Users of MapReduce often run into performance problems when they scale up their workloads. Many of the problems they encounter can be overcome by applying techniques learned from ...
Avrilia Floratou, Jignesh M. Patel, Eugene J. Shek...
Hadoop is a software framework supporting the Map/Reduce programming model. It relies on the Hadoop Distributed File System (HDFS) as its primary storage system. The efficiency of ...
Bogdan Nicolae, Diana Moise, Gabriel Antoniu, Luc ...
The Hadoop filesystem is a large scale distributed filesystem used to manage and quickly process extremely large data sets. We want to utilize Hadoop to assist with dataintensive ...
The rise of ad-hoc data-intensive computing has led to the development of data-parallel programming systems such as Map/Reduce and Hadoop, which achieve scalability by tightly cou...
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...
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...
In this paper we present the design of a modern course in cluster computing and large-scale data processing. The defining differences between this and previously published designs...
Aaron Kimball, Sierra Michels-Slettvet, Christophe...
Hadoop is a reference software framework supporting the Map/Reduce programming model. It relies on the Hadoop Distributed File System (HDFS) as its primary storage system. Althoug...
Parallel dataflow programs generate enormous amounts of distributed data that are short-lived, yet are critical for completion of the job and for good run-time performance. We ca...
Steven Y. Ko, Imranul Hoque, Brian Cho, Indranil G...