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ICDE
2011
IEEE
258views Database» more  ICDE 2011»
12 years 7 months ago
SystemML: Declarative machine learning on MapReduce
Abstract—MapReduce is emerging as a generic parallel programming paradigm for large clusters of machines. This trend combined with the growing need to run machine learning (ML) a...
Amol Ghoting, Rajasekar Krishnamurthy, Edwin P. D....
ICDE
2011
IEEE
265views Database» more  ICDE 2011»
12 years 7 months ago
RAFTing MapReduce: Fast recovery on the RAFT
MapReduce is a computing paradigm that has gained a lot of popularity as it allows non-expert users to easily run complex analytical tasks at very large-scale. At such scale, task...
Jorge-Arnulfo Quiané-Ruiz, Christoph Pinkel...
CORR
2011
Springer
259views Education» more  CORR 2011»
12 years 10 months ago
Automatic Optimization for MapReduce Programs
The MapReduce distributed programming framework has become popular, despite evidence that current implementations are inefficient, requiring far more hardware than a traditional r...
Eaman Jahani, Michael J. Cafarella, Christopher R&...
CLOUDCOM
2010
Springer
13 years 1 months ago
Evaluation of MapReduce for Gridding LIDAR Data
-- The MapReduce programming model, introduced by Google, has become popular over the past few years as a mechanism for processing large amounts of data, using sharednothing parall...
Sriram Krishnan, Chaitanya K. Baru, Christopher J....
PVLDB
2010
204views more  PVLDB 2010»
13 years 2 months ago
Cheetah: A High Performance, Custom Data Warehouse on Top of MapReduce
Large-scale data analysis has become increasingly important for many enterprises. Recently, a new distributed computing paradigm, called MapReduce, and its open source implementat...
Songting Chen
PVLDB
2010
178views more  PVLDB 2010»
13 years 2 months ago
Hadoop++: Making a Yellow Elephant Run Like a Cheetah (Without It Even Noticing)
MapReduce is a computing paradigm that has gained a lot of attention in recent years from industry and research. Unlike parallel DBMSs, MapReduce allows non-expert users to run co...
Jens Dittrich, Jorge-Arnulfo Quiané-Ruiz, A...
SCP
2008
150views more  SCP 2008»
13 years 3 months ago
Google's MapReduce programming model - Revisited
Google's MapReduce programming model serves for processing large data sets in a massively parallel manner. We deliver the first rigorous description of the model including it...
Ralf Lämmel
BMCBI
2010
135views more  BMCBI 2010»
13 years 3 months ago
MrsRF: an efficient MapReduce algorithm for analyzing large collections of evolutionary trees
Background: MapReduce is a parallel framework that has been used effectively to design largescale parallel applications for large computing clusters. In this paper, we evaluate th...
Suzanne Matthews, Tiffani L. Williams
HPDC
2010
IEEE
13 years 4 months ago
Twister: a runtime for iterative MapReduce
MapReduce programming model has simplified the implementation of many data parallel applications. The simplicity of the programming model and the quality of services provided by m...
Jaliya Ekanayake, Hui Li, Bingjing Zhang, Thilina ...
NSDI
2010
13 years 5 months ago
MapReduce Online
MapReduce is a popular framework for data-intensive distributed computing of batch jobs. To simplify fault tolerance, many implementations of MapReduce materialize the entire outp...
Tyson Condie, Neil Conway, Peter Alvaro, Joseph M....