observed in our fleet. View details
    Preview abstract Very large data sets often have a flat but regular structure and span multiple disks and machines. Examples include telephone call records, network logs, and web document repositories. These large data sets are not amenable to study using traditional database techniques, if only because they can be too large to fit in a single relational database. On the other hand, many of the analyses done on them can be expressed using simple, easily distributed computations: filtering, aggregation, extraction of statistics, and so on. We present a system for automating such analyses. A filtering phase, in which a query is expressed using a new programming language, emits data to an aggregation phase. Both phases are distributed over hundreds or even thousands of computers. The results are then collated and saved to a file. The design -- including the separation into two phases, the form of the programming language, and the properties of the aggregators -- exploits the parallelism inherent in having data and computation distributed across many machines. Animation: The paper references this movie showing how the distribution of requests to google.com around the world changed through the day on August 14, 2003. View details
    Security in Plan 9
    Eric Grosse
    Rob Pike
    David L. Presotto
    USENIX Security Symposium (2002), pp. 3-16
    Venti: A New Approach to Archival Storage
    FAST (2002), pp. 89-101
    Robot planning and control
    Oussama Khatib
    David Williams
    Robotics and Autonomous Systems, vol. 21 (1997), pp. 249-261
    Efficient Distance Computation Between Non-Convex Objects
    ICRA (1994), pp. 3324-3329
    Elastic Bands: Connecting Path Planning and Control
    Oussama Khatib
    ICRA (2) (1993), pp. 802-807
    A Cached WORM File System
    Softw., Pract. Exper., vol. 21 (1991), pp. 1289-1299
    Towards Real-Time Execution of Motion Tasks
    Oussama Khatib
    ISER (1991), pp. 241-254