Quotation Stefan, Schönig, Di Ciccio, Claudio, Mendling, Jan. 2019. Configuring SQL-based process mining for performance and storage optimisation. In Proceedings of the 34th ACM/SIGAPP Symposium on Applied Computing, SAC 2019, Hrsg. Chih-Cheng Hung and George A. Papadopoulos, 94-97. Limassol, Cyprus: ACM Press.




Process mining is the area of research that embraces the automated discovery, conformance checking and enhancement of process models. Declarative process mining approaches offer capabilities to automatically discover models of flexible processes from event logs. However, they often suffer from performance issues with real-life event logs, especially when constraints to be discovered go beyond a standard repertoire of templates. By leveraging relational database performance technology, a new approach based on SQL querying has been recently introduced, to improve performance though still keeping the nature of discovered constraints customisable. In this paper, we provide an in-depth analysis of configuration parameters that allow for a speed-up of the answering time and a decrease of storage space needed for query processing. Thereupon, we provide configuration recommendations for process mining with SQL on relational databases.


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Publication's profile

Status of publication Published
Affiliation WU
Type of publication Contribution to conference proceedings
Language English
Title Configuring SQL-based process mining for performance and storage optimisation
Title of whole publication Proceedings of the 34th ACM/SIGAPP Symposium on Applied Computing, SAC 2019
Editor Chih-Cheng Hung and George A. Papadopoulos
Page from 94
Page to 97
Location Limassol, Cyprus
Publisher ACM Press
Year 2019
URL https://doi.org/10.1145/3297280.3297532
Open Access N


Cyber-Physical Social Systems for City-wide Infrastructures
Di Ciccio, Claudio (Former researcher)
Mendling, Jan (Details)
Stefan, Schönig (University of Bayreuth, Germany)
Institute for Data, Process and Knowledge Management (AE Sabou) (Details)
Research areas (ÖSTAT Classification 'Statistik Austria')
1105 Computer software (Details)
1108 Informatics (Details)
1109 Information and data processing (Details)
5306 Business data processing (Details)
5367 Management information systems (Details)
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