Wilson C. Hsieh

Wilson C. Hsieh

Authored 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., 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
    Bigtable: A Distributed Storage System for Structured Data
    Fay Chang
    Deborah A. Wallach
    Mike Burrows
    Andrew Fikes
    7th USENIX Symposium on Operating Systems Design and Implementation (OSDI), {USENIX}(2006), pp. 205-218
    Preview abstract Bigtable is a distributed storage system for managing structured data that is designed to scale to a very large size: petabytes of data across thousands of commodity servers. Many projects at Google store data in Bigtable, including web indexing, Google Earth, and Google Finance. These applications place very different demands on Bigtable, both in terms of data size (from URLs to web pages to satellite imagery) and latency requirements (from backend bulk processing to real-time data serving). Despite these varied demands, Bigtable has successfully provided a flexible, high-performance solution for all of these Google products. In this paper we describe the simple data model provided by Bigtable, which gives clients dynamic control over data layout and format, and we describe the design and implementation of Bigtable. View details