DocumentCode :
2080072
Title :
I/O-efficient statistical computing with RIOT
Author :
Zhang, Yi ; Zhang, Weiping ; Yang, Jun
Author_Institution :
Dept. of Comput. Sci., Duke Univ., Durham, NC, USA
fYear :
2010
fDate :
1-6 March 2010
Firstpage :
1157
Lastpage :
1160
Abstract :
Statistical analysis of massive data is becoming indispensable to science, commerce, and society today. Such analysis requires efficient, flexible storage support and special optimization techniques. In this demo, we present RIOT (R with I/O Transparency), a system that extends R, a popular computing environment for statistical data analysis. RIOT makes R programs I/O-efficient in a way transparent to users. It features a flexible array storage manager and an optimization engine suitable for statistical and numerical operations. RIOT also seamlessly integrates with external database systems, offering additional opportunities for processing data that reside in databases by blurring the boundary between database and host-language processing. This demo will show how statistical computation can be effectively and efficiently handled by RIOT.
Keywords :
input-output programs; optimisation; statistical analysis; I/O-efficient statistical computing; RIOT; external database systems; flexible array storage manager; host language processing; optimization techniques; statistical analysis; Adaptive arrays; Business; Computer science; Data analysis; Database systems; Libraries; MATLAB; Multidimensional systems; Spatial databases; Switches;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Data Engineering (ICDE), 2010 IEEE 26th International Conference on
Conference_Location :
Long Beach, CA
Print_ISBN :
978-1-4244-5445-7
Electronic_ISBN :
978-1-4244-5444-0
Type :
conf
DOI :
10.1109/ICDE.2010.5447819
Filename :
5447819
Link To Document :
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