Robert E. Gruber
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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
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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.
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PADX: Querying large-scale ad hoc data with XQuery
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Mary Fernandez
Kathleen Fisher
Yitzhak Mandelbaum
Proceedings of PLAN-X 2006: Workshop on Programming Language technologies for XML (2006)
PADS: a Domain-Specific Language for Processing ad hoc Data
Kathleen Fisher
Proceedings of the 2005 ACM SIGPLAN Conference on Programming Language Design and Implementation (2005), pp. 295-304
Robustness Testing and Hardening of CORBA ORB Implementations
Jianto Pan
Philip Koopman
Daniel Siewiorek
Yennun Huang
Mimi Ling Jiang
Proceedingsof the International Conference on Dependable Systems and Networks (ICDSN/FTCS) (2001), pp. 141-150
High-level Constructs in the READY Event Notification System
Balachander Krishnamurthy
Euthimios Panagos
Proceedings of the 8th ACM SIGOPS European Workshop (EW'98) on Support for Composing Distributed Applications, ACM Press New York, NY, USA (1998), pp. 195-202
Optimism vs. Locking: A Study of Concurrency Control for Client-Server Object-Oriented Databases. Available as Technical Report MIT/LCS/TR-708
Massachusetts Institute of Technology, Cambridge, MA, USA (1997)
Efficient Optimistic Concurrency Control using Loosely Synchronized Clocks
{Atul Adya
Barbara Liskov
Umesh Maheshwari}
Proceedings of the 1995 ACM SIGMOD international conference on Management of Data (1995), pp. 23-34
Efficient Optimistic Concurrency Control Using Loosely Synchronized Clocks
Replication in the Harp File System
Barbara Liskov
Paul Johnson
Liuba Shrira
Michael Williams
Proceedings of 13th ACM Symposium on Operating Systems Principles (SOSP), Association for Computing Machinery SIGOPS (1991), pp. 226-38
