Temporal Coalescing on Window Extents over Data Streams
Summary :
This paper focuses on the coalescing operator applied to the processing of continuous queries with temporal functions and predicates over windowed data streams. Coalescing is a key operation enabling the evaluation of interval predicates and functions on temporal tuples. Applying this operation for temporal query processing on windowed streams brings the challenge of coalescing tuples in a window extent each time the window slides over the data stream. This coalescing becomes even more involving when some tuples arrive out of order. This paper distinguishes between eager coalescing and lazy coalescing, the two known coalescing schemes. The former coalesces tuples during window extent update and the latter does it during window extent scan. With these two schemes, the paper first presents algorithms for updating a window extent for both tuple-based and time-based windows. Then, the problem of optimally selecting between eager and lazy coalescing for concurrent queries is formulated as a 0-1 integer programming problem. Through extensive performance study, the two schemes are compared and the optimal selection is demonstrated.
- Publication
- IEICE TRANSACTIONS on Information Vol.E94-D No.3 pp.489-503
- Publication Date
- 2011/03/01
- Publicized
- Online ISSN
- 1745-1361
- DOI
- 10.1587/transinf.E94.D.489
- Type of Manuscript
- Special Section PAPER (Special Section on Data Engineering)
- Category
Authors
Keyword
Latest Issue
Copyrights notice of machine-translated contents
The copyright of the original papers published on this site belongs to IEICE. Unauthorized use of the original or translated papers is prohibited. See IEICE Provisions on Copyright for details.
Cite this
Copy
Mohammed AL-KATEB, Sasi Sekhar KUNTA, Byung Suk LEE, "Temporal Coalescing on Window Extents over Data Streams" in IEICE TRANSACTIONS on Information,
vol. E94-D, no. 3, pp. 489-503, March 2011, doi: 10.1587/transinf.E94.D.489.
Abstract: This paper focuses on the coalescing operator applied to the processing of continuous queries with temporal functions and predicates over windowed data streams. Coalescing is a key operation enabling the evaluation of interval predicates and functions on temporal tuples. Applying this operation for temporal query processing on windowed streams brings the challenge of coalescing tuples in a window extent each time the window slides over the data stream. This coalescing becomes even more involving when some tuples arrive out of order. This paper distinguishes between eager coalescing and lazy coalescing, the two known coalescing schemes. The former coalesces tuples during window extent update and the latter does it during window extent scan. With these two schemes, the paper first presents algorithms for updating a window extent for both tuple-based and time-based windows. Then, the problem of optimally selecting between eager and lazy coalescing for concurrent queries is formulated as a 0-1 integer programming problem. Through extensive performance study, the two schemes are compared and the optimal selection is demonstrated.
URL: https://global.ieice.org/en_transactions/information/10.1587/transinf.E94.D.489/_p
Copy
@ARTICLE{e94-d_3_489,
author={Mohammed AL-KATEB, Sasi Sekhar KUNTA, Byung Suk LEE, },
journal={IEICE TRANSACTIONS on Information},
title={Temporal Coalescing on Window Extents over Data Streams},
year={2011},
volume={E94-D},
number={3},
pages={489-503},
abstract={This paper focuses on the coalescing operator applied to the processing of continuous queries with temporal functions and predicates over windowed data streams. Coalescing is a key operation enabling the evaluation of interval predicates and functions on temporal tuples. Applying this operation for temporal query processing on windowed streams brings the challenge of coalescing tuples in a window extent each time the window slides over the data stream. This coalescing becomes even more involving when some tuples arrive out of order. This paper distinguishes between eager coalescing and lazy coalescing, the two known coalescing schemes. The former coalesces tuples during window extent update and the latter does it during window extent scan. With these two schemes, the paper first presents algorithms for updating a window extent for both tuple-based and time-based windows. Then, the problem of optimally selecting between eager and lazy coalescing for concurrent queries is formulated as a 0-1 integer programming problem. Through extensive performance study, the two schemes are compared and the optimal selection is demonstrated.},
keywords={},
doi={10.1587/transinf.E94.D.489},
ISSN={1745-1361},
month={March},}
Copy
TY - JOUR
TI - Temporal Coalescing on Window Extents over Data Streams
T2 - IEICE TRANSACTIONS on Information
SP - 489
EP - 503
AU - Mohammed AL-KATEB
AU - Sasi Sekhar KUNTA
AU - Byung Suk LEE
PY - 2011
DO - 10.1587/transinf.E94.D.489
JO - IEICE TRANSACTIONS on Information
SN - 1745-1361
VL - E94-D
IS - 3
JA - IEICE TRANSACTIONS on Information
Y1 - March 2011
AB - This paper focuses on the coalescing operator applied to the processing of continuous queries with temporal functions and predicates over windowed data streams. Coalescing is a key operation enabling the evaluation of interval predicates and functions on temporal tuples. Applying this operation for temporal query processing on windowed streams brings the challenge of coalescing tuples in a window extent each time the window slides over the data stream. This coalescing becomes even more involving when some tuples arrive out of order. This paper distinguishes between eager coalescing and lazy coalescing, the two known coalescing schemes. The former coalesces tuples during window extent update and the latter does it during window extent scan. With these two schemes, the paper first presents algorithms for updating a window extent for both tuple-based and time-based windows. Then, the problem of optimally selecting between eager and lazy coalescing for concurrent queries is formulated as a 0-1 integer programming problem. Through extensive performance study, the two schemes are compared and the optimal selection is demonstrated.
ER -
English
