Optimizing multiple queries on scientific datasets with partial replicas

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Optimizing multiple queries on scientific datasets with partial replicas
We propose strategies to efficiently execute a query workload, which consists of multiple related queries submitted against a scientific dataset, on a distributed-memory system in the presence of partial dataset replicas. Partial replication re-organizes and re-distributes one or more subsets of a dataset across the storage system to reduce I/O overheads and increase I/O parallelism. Our work targets a class of queries, called range queries, in which the query predicate specifies lower and upper bounds on the values of all or a subset of attributes of a dataset. Data elements whose attribute values fall into the specified bounds are retrieved from the dataset. If we think of the attributes of a dataset forming multi-dimensional space, where each attribute corresponds to one of the dimensions, a range query defines a bounding box in this multi-dimensional space. We evaluate our strategies in two scenarios involving range queries. The first scenario represents the case in which queries ...
Li Weng, Ümit V. Çatalyürek, Tahs
Added 16 Aug 2010
Updated 16 Aug 2010
Type Conference
Year 2007
Where GRID
Authors Li Weng, Ümit V. Çatalyürek, Tahsin M. Kurç, Gagan Agrawal, Joel H. Saltz
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