Search: onr:"swepub:oai:DiVA.org:uu-78095" > Customizable parall...
Fältnamn | Indikatorer | Metadata |
---|---|---|
000 | 02467naa a2200301 4500 | |
001 | oai:DiVA.org:uu-78095 | |
003 | SwePub | |
008 | 061221s2005 | |||||||||||000 ||eng| | |
024 | 7 | a https://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-780952 URI |
040 | a (SwePub)uu | |
041 | a engb eng | |
042 | 9 SwePub | |
072 | 7 | a ref2 swepub-contenttype |
072 | 7 | a kon2 swepub-publicationtype |
100 | 1 | a Ivanova, Milenau Uppsala universitet,Institutionen för informationsteknologi,Datalogi,UDBL4 aut |
245 | 1 0 | a Customizable parallel execution of scientific stream queries |
264 | 1 | c 2005 |
338 | a print2 rdacarrier | |
520 | a Scientific applications require processing high-volume on-line streams of numerical data from instruments and simulations. We present an extensible stream database system that allows scalable and flexible continuous queries on such streams. Application dependent streams and query functions are defined through an object-relational model. Distributed execution plans for continuous queries are described as high-level data flow distribution templates. Using a generic template we define two partitioning strategies for scalable parallel execution of expensive stream queries: window split and window distribute. Window split provides operators for parallel execution of query functions by reducing the size of stream data units using application dependent functions as parameters. By contrast, window distribute provides operators for customized distribution of entire data units without reducing their size. We evaluate these strategies for a typical high volume scientific stream application and show that window split is favorable when expensive queries are executed on limited resources, while window distribution is better otherwise. | |
650 | 7 | a NATURVETENSKAPx Data- och informationsvetenskapx Datavetenskap0 (SwePub)102012 hsv//swe |
650 | 7 | a NATURAL SCIENCESx Computer and Information Sciencesx Computer Sciences0 (SwePub)102012 hsv//eng |
653 | a Databases | |
653 | a Databaser | |
700 | 1 | a Risch, Toreu Uppsala universitet,Institutionen för informationsteknologi,Datalogi,UDBL4 aut0 (Swepub:uu)torerisc |
710 | 2 | a Uppsala universitetb Institutionen för informationsteknologi4 org |
773 | 0 | t 31st International Conference on Very Large Data Bases |
856 | 4 | u http://www.vldb2005.org/program/paper/tue/p157-ivanova.pdf |
856 | 4 8 | u https://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-78095 |
Kungliga biblioteket hanterar dina personuppgifter i enlighet med EU:s dataskyddsförordning (2018), GDPR. Läs mer om hur det funkar här.
Så här hanterar KB dina uppgifter vid användning av denna tjänst.