Simulation of MapReduce Computations on a Cluster

Student: Orlov Nikita

Educational Programme: Applied Mathematics and Information Science (Bachelor)

Year of Graduation: 2020

MapReduce is an essential framework for data analysis and data processing. Many businesses and individuals use MapReduce to process server logs, build new data from an existing dataset. Therefore having an instrument to accurately predict MapReduce job execution time on a given set of servers is essential to building cost-efficient and powerful clusters. In this thesis, I propose an improved method for modelling MapReduce job execution time based on the testing user-provided job description and input data sample.

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