Mapreduce: Simplified Data Processing on Clusters with Privacy Preserving By using Anonymization Techniques
Year: 2020
Type: article
Abstract: Computerized Data from various sources, such as remote sensors, cutting-edge sequencing of bioinformatics and high-performance instruments, are increasing at extremely high speeds. To keep analyzing through results for programming, facilities and measurements, The Researches have to use new procedures and techniques. Google's team started MapReduce programming system which aims to manipulate huge data sets in disseminated frameworks; this design lets software engineers create applications that are extremely valuable to large data processing. The motive of this paper is to explore MapReduce research techniques and to increase current research efforts to improve the execution of MapReduce and its capabilities.
Authors: Ashutosh Dixit, Nidhi Tyagi, Professor, MIET, Meerut
Language: English
Subfield: Information Systems
Field: Computer Science
Domain: Physical Sciences
Open Access status: diamond
OpenAlex ID: W4238106902