Big Data Performance Analysis In Apache And Internet Information Services
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International Journal of Computer Trends and Technology (IJCTT) |  |
| © 2019 by IJCTT Journal | ||
| Volume-67 Issue-11 |
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| Year of Publication : 2019 | ||
| Authors : Mohammed M. A , Bartholomew E | ||
| DOI : 10.14445/22312803/IJCTT-V67I11P103 |
MLA Style:Mohammed M. A , Bartholomew E "Big Data Performance Analysis In Apache And Internet Information Services," International Journal of Computer Trends and Technology 67.11 (2019):14-17.
APA Style Mohammed M. A , Bartholomew E. Big Data Performance Analysis In Apache And Internet Information Services International Journal of Computer Trends and Technology, 67(11),14-17.
Abstract
The goal of this study is to identify the impacts of big data on server performance, how it is being used and the amount of processing power it consumes from the server. Big data handling system individually on different servers using integrated software tools. In this study, data were captured and analyzed in order to gain actionable insights from the data at a much lower cost. The study uses the metrics (Response Time, Throughput, Computer Resources, Availability, Data Compressibility and Bandwidth) and main techniques which include Analysis modeling, Simulation and Measurement. The results of this analysis offer researchers with tool to predetermine true expectations from the big data. This will allow for more evaluation of big data and may direct future research on its performance on web servers. By identifying big data performance on servers, we will eliminate the assumption of server barriers. The performance analysis covers the volume of data, variety of types of data and the speed at which the data must be must processed. The findings may be useful for business people, consumer companies, massive big data companies, media, private sector, retail banking, government, individuals and researchers. This was further implemented using VB.NET.
Reference
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Keywords
Big Data, Server, Performance, Analysis, XAMPP, SSMS, VB.NET, APACHE, IIS, NGINX.