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image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao https://doi.org/10.1...arrow_drop_down
image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
https://doi.org/10.1109/iccd.2...
Article . 2000 . Peer-reviewed
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Unified fine-granularity buffering of index and data: approach and implementation

Authors: Qiang Cao; Josep Torrellas; H. V. Jagadish;

Unified fine-granularity buffering of index and data: approach and implementation

Abstract

Disk I/O is recognized as a major performance bottleneck in many database applications. Consequently, a topic of considerable study in database systems has traditionally been buffer management. Recently, disk pages have been increasing in size, enabling more and more data to fit in a single page. Such a trend suggests that buffering the data at a grain size finer than a page may use memory better. As a result, there has been some interest in fine-granularity buffering. Past approaches to fine-granularity buffering have proposed buffering either data tuples alone or index entries alone. In this paper, we propose a scheme to support fine-granularity buffering of both index and data entries in a unified manner. The scheme, which we call Hot-Entry buffering, can be used in combination with conventional page-level buffering. Through the experimental evaluation of a simple system, we demonstrate the benefits of our scheme over conventional page-level buffering, and over index-only and data-only fine-granularity buffering. In particular, we show that, for a range of parameter values, our buffering scheme speeds-up query execution by 20-60% relative to page-level buffering only, and by 10-20% relative to the best of index-only or data-only fine-granularity buffering.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
2
Average
Average
Average
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