Practical Multi-pattern Matching Approach for Fast and Scalable
Log Abstraction

D 2016

Practical Multi-pattern Matching Approach for Fast and Scalable Log Abstraction

TOVARŇÁK, Daniel

Basic information

Original name

Practical Multi-pattern Matching Approach for Fast and Scalable Log Abstraction

Authors

TOVARŇÁK, Daniel (203 Czech Republic, guarantor, belonging to the institution)

Edition

Lisbon, Portugal, ICSOFT-EA 2016 - Proceedings of the 11th International Joint Conference on Software Technologies, p. 319-329, 11 pp. 2016

Publisher

SCITEPRESS

Other information

Language

English

Type of outcome

Stať ve sborníku

Field of Study

10201 Computer sciences, information science, bioinformatics

Confidentiality degree

není předmětem státního či obchodního tajemství

Publication form

printed version "print"

References:

URL

RIV identification code

RIV/00216224:14330/16:00091170

Organization unit

Faculty of Informatics

ISBN

978-989-758-194-6

DOI

http://dx.doi.org/10.5220/0006006603190329

UT WoS

000391095600037

Keywords in English

Log Processing; Pattern Matching; Log Abstraction; Big Data

Abstract

V originále

Log abstraction, i.e. the separation of static and dynamic part of log message, is becoming an indispensable task when processing logs generated by large enterprise systems and networks. In practice, the log message types are described via regex matching patterns that are in turn used to actually facilitate the abstraction process. Although the area of multi-regex matching is well studied, there is a lack of suitable practical implementations available for common programming languages. In this paper we present an alternative approach to multi-pattern matching for the purposes of log abstraction that is based on a trie-like data structure we refer to as regex trie. REtrie is easy to implement and the real world experiments show its scalability and good performance even for thousands of matching patterns.

Citovat

TOVARŇÁK, Daniel. Practical Multi-pattern Matching Approach for Fast and Scalable Log Abstraction. In ICSOFT-EA 2016 - Proceedings of the 11th International Joint Conference on Software Technologies. Lisbon, Portugal: SCITEPRESS, 2016, p. 319-329. ISBN 978-989-758-194-6. Available from: https://dx.doi.org/10.5220/0006006603190329.

@inproceedings{1356567,
   author = {Tovarňák, Daniel},
   address = {Lisbon, Portugal},
   booktitle = {ICSOFT-EA 2016 - Proceedings of the 11th International Joint Conference on Software Technologies},
   doi = {http://dx.doi.org/10.5220/0006006603190329},
   keywords = {Log Processing; Pattern Matching; Log Abstraction; Big Data},
   howpublished = {tištěná verze "print"},
   language = {eng},
   location = {Lisbon, Portugal},
   isbn = {978-989-758-194-6},
   pages = {319-329},
   publisher = {SCITEPRESS},
   title = {Practical Multi-pattern Matching Approach for Fast and Scalable Log Abstraction},
   url = {http://www.scitepress.org/DigitalLibrary/PublicationsDetail.aspx?ID=SFHlGUrQnPo=&t=1},
   year = {2016}
}

TY  - JOUR
ID  - 1356567
AU  - Tovarňák, Daniel
PY  - 2016
TI  - Practical Multi-pattern Matching Approach for Fast and Scalable Log Abstraction
PB  - SCITEPRESS
CY  - Lisbon, Portugal
SN  - 9789897581946
KW  - Log Processing
KW  - Pattern Matching
KW  - Log Abstraction
KW  - Big Data
UR  - http://www.scitepress.org/DigitalLibrary/PublicationsDetail.aspx?ID=SFHlGUrQnPo=&t=1
N2  - Log abstraction, i.e. the separation of static and dynamic part of log message, is becoming an indispensable task when processing logs generated by large enterprise systems and networks. In practice, the log message types are described via regex matching patterns that are in turn used to actually facilitate the abstraction process. Although the area of multi-regex matching is well studied, there is a lack of suitable practical implementations available for common programming languages. In this paper we present an alternative approach to multi-pattern matching for the purposes of log abstraction that is based on a trie-like data structure we refer to as regex trie. REtrie is easy to implement and the real world experiments show its scalability and good performance even for thousands of matching patterns.
ER  -

TOVARŇÁK, Daniel. Practical Multi-pattern Matching Approach for Fast and Scalable Log Abstraction. In \textit{ICSOFT-EA 2016 - Proceedings of the 11th International Joint Conference on Software Technologies}. Lisbon, Portugal: SCITEPRESS, 2016, p.~319-329. ISBN~978-989-758-194-6. Available from: https://dx.doi.org/10.5220/0006006603190329.

Detailed Information on Publication Record