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Title
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Scale independence : using small data to answer queries on big data (invited talk)
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Author
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Abstract
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| Large datasets introduce challenges to the scalability of query answering. Given a query Q and a dataset D, it is often prohibitively costly to compute the query answers Q(D) when D is big. To this end, one may want to use heuristics, quick and dirty algorithms which return approximate answers. However, in many applications it is a must to find exact query answers. So, how can we efficiently compute Q(D) when D is big or when we only have limited resources? One idea is to find a small subset DQ of D such that Q(DQ) = Q(D) where the size of DQ is independent of the size of the underlying dataset D. Intuitively, when such a DQ can be found for a query Q, the query is said to be scale independent [1, 2, 9]. Indeed, for answering such queries the size of the underlying database does not matter, i.e., query processing is independent of the scale of the database. In this talk, I will survey various formalisms that enable large classes of queries to be scale independent. These formalisms primarily rely on the availability of access constraints, a combination of indexes and cardinality constraints, on the data [8, 9]. We will take a closer look at how, in the presence of such constraints, queries can often be compiled into efficient query plans that access a bounded amount data [6, 8], and how these techniques relate to query processing in the presence of access patterns [3, 4, 7]. Finally, we illustrate that scale independent queries are quite common in practice and that they indeed can be efficiently answered on big datasets when access constraints are present [5, 6]. |
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Language
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English
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Source (journal)
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LIPIcs : Leibniz International Proceedings in Informatics. - Place of publication unknown
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Source (book)
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19th International Conference on Database Theory (ICDT 2016) / Martens, Wim [edit.]; et al.
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Publication
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Germany
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Schloss Dagstuhl, Leibniz-Zentrum fuer Informatik
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2016
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ISBN
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978-3-95977-002-6
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Volume/pages
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48
(2016)
, p. 2:1-2:2
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Full text (Publisher's DOI)
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Full text (open access)
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