UT Institute of Computer Science Graduation Theses Topics Registry

Organization

Data Group system

Abstract

With the emergence of the big data age, along with the data-centric and -intensive computing trend, the great amount of energy consumed by database systems has become a major concern in a society that pursues green information technology. Apache Hadoop framework supports the storing and processing of big data datasets using simple programming models. Today, in many compagnies Hadoop becoming the de facto standard for data collection and management. Research work on energy efficiency in the Hadoop ecosystem can be categorized into two approaches: software-based and hardware-based. The software approach covers Scheduling, data placement and resource management but does not make an in-depth analysis of the query processing system within Hadoop systems. The objective of this master thesis work is to analyze the operation of the Hadoop ecosystem during the execution of analytical queries in order to identify configurations along several dimensions (database type, storage engine, partitioning form, etc.) that can better optimize energy consumption.

Graduation Theses defence year

2022-2023

Supervisor

Simon Pierre DEMBELE

Spoken language (s)

English

Requirements for candidates

Level

Masters

Keywords

 

Name

Ahmed Awad

Phone

E-mail

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