Presentation 2006-07-13
Data Lifetime Management Method in Stream Data Processing
Tsuneyuki IMAKI, Itaru NISHIZAWA,
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Abstract(in English) Emerging RFID technology and sensor network systems produce huge amount of data, and modern enterprise data processing systems must handle the huge amount of data in the real-time fashion. Stream data processing, which continuously processes the data in the real-time fashion, has proposed and accepted as a new data processing paradigm. Data lifetime notion is essential in the stream data processing because it requires extracting the target data from infinite data sequences using the notion. Negative Tuple Method (NT) and Direct Method (DT) have been proposed to manage the data lifetime. Although DT outperforms NT in the system throughput, it cannot be applied to some basic query processing operators due to its processing mechanism. This paper proposes a new data lifetime management method which extends DT to enable applying it to the basic query processing operators as the same as NT. Moreover, we have confirmed by experiments that our new data lifetime management method outperforms NT by 1.4-2.0 times in the system throughput.
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Keyword(in English) Stream / Window / Continuous Query / CQL
Paper # DE2006-86
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Committee DE
Conference Date 2006/7/6(1days)
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Registration To Data Engineering (DE)
Language JPN
Title (in Japanese) (See Japanese page)
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Title (in English) Data Lifetime Management Method in Stream Data Processing
Sub Title (in English)
Keyword(1) Stream
Keyword(2) Window
Keyword(3) Continuous Query
Keyword(4) CQL
1st Author's Name Tsuneyuki IMAKI
1st Author's Affiliation Hitachi, Ltd., Central Research Laboratory()
2nd Author's Name Itaru NISHIZAWA
2nd Author's Affiliation Hitachi, Ltd., Central Research Laboratory
Date 2006-07-13
Paper # DE2006-86
Volume (vol) vol.106
Number (no) 149
Page pp.pp.-
#Pages 6
Date of Issue