ITM Web Conf.
Volume 26, 20192018 International Conference on Computer Science and Education Technology (CSET 2018)
|Number of page(s)||4|
|Section||Modeling and Simulation|
|Published online||04 February 2019|
Research on Computing Efficiency of MapReduce in Big Data Environment
School of Information, Yunnan University of Finance and Economics, Kunming, 650221, China
a Corresponding author: firstname.lastname@example.org
The emergence of big data has brought a great impact on traditional computing mode, the distributed computing framework represented by MapReduce has become an important solution to this problem. Based on the big data, this paper deeply studies the principle and framework of MapReduce programming. On the basis of mastering the principle and framework of MapReduce programming, the time consumption of distributed computing framework MapReduce and traditional computing model is compared with concrete programming experiments. The experiment shows that MapReduce has great advantages in large data volume.
© The Authors, published by EDP Sciences, 2019
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.