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» MapReduce: Simplified Data Processing on Large Clusters
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OSDI
2004
ACM
14 years 5 months ago
MapReduce: Simplified Data Processing on Large Clusters
MapReduce is a programming model and an associated implementation for processing and generating large data sets. Users specify a map function that processes a key/value pair to ge...
Jeffrey Dean, Sanjay Ghemawat
SIGMOD
2007
ACM
190views Database» more  SIGMOD 2007»
14 years 5 months ago
Map-reduce-merge: simplified relational data processing on large clusters
Map-Reduce is a programming model that enables easy development of scalable parallel applications to process vast amounts of data on large clusters of commodity machines. Through ...
Hung-chih Yang, Ali Dasdan, Ruey-Lung Hsiao, Dougl...
ICPADS
2010
IEEE
13 years 3 months ago
Enhancing MapReduce via Asynchronous Data Processing
The MapReduce programming model simplifies large-scale data processing on commodity clusters by having users specify a map function that processes input key/value pairs to generate...
Marwa Elteir, Heshan Lin, Wu-chun Feng
EDBT
2012
ACM
306views Database» more  EDBT 2012»
11 years 7 months ago
Clydesdale: structured data processing on MapReduce
MapReduce has emerged as a promising architecture for large scale data analytics on commodity clusters. The rapid adoption of Hive, a SQL-like data processing language on Hadoop (...
Tim Kaldewey, Eugene J. Shekita, Sandeep Tata
JDCTA
2010
464views more  JDCTA 2010»
12 years 12 months ago
A New Agglomerative Hierarchical Clustering Algorithm Implementation based on the Map Reduce Framework
Text clustering is one of the difficult and hot research fields in the text mining research. Combing Map Reduce framework and the neuron initialization method of VPSOM (vector pre...
Hui Gao, Jun Jiang, Li She, Yan Fu