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Configuring SQL-based process mining for performance and storage optimisation

Title data

Schönig, Stefan ; Di Ciccio, Claudio ; Mendling, Jan:
Configuring SQL-based process mining for performance and storage optimisation.
In: Proceedings of the 34th ACM/SIGAPP Symposium on Applied Computing, SAC 2019, Limassol, Cyprus, April 8-12, 2019. - Limassol, Cyprus , 2019 . - pp. 94-97
ISBN 978-1-4503-5933-7
DOI: https://doi.org/10.1145/3297280.3297532

Abstract in another language

Process mining is the area of research that embraces the automateddiscovery, conformance checking and enhancement of process mod-els. Declarative process mining approaches offer capabilities to au-tomatically discover models of flexible processes from event logs.However, they often suffer from performance issues with real-lifeevent logs, especially when constraints to be discovered go beyonda standard repertoire of templates. By leveraging relational databaseperformance technology, a new approach based on SQL queryinghas been recently introduced, to improve performance though stillkeeping the nature of discovered constraints customisable. In thispaper, we provide an in-depth analysis of configuration parametersthat allow for a speed-up of the answering time and a decrease ofstorage space needed for query processing. Thereupon, we provideconfiguration recommendations for process mining with SQL onrelational databases.

Further data

Item Type: Article in a book
Refereed: Yes
Keywords: Declarative process mining; relational databases; SQL
Institutions of the University: Faculties > Faculty of Mathematics, Physics und Computer Science > Department of Computer Science > Chair Applied Computer Science IV > Chair Applied Computer Science IV - Univ.-Prof. Dr.-Ing. Stefan Jablonski
Result of work at the UBT: Yes
DDC Subjects: 000 Computer Science, information, general works > 004 Computer science
Date Deposited: 29 May 2019 09:23
Last Modified: 29 May 2019 09:23
URI: https://eref.uni-bayreuth.de/id/eprint/49142