Assessing Big Data SQL Frameworks for Analyzing Event Logs

Markku Hinkka; Teemu Lehto; Keijo Heljanko

doi:10.1109/PDP.2016.26

Assessing Big Data SQL Frameworks for Analyzing Event Logs

Markku Hinkka, Teemu Lehto, Keijo Heljanko

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Scientific › peer-review

6 Citations (Scopus)

Abstract

Performing Process Mining by analyzing event logs generated by various systems is a very computation and I/O intensive task. Distributed computing and Big Data processing frameworks make it possible to distribute all kinds of computation tasks to multiple computers instead of performing the whole task in a single computer. This paper assesses whether contemporary structured query language (SQL) supporting Big Data processing frameworks are mature enough to be efficiently used to distribute computation of two central Process Mining tasks to two dissimilar clusters of computers providing BPM as a service in the cloud. Tests are performed by using a novel automatic testing framework detailed in this paper and its supporting materials. As a result, an assessment is made on how well selected Big Data processing frameworks manage to process and to parallelize the analysis work required by Process Mining tasks.

Original language	English
Title of host publication	Proceedings - 24th Euromicro International Conference on Parallel, Distributed, and Network-Based Processing, PDP 2016
Publisher	IEEE
Pages	101-108
Number of pages	8
ISBN (Print)	9781467387750
DOIs	https://doi.org/10.1109/PDP.2016.26
Publication status	Published - 31 Mar 2016
MoE publication type	A4 Article in a conference publication
Event	Euromicro International Conference on Parallel, Distributed, and Network-Based Processing - Heraklion, Greece Duration: 17 Feb 2016 → 19 Feb 2016 Conference number: 24

Conference

Conference	Euromicro International Conference on Parallel, Distributed, and Network-Based Processing
Abbreviated title	PDP
Country/Territory	Greece
City	Heraklion
Period	17/02/2016 → 19/02/2016

Keywords

automatic business process discovery
distributed computing framework
distributed SQL
event log analysis
Hadoop
Hive
Presto
process mining
Spark

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10.1109/PDP.2016.26

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@inproceedings{38232fe92fcc41afbb679e66243c12f8,

title = "Assessing Big Data SQL Frameworks for Analyzing Event Logs",

abstract = "Performing Process Mining by analyzing event logs generated by various systems is a very computation and I/O intensive task. Distributed computing and Big Data processing frameworks make it possible to distribute all kinds of computation tasks to multiple computers instead of performing the whole task in a single computer. This paper assesses whether contemporary structured query language (SQL) supporting Big Data processing frameworks are mature enough to be efficiently used to distribute computation of two central Process Mining tasks to two dissimilar clusters of computers providing BPM as a service in the cloud. Tests are performed by using a novel automatic testing framework detailed in this paper and its supporting materials. As a result, an assessment is made on how well selected Big Data processing frameworks manage to process and to parallelize the analysis work required by Process Mining tasks.",

keywords = "automatic business process discovery, distributed computing framework, distributed SQL, event log analysis, Hadoop, Hive, Presto, process mining, Spark",

author = "Markku Hinkka and Teemu Lehto and Keijo Heljanko",

year = "2016",

month = mar,

day = "31",

doi = "10.1109/PDP.2016.26",

language = "English",

isbn = "9781467387750",

pages = "101--108",

booktitle = "Proceedings - 24th Euromicro International Conference on Parallel, Distributed, and Network-Based Processing, PDP 2016",

publisher = "IEEE",

address = "United States",

note = "Euromicro International Conference on Parallel, Distributed, and Network-Based Processing , PDP ; Conference date: 17-02-2016 Through 19-02-2016",

}

Hinkka, M, Lehto, T & Heljanko, K 2016, Assessing Big Data SQL Frameworks for Analyzing Event Logs. in Proceedings - 24th Euromicro International Conference on Parallel, Distributed, and Network-Based Processing, PDP 2016., 7445319, IEEE, pp. 101-108, Euromicro International Conference on Parallel, Distributed, and Network-Based Processing , Heraklion, Greece, 17/02/2016. https://doi.org/10.1109/PDP.2016.26

Assessing Big Data SQL Frameworks for Analyzing Event Logs. / Hinkka, Markku; Lehto, Teemu; Heljanko, Keijo.

Proceedings - 24th Euromicro International Conference on Parallel, Distributed, and Network-Based Processing, PDP 2016. IEEE, 2016. p. 101-108 7445319.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Scientific › peer-review

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Assessing Big Data SQL Frameworks for Analyzing Event Logs

Abstract

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Keywords

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Science-IT

Cite this

Assessing Big Data SQL Frameworks for Analyzing Event Logs

Abstract

Conference

Keywords

Access to Document

OpenUrl availability

Other files and links

Fingerprint

Equipment

Science-IT

Cite this