Open AccessSurvey on Online Log Parsers
Author(s) -
S Tejaswini,
Azra Nasreen
Publication year - 2021
Publication title -
international journal of engineering and advanced technology
Language(s) - English
Resource type - Journals
ISSN - 2249-8958
DOI - 10.35940/ijeat.e2816.0610521
Subject(s) - parsing , computer science , leaps , process (computing) , constant (computer programming) , template , base (topology) , software , data mining , artificial intelligence , programming language , mathematical analysis , mathematics , financial economics , economics
Technological dependence is growing in leaps andbounds as days progress. As a result, software applications arerequired to be up and running at all times without fail. Thehealth and safety of these applications need to be monitoredregularly by theuse of constant logging of any faults that occurat their runtime executions. Log analysis techniques areapplied to recorded logsto obtain a better overview of how tohandle failures and health deterioration. Before thesealgorithms can be utilized in practice, the raw unstructured logsneed to be converted into structured log events. This process isperformed by log parsers, which are accessible in two differentmodes – offline and online. While offline log parsers have a predefined knowledge base containing templates and conversionrules, online log parsers learn new templates on the job. Thispaper focuses on surveying and creating a comparative study ononline log parses by analysing the type of technique used,efficiency and accuracy of the parser on a given dataset, timecomplexity, and their effectiveness in motivating applications.