  We develop a family of efficient plane-sweeping interval join algorithms that
can evaluate a wide range of interval predicates such as Allen's relationships
and parameterized relationships. Our technique is based on a framework,
components of which can be flexibly combined in different manners to support
the required interval relation. In temporal databases, our algorithms can
exploit a well-known and flexible access method, the Timeline Index, thus
expanding the set of operations it supports even further. Additionally,
employing a compact data structure, the gapless hash map, we utilize the CPU
cache efficiently. In an experimental evaluation, we show that our approach is
several times faster and scales better than state-of-the-art techniques, while
being much better suited for real-time event processing.
