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Data & Knowledge Engineering
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Therefore, index structures can easily be used in queries. A typical example is a join cursor which consumes the outputs of two underlying cursors. Most of our work is however not dedicated to the area of relational databases, but mainly refers to spatial and temporal data. For spatial databases, for example, we provide several implementations of spatial join algorithms [3]. The cursor-based processing is however the major advantage of XXL in contrast to approaches like LEDA [6] and TPIE [7]. For more information on XXL see http://www.mathematik.uni-marburg.de/DBS/xxl.We will demonstrate the latest version of XXL using examples to show its core functionality. We will concentrate on three key aspects of XXL.Usage: We show how easily state-of-the-art spatial join-algorithms can be implemented in XXL using data from different sources. Reuse: We will demonstrate how to support different joins, e.g. spatial and temporal joins, using the same generic algorithm like Plug&Join [1].Comparability: We will demonstrate how XXL serves as an ideal testbed to compare query processing algorithms and index structures.