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Contribution Details

Type Journal Article
Scope Discipline-based scholarship
Title Extending the kernel of a relational dbms with comprehensive support for sequenced temporal queries
Organization Unit
Authors
  • Anton Dignös
  • Michael Hanspeter Böhlen
  • Johann Gamper
  • Christian S Jensen
Item Subtype Original Work
Refereed Yes
Status Published in final form
Language
  • English
Journal Title ACM Transactions on Database Systems
Publisher Association for Computing Machinery
Geographical Reach international
ISSN 0362-5915
Volume 41
Number 4
Page Range 1 - 46
Date 2016
Abstract Text Many databases contain temporal, or time-referenced, data and use intervals to capture the temporal aspect. While SQL-based database management systems (DBMSs) are capable of supporting the management of interval data, the support they offer can be improved considerably. A range of proposed temporal data models and query languages offer ample evidence to this effect. Natural queries that are very difficult to formulate in SQL are easy to formulate in these temporal query languages. The increased focus on analytics over historical data where queries are generally more complex exacerbates the difficulties and thus the potential benefits of a temporal query language. Commercial DBMSs have recently started to offer limited temporal functionality in a step-by-step manner, focusing on the representation of intervals and neglecting the implementation of the query evaluation engine. This article demonstrates how it is possible to extend the relational database engine to achieve a full-fledged, industrial-strength implementation of sequenced temporal queries, which intuitively are queries that are evaluated at each time point. Our approach reduces temporal queries to nontemporal queries over data with adjusted intervals, and it leaves the processing of nontemporal queries unaffected. Specifically, the approach hinges on three concepts: interval adjustment, timestamp propagation, and attribute scaling. Interval adjustment is enabled by introducing two new relational operators, a temporal normalizer and a temporal aligner, and the latter two concepts are enabled by the replication of timestamp attributes and the use of so-called scaling functions. By providing a set of reduction rules, we can transform any temporal query, expressed in terms of temporal relational operators, to a query expressed in terms of relational operators and the two new operators. We prove that the size of a transformed query is linear in the number of temporal operators in the original query. An integration of the new operators and the transformation rules, along with query optimization rules, into the kernel of PostgreSQL is reported. Empirical studies with the resulting temporal DBMS are covered that offer insights into pertinent design properties of the article's proposal. The new system is available as open-source software.
Digital Object Identifier 10.1145/2967608
Other Identification Number merlin-id:14054
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Additional Information © 2017 ACM, Inc. This is the author's version of the work. It is posted here for your personal use. Not for redistribution. The definitive Version of Record was published in ACM Transactions on Database Systems (TODS), Volume 41 Issue 4, December 2016, Article No. 26, http://dx.doi.org/10.1145/2967608