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On the performance projectability of MapReduce
4th IEEE International Conference on Cloud Computing Technology and Science Proceedings, 2012A key challenge faced by users of public clouds today is how to request for the right amount of resources in the production datacenter that satisfies a target performance for a given cloud application. An obvious approach is to develop a performance model for a class of applications such as MapReduce.
Di Xie +2 more
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2009 Third IEEE International Symposium on Theoretical Aspects of Software Engineering, 2009
As a programming model, MapReduce is implied for easier processing and generating large cluster of distributed data sets. We use CSP framework to model MapReduce system through which the parallelization of the computation and the distribution of data across multiple machines can be reflected.
Wen Su +3 more
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As a programming model, MapReduce is implied for easier processing and generating large cluster of distributed data sets. We use CSP framework to model MapReduce system through which the parallelization of the computation and the distribution of data across multiple machines can be reflected.
Wen Su +3 more
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Proceedings of the 2013 ACM SIGMOD International Conference on Management of Data, 2013
MapReduce has become a dominant parallel computing paradigm for big data, i.e., colossal datasets at the scale of tera-bytes or higher. Ideally, a MapReduce system should achieve a high degree of load balancing among the participating machines, and minimize the space usage, CPU and I/O time, and network transfer at each machine.
Yufei Tao 0001 +2 more
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MapReduce has become a dominant parallel computing paradigm for big data, i.e., colossal datasets at the scale of tera-bytes or higher. Ideally, a MapReduce system should achieve a high degree of load balancing among the participating machines, and minimize the space usage, CPU and I/O time, and network transfer at each machine.
Yufei Tao 0001 +2 more
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Proceedings of the 25th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, 2017
This paper provides the first attempt for a full-fledged query optimizer for MapReduce-based spatial join algorithms. The optimizer develops its own taxonomy that covers almost all possible ways of doing a spatial join for any two input datasets. The optimizer comes in two flavors; cost-based and rule-based.
Ibrahim Sabek, Mohamed F. Mokbel
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This paper provides the first attempt for a full-fledged query optimizer for MapReduce-based spatial join algorithms. The optimizer develops its own taxonomy that covers almost all possible ways of doing a spatial join for any two input datasets. The optimizer comes in two flavors; cost-based and rule-based.
Ibrahim Sabek, Mohamed F. Mokbel
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A Survey on MapReduce Implementations
International Journal of Cloud Applications and Computing, 2016A distinguished successful platform for parallel data processing MapReduce is attracting a significant momentum from both academia and industry as the volume of data to capture, transform, and analyse grows rapidly. Although MapReduce is used in many applications to analyse large scale data sets, there is still a lot of debate among scientists and ...
Amer Al-Badarneh +2 more
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Implementing MapReduce with MSVL
2018This paper presents an approach to implementing MapReduce processes with Modeling Simulation and Verification Language (MSVL). This facilitates programmers not only to deal with large data sets but also to verify properties of programs in a convenient way.
Nan Zhang 0001 +4 more
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Communications of the ACM, 2010
MapReduce advantages over parallel databases include storage-system independence and fine-grain fault tolerance for large jobs.
Jeffrey Dean, Sanjay Ghemawat
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MapReduce advantages over parallel databases include storage-system independence and fine-grain fault tolerance for large jobs.
Jeffrey Dean, Sanjay Ghemawat
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Private Searching on MapReduce
2010In this paper, a private searching protocol on MapReduce is introduced and formalized within the Mapping-Filtering-Reducing framework. The idea behind of our construction is that a map function Map is activated to generate (key, value) pairs; an intermedial filtering protocol is invoked to filter (key, value) pairs according to a query criteria; a ...
Huafei Zhu, Feng Bao 0001
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Assessing MapReduce for Internet Computing: A Comparison of Hadoop and BitDew-MapReduce
2012 ACM/IEEE 13th International Conference on Grid Computing, 2012MapReduce is emerging as an important programming model for data-intensive application. Adapting this model to desktop grid would allow taking advantage of the vast amount of computing power and distributed storage to execute new range of application able to process enormous amount of data.
Lu, Lu +3 more
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Proceedings of the VLDB Endowment, 2010
MapReduce has been widely used for large-scale data analysis in the Cloud. The system is well recognized for its elastic scalability and fine-grained fault tolerance although its performance has been noted to be suboptimal in the database context. According to a recent study [19], Hadoop, an open source implementation of MapReduce, is slower than two ...
Jiang, D., Ooi, B.C., Shi, L., Wu, S.
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MapReduce has been widely used for large-scale data analysis in the Cloud. The system is well recognized for its elastic scalability and fine-grained fault tolerance although its performance has been noted to be suboptimal in the database context. According to a recent study [19], Hadoop, an open source implementation of MapReduce, is slower than two ...
Jiang, D., Ooi, B.C., Shi, L., Wu, S.
openaire +1 more source