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2009 First International Workshop on Database Technology and Applications
Data Streams Join Aggregate Algorithms Based on Compound Sliding Window
Wuhan, Hubei, China
April 25-April 26
ISBN: 978-0-7695-3604-0
ASCII Text
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Yingli Zhong, Weiping Wang, Longjiang Guo, "Data Streams Join Aggregate Algorithms Based on Compound Sliding Window," Database Technology and Applications, International Workshop on, pp. 426-430, 2009 First International Workshop on Database Technology and Applications, 2009.
 
 
BibTex
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@article{ 10.1109/DBTA.2009.71,
author = {Yingli Zhong and Weiping Wang and Longjiang Guo},
title = {Data Streams Join Aggregate Algorithms Based on Compound Sliding Window},
journal ={Database Technology and Applications, International Workshop on},
volume = {0},
year = {2009},
isbn = {978-0-7695-3604-0},
pages = {426-430},
doi = {http://doi.ieeecomputersociety.org/10.1109/DBTA.2009.71},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
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TY - CONF
JO - Database Technology and Applications, International Workshop on
TI - Data Streams Join Aggregate Algorithms Based on Compound Sliding Window
SN - 978-0-7695-3604-0
SP426
EP430
A1 - Yingli Zhong,
A1 - Weiping Wang,
A1 - Longjiang Guo,
PY - 2009
KW - data streams
KW - basic window
KW - compound sliding window
KW - join aggregate algorithms
VL - 0
JA - Database Technology and Applications, International Workshop on
ER -
 
In many applications of data stream, join aggregate queries based on sliding window are a sort of queries that are widely used. All the join aggregate query algorithms in existing research works are designed for immediate continuous queries. In this paper, a join aggregate query method based on compound sliding window for periodically executed continuous queries is presented. This method organizes the basic windows in a compound sliding window into hash tables, according to their join properties, the aggregate values are computed while the join processing, the join results of compound sliding window are not saved, so the memory used by query processing is greatly reduced. An algorithm that computes the N+1th join aggregate value increment by using the Nth one is presented. Theoretical analysis and experiment result both show good time and space complexity of this incremental algorithm.
Index Terms:
data streams, basic window, compound sliding window, join aggregate algorithms
Citation:
Yingli Zhong, Weiping Wang, Longjiang Guo, "Data Streams Join Aggregate Algorithms Based on Compound Sliding Window," dbta, pp.426-430, 2009 First International Workshop on Database Technology and Applications, 2009
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