The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. ex. Some numerals are expressed as "XNUMX".
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The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. Copyrights notice
Este artigo enfoca o operador coalescente aplicado ao processamento de consultas contínuas com funções temporais e predicados em fluxos de dados em janelas. A coalescência é uma operação chave que permite a avaliação de predicados e funções de intervalo em tuplas temporais. Aplicar esta operação para processamento de consulta temporal em fluxos de janela traz o desafio de unir tuplas em uma extensão de janela cada vez que a janela desliza sobre o fluxo de dados. Essa união torna-se ainda mais envolvente quando algumas tuplas chegam fora de ordem. Este artigo distingue entre coalescência ansiosa e coalescência preguiçosa, os dois esquemas de coalescência conhecidos. O primeiro agrupa tuplas durante a atualização da extensão da janela e o último faz isso durante a varredura da extensão da janela. Com esses dois esquemas, o artigo apresenta primeiro algoritmos para atualizar a extensão de uma janela tanto para janelas baseadas em tuplas quanto para janelas baseadas em tempo. Então, o problema de selecionar de maneira ideal entre coalescência ansiosa e preguiçosa para consultas simultâneas é formulado como um problema de programação inteira 0-1. Através de extenso estudo de desempenho, os dois esquemas são comparados e a seleção ideal é demonstrada.
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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
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@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},}
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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 -