BBoxDB: a distributed and highly available key-bounding-box-value store

BBoxDB is a distributed and highly available key-bounding-box-value store, which is designed to handle multi-dimensional big data. To handle large amounts of data, the software splits the stored data into multi-dimensional shards and spreads them across a cluster of nodes. Unlike existing key-value...

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Veröffentlicht in:Distributed and parallel databases : an international journal 2020-06, Vol.38 (2), p.439-493
Hauptverfasser: Nidzwetzki, Jan Kristof, Güting, Ralf Hartmut
Format: Artikel
Sprache:eng
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Zusammenfassung:BBoxDB is a distributed and highly available key-bounding-box-value store, which is designed to handle multi-dimensional big data. To handle large amounts of data, the software splits the stored data into multi-dimensional shards and spreads them across a cluster of nodes. Unlike existing key-value stores, BBoxDB stores each value together with an n -dimensional, axis parallel bounding box. The bounding box describes the spatial location of the value in an n -dimensional space. Multi-dimensional data can be retrieved by using range queries, which are efficiently supported by indices. A space partitioner (e.g., a K-D Tree, a Quad-Tree or a Grid) is used to split the n -dimensional space into disjoint regions (distribution regions). Distribution regions are created dynamically, based on the stored data. BBoxDB can handle growing and shrinking datasets. The data redistribution is performed in the background and does not affect the availability of the system; read and write access is still possible at any time. BBoxDB works with distribution groups, the data of all tables in a distribution group are distributed in the same way (co-partitioned). Spatial joins on co-partitioned tables can be executed efficiently without data shuffling between nodes. BBoxDB supports spatial joins out-of-the-box using the bounding boxes of the stored data. The joins are supported by a spatial index and executed in a distributed and parallel manner on the nodes of the cluster.
ISSN:0926-8782
1573-7578
DOI:10.1007/s10619-019-07275-w