Execution Reordering for Tertiary Memory Access.
Sunita Sarawagi:
Execution Reordering for Tertiary Memory Access.
IEEE Data Eng. Bull. 20(3): 46-54(1997)@article{DBLP:journals/debu/Sarawagi97a,
author = {Sunita Sarawagi},
title = {Execution Reordering for Tertiary Memory Access},
journal = {IEEE Data Eng. Bull.},
volume = {20},
number = {3},
year = {1997},
pages = {46-54},
ee = {db/journals/debu/Sarawagi97a.html},
bibsource = {DBLP, http://dblp.uni-trier.de}
}
BibTeX
Abstract
In this article we investigate methods of dynamically reordering execution of a query plan.
In existing systems, once a query is optimized, it is executed in a fixed order, with the result that data requests are made in a fixed order.
Only limited forms of runtime reordering can be provided by low-level device managers.
More aggressive reordering strategies are essential in scenarios where the latency of access to data objects varies widely and dynamically, as in tertiary devices, wide area distributed systems and broadcast disks in mobile computing.
In this article we focus on methods of dynamically reordering different parts of a plan tree to match execution order to the optimal data fetch order.
These techniques were developed in the context of a tertiary memory database system but are applicable to other cases as well.
Our prototype implementation based on Postgres yields significant performance improvements with these techniques.
Copyright © 1997 by The Institute of
Electrical and Electronic Engineers, Inc. (IEEE).
Abstract used with permission.
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BibTeX
Online Edition:
Data Engineering Bulletin September 1997:
Improving Query Responsiveness (Michael Franklin, ed.)
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Referenced by
- Luis M. Bernardo, Henrik Nordberg, Doron Rotem, Arie Shoshani:
Determining the Optimal File Size on Tertiary Storage Systems Based on the Distribution of Query Sizes.
SSDBM 1998: 22-31
BibTeX
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