Presentation 1997/12/3
Storing a Large Time Sequenced Data within Disks
Hiroshi Sakai, Akihiko Nakase, Shigeru Oyanari,
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Abstract(in Japanese) (See Japanese page)
Abstract(in English) We propose a new method for storing large time sequenced data of several items which are measured at many points and are often default values. The new method uses an index file having a bitmap and item files each of which holds measured data of the corresponding item. An item file is a list of time sequenced data of each point having a filed size in the item file. The bitmap avoids holding a set of default values. The operations are limited to referring data, adding newly measured data, and deleting out-of-date data. Our experiment shows ten times faster data access and three times more effective disk space usage comparing with a conventional relational database management system.
Keyword(in Japanese) (See Japanese page)
Keyword(in English) Time sequenced data / Data storage / POS data / Data warehouse / Data mining
Paper # AI97-49
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Committee AI
Conference Date 1997/12/3(1days)
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Registration To Artificial Intelligence and Knowledge-Based Processing (AI)
Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) Storing a Large Time Sequenced Data within Disks
Sub Title (in English)
Keyword(1) Time sequenced data
Keyword(2) Data storage
Keyword(3) POS data
Keyword(4) Data warehouse
Keyword(5) Data mining
1st Author's Name Hiroshi Sakai
1st Author's Affiliation RWC Partnership Parallel Application Toshiba Laboratory()
2nd Author's Name Akihiko Nakase
2nd Author's Affiliation RWC Partnership Parallel Application Toshiba Laboratory
3rd Author's Name Shigeru Oyanari
3rd Author's Affiliation RWC Partnership Parallel Application Toshiba Laboratory
Date 1997/12/3
Paper # AI97-49
Volume (vol) vol.97
Number (no) 416
Page pp.pp.-
#Pages 6
Date of Issue