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» MapReduce: Simplified Data Processing on Large Clusters
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PVLDB
2010
146views more  PVLDB 2010»
13 years 1 months ago
HaLoop: Efficient Iterative Data Processing on Large Clusters
The growing demand for large-scale data mining and data analysis applications has led both industry and academia to design new types of highly scalable data-intensive computing pl...
Yingyi Bu, Bill Howe, Magdalena Balazinska, Michae...
IPPS
2010
IEEE
13 years 4 months ago
Improving MapReduce performance through data placement in heterogeneous Hadoop clusters
MapReduce has become an important distributed processing model for large-scale data-intensive applications like data mining and web indexing. Hadoop
Jiong Xie, Shu Yin, Xiaojun Ruan, Zhiyang Ding, Yu...
SIGMOD
2011
ACM
248views Database» more  SIGMOD 2011»
12 years 9 months ago
Llama: leveraging columnar storage for scalable join processing in the MapReduce framework
To achieve high reliability and scalability, most large-scale data warehouse systems have adopted the cluster-based architecture. In this paper, we propose the design of a new clu...
Yuting Lin, Divyakant Agrawal, Chun Chen, Beng Chi...
EDBT
2010
ACM
188views Database» more  EDBT 2010»
13 years 9 months ago
DEDUCE: at the intersection of MapReduce and stream processing
MapReduce and stream processing are two emerging, but different, paradigms for analyzing, processing and making sense of large volumes of modern day data. While MapReduce offers t...
Vibhore Kumar, Henrique Andrade, Bugra Gedik, Kun-...
CLOUDCOM
2010
Springer
13 years 3 months ago
Voronoi-Based Geospatial Query Processing with MapReduce
Geospatial queries (GQ) have been used in a wide variety of applications such as decision support systems, profile-based marketing, bioinformatics and GIS. Most of the existing qu...
Afsin Akdogan, Ugur Demiryurek, Farnoush Banaei Ka...