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HP Wrote: ------------------------------------------------------- > The Google File System > Sanjay Ghemawat, Howard Gobioff, and Shun-Tak > Leung > > Link: http://labs.google.com/papers/gfs.html > > Abstract > > We have designed and implemented the Google File > System, a scalable distributed file system for > large distributed data-intensive applications. It > provides fault tolerance while running on > inexpensive commodity hardware, and it delivers > high aggregate performance to a large number of > clients. > > While sharing many of the same goals as previous > distributed file systems, our design has been > driven by observations of our application > workloads and technological environment, both > current and anticipated, that reflect a marked > departure from some earlier file system > assumptions. This has led us to reexamine > traditional choices and explore radically > different design points. > > The file system has successfully met our storage > needs. It is widely deployed within Google as the > storage platform for the generation and processing > of data used by our service as well as research > and development efforts that require large data > sets. The largest cluster to date provides > hundreds of terabytes of storage across thousands > of disks on over a thousand machines, and it is > concurrently accessed by hundreds of clients. > > In this paper, we present file system interface > extensions designed to support distributed > applications, discuss many aspects of our design, > and report measurements from both micro-benchmarks > and real world use. > > Appeared in: > 19th ACM Symposium on Operating Systems > Principles, > Lake George, NY, October, 2003. > > Download: PDF Version > > > Bigtable: A Distributed Storage System for > Structured Data > Fay Chang, Jeffrey Dean, Sanjay Ghemawat, Wilson > C. Hsieh, Deborah A. Wallach, Mike Burrows, Tushar > Chandra, Andrew Fikes, and Robert E. Gruber > > Link: http://labs.google.com/papers/bigtable.html > > 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. > > Appeared in: > OSDI'06: Seventh Symposium on Operating System > Design and Implementation, > Seattle, WA, November, 2006. > > Download: PDF Version