WebLog Analyzer Using Big Data Technology (Record no. 4995)

MARC details
000 -LEADER
fixed length control field 02453nam a22001817a 4500
003 - CONTROL NUMBER IDENTIFIER
control field OSt
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20220107122809.0
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 160316b xxu||||| |||| 00| 0 eng d
040 ## - CATALOGING SOURCE
Transcribing agency
100 ## - MAIN ENTRY--PERSONAL NAME
Personal name Aaditya Reji George (93613000 )
9 (RLIN) 8529
245 ## - TITLE STATEMENT
Title WebLog Analyzer Using Big Data Technology
502 ## - DISSERTATION NOTE
Degree type Master of Science in Computer Science & Information Security
Name of granting institution 2013-2015
Year degree granted EXT
-- Meraj Uddin
-- Rakesh Kumar R G
Miscellaneous information "Mirox Cyber Security & Technology Pvt Ltd "
520 ## - SUMMARY, ETC.
Summary, etc. In today’s Internet world, log file analysis is becoming a necessary task for analyzing the customer’s behavior in order to improve advertising and sales as well as for datasets like environment, medical, banking system it is important to analyze the log data to get required knowledge from it. Web mining is the process of discovering the knowledge from the web data. Log files are getting generated very fast at the rate of 1-10 Mb/s per machine, a single data center can generate tens of terabytes of log data in a day. These datasets are huge. In order to analyze such large datasets we need parallel processing system and reliable data storage mechanism. Virtual database system is an effective solution for integrating the data but it becomes inefficient for large datasets. The Hadoop framework provides reliable data storage by Hadoop Distributed File System and MapReduce programming model which is a parallel processing system for large datasets. Hadoop distributed file system breaks up input data and sends fractions of the original data to several machines in Hadoop cluster to hold blocks of data. This mechanism helps to process log data in parallel using all the machines in the hadoop cluster and computes result efficiently. The overall objective of this project is to analyze System Log of Internal organization. Log Files contain list of activities that can be a response to any request which is being occurred on the system server or any hosted application. These log files may resides in the same system server. Each individual request is listed on a separate line in a log file, called a log entry. The aim of a log file is to keep track of what is going on with the system server/application. Analyzing these log files can give lots of insights that help understand traffic patterns, user activity, Security breaks, user’s interest etc. <br/><br/>
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element DBMS
9 (RLIN) 8530
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element HADOOP
9 (RLIN) 8531
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element BIG DATA
9 (RLIN) 8532
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Source of classification or shelving scheme Dewey Decimal Classification
Koha item type
Holdings
Withdrawn status Lost status Source of classification or shelving scheme Damaged status Not for loan Home library Current library Date acquired Total Checkouts Barcode Date last seen Price effective from Koha item type
    Dewey Decimal Classification     IIITM-K Kerala University of Digital Sciences, Innovation and Technology Knowledge Centre 16/03/2016   R-699 16/03/2016 16/03/2016 Project Reports
    Dewey Decimal Classification     IIITM-K Kerala University of Digital Sciences, Innovation and Technology Knowledge Centre 08/02/2017   R-922 08/02/2017 08/02/2017 Project Reports