Diag-Join: An Opportunistic Join Algorithm for 1:N Relationships


Helmer, Sven ; Westmann, Till ; Moerkotte, Guido


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URL: http://ub-madoc.bib.uni-mannheim.de/788
URN: urn:nbn:de:bsz:180-madoc-7880
Document Type: Working paper
Year of publication: 1997
Publication language: English
Institution: School of Business Informatics and Mathematics > Sonstige - Fakultät für Mathematik und Informatik
MADOC publication series: Veröffentlichungen der Fakultät für Mathematik und Informatik > Institut für Informatik > Technical Reports
Subject: 004 Computer science, internet
Subject headings (SWD): Join-Operation , Data-Warehouse-Konzept
Keywords (English): join algorithm , Data-Warehousing
Abstract: Time of creation is one of the predominant (often implicit) clustering strategies found not only in Data Warehouse systems: line items are created together with their corresponding order, objects are created together with their subparts and so on. The newly created data is then appended to the existing data. We present a new join algorithm, called Diag-Join, which exploits time-of-creation clustering. The performance evaluation reveals its superiority over standard join algorithms like nested-loop join and GRACE hash join. We also present an analytical cost model for Diag-Join.
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Helmer, Sven ; Westmann, Till ; Moerkotte, Guido (1997) Diag-Join: An Opportunistic Join Algorithm for 1:N Relationships. Open Access [Working paper]
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