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Contribution Details
| Type | Journal Article |
| Scope | Discipline-based scholarship |
| Title | Leveraging range joins for the computation of overlap joins |
| Organization Unit | |
| Authors |
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| Item Subtype | Original Work |
| Refereed | Yes |
| Status | Published in final form |
| Language |
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| Journal Title | The VLDB Journal |
| Publisher | Springer |
| Geographical Reach | international |
| ISSN | 1066-8888 |
| Volume | 31 |
| Number | 1 |
| Page Range | 75 - 99 |
| Date | 2022 |
| Abstract Text | Joins are essential and potentially expensive operations in database management systems. When data is associated with time periods, joins commonly include predicates that require pairs of argument tuples to overlap in order to qualify for the result. Our goal is to enable built-in systems support for such joins. In particular, we present an approach where overlap joins are formulated as unions of range joins, which are more general purpose joins compared to overlap joins, i.e., are useful in their own right, and are supported well by B+-trees. The approach is sufficiently flexible that it also supports joins with additional equality predicates, as well as open, closed, and half-open time periods over discrete and continuous domains, thus offering both generality and simplicity, which is important in a system setting. We provide both a stand-alone solution that performs on par with the state-of-the-art and a DBMS embedded solution that is able to exploit standard indexing and clearly outperforms existing DBMS solutions that depend on specialized indexing techniques. We offer both analytical and empirical evaluations of the proposals. The empirical study includes comparisons with pertinent existing proposals and offers detailed insight into the performance characteristics of the proposals. |
| Free access at | DOI |
| Official URL | https://link.springer.com/article/10.1007/s00778-021-00692-3 |
| Digital Object Identifier | 10.1007/s00778-021-00692-3 |
| Other Identification Number | merlin-id:23075 |
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| Keywords | Overlap join, Range join, Temporal join, Interval join, Temporal databases |