Log Analysis with Hadoop MapReduce

Home Page
About
Submit A Journal
Submit A Conference
Submit Paper/Book
- Submit a Preprint
- Submit a Book
Contact

Journal of Emerging Computer Technologies
Volume:1 Issue:1
Log Analysis with Hadoop MapReduce

Log Analysis with Hadoop MapReduce

Authors : Gligor RİSTESKİ, Mihiri CHATHURİKA, Beyza ALİ, Atanas HRİSTOV

Pages : 1-5

View : 212 | Download : 44

Publication Date : 2021-06-30

Article Type : Research Paper

Abstract :Pretty much every part of life now results in the generation of data. Logs are documentation of events or records of system activities and are created automatically through IT systems. Log data analysis is a process of making sense of these records. Log data often grows quickly and the conventional database solutions run short for dealing with a large volume of log files. Hadoop, having a wide area of applications for Big Data analysis, provides a solution for this problem. In this study, Hadoop was installed on two virtual machines. Log files generated by a Python script were analyzed in order to evaluate the system activities. The aim was to validate the importance of Hadoop in meeting the challenge of dealing with Big Data. The performed experiments show that analyzing logs with Hadoop MapReduce makes the data processing and detection of malfunctions and defects faster and simpler.
Keywords : Hadoop, MapReduce, Big Data, log analysis, distributed file systems

ORIGINAL ARTICLE URL

* There may have been changes in the journal, article,conference, book, preprint etc. informations. Therefore, it would be appropriate to follow the information on the official page of the source. The information here is shared for informational purposes. IAD is not responsible for incorrect or missing information.