State-space optimization of ETL workflows

Simitsis, A; Vassiliadis, P; Sellis, T

dc.contributor.author	Simitsis, A	en
dc.contributor.author	Vassiliadis, P	en
dc.contributor.author	Sellis, T	en
dc.date.accessioned	2014-03-01T01:23:06Z
dc.date.available	2014-03-01T01:23:06Z
dc.date.issued	2005	en
dc.identifier.issn	1041-4347	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/16820
dc.subject	Data warehouse and repository	en
dc.subject	Database integration	en
dc.subject	Database management	en
dc.subject	Heterogeneous databases	en
dc.subject	Workflow management	en
dc.subject.classification	Computer Science, Artificial Intelligence	en
dc.subject.classification	Computer Science, Information Systems	en
dc.subject.classification	Engineering, Electrical & Electronic	en
dc.subject.other	Customization	en
dc.subject.other	Extraction-Transformation-loading (ETL) tools	en
dc.subject.other	Logical optimization	en
dc.subject.other	Algorithms	en
dc.subject.other	Computer software	en
dc.subject.other	Data warehouses	en
dc.subject.other	Formal logic	en
dc.subject.other	Mathematical transformations	en
dc.subject.other	Optimization	en
dc.subject.other	State space methods	en
dc.title	State-space optimization of ETL workflows	en
heal.type	journalArticle	en
heal.identifier.primary	10.1109/TKDE.2005.169	en
heal.identifier.secondary	http://dx.doi.org/10.1109/TKDE.2005.169	en
heal.language	English	en
heal.publicationDate	2005	en
heal.abstract	Extraction-Transformation-Loading (ETL) tools are pieces of software responsible for the extraction of data from several sources, their cleansing, customization, and insertion into a data warehouse. In this paper, we delve into the logical optimization of ETL processes, modeling it as a state-space search problem. We consider each ETL workflow as a state and fabricate the state space through a set of correct state transitions. Moreover, we provide an exhaustive and two heuristic algorithms toward the minimization of the execution cost of an ETL workflow. The heuristic algorithm with greedy characteristics significantly outperforms the other two algorithms for a large set of experimental cases. © 2005 IEEE.	en
heal.publisher	IEEE COMPUTER SOC	en
heal.journalName	IEEE Transactions on Knowledge and Data Engineering	en
dc.identifier.doi	10.1109/TKDE.2005.169	en
dc.identifier.isi	ISI:000231274600008	en
dc.identifier.volume	17	en
dc.identifier.issue	10	en
dc.identifier.spage	1404	en
dc.identifier.epage	1419	en