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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.

We study the problem of enumeration of all k-sized subsets of temporal events that mutually overlap at some point in a query time window. This problem arises in many application domains, e.g., in social networks, life sciences, smart cities, telecommunications, and others. We propose a start time index (STI) approach that overcomes the efficiency bottlenecks of current methods which are based on 2-way join algorithms to enumerate temporal k-cliques. Additionally, we investigate how precomputed checkpoints can be used to further improve the efficiency of STI. Our experimental results demonstrate that STI outperforms the state of the art by a wide margin and that our checkpointing strategies are effective.

Vremenske baze podataka (eng. temporal databases) omogućuju pohranu informacija vezano uz prošlost, sadašnjost i budućnost za razliku od uobičajenih baza podataka koje sadrže vrijednosti koje su istinite u trenutnom vremenu. U ovom radu detaljno se opisuju osnovni vremenski koncepti te različiti relacijski sustavi (PostgreSQL, Oracle Database i Microsoft SQL Server.) koji u određenoj mjeri podupiru vremenske značajke propisane standardnom SQL:2011. Dodatno, detaljno su opisane operacije različitih temporalnih spajanja i potrebne izmjene relacijskog sustava PostgreSQL kako bi podupirao temporalno spajanje relacija. Temporal databases offer the ability to store past, present and future-related information in contrast to current databases which store facts that contain values that are true at the current time. This thesis describes basic temporal concepts, various temporal join operations and relational database management systems (PostgreSQL, Oracle Database and Microsoft SQL Server) which support temporal features differently based on the standard SQL:2011. In addition, the necessary changes in order to support temporal joining operations in PostgreSQL are also described.