ACM Transactions on Database Systems (TODS)
Caching multidimensional queries using chunks
SIGMOD '98 Proceedings of the 1998 ACM SIGMOD international conference on Management of data
Common Subexpression Processing in Multiple-Query Processing
IEEE Transactions on Knowledge and Data Engineering
Trust but Check: Mutable Objects in Untrusted Cooperative Caches
Proceedings of the 8th International Workshop on Persistent Object Systems (POS8) and Proceedings of the 3rd International Workshop on Persistence and Java (PJW3): Advances in Persistent Object Systems
A predicate-based caching scheme for client-server database architectures
The VLDB Journal — The International Journal on Very Large Data Bases
MSS '01 Proceedings of the Eighteenth IEEE Symposium on Mass Storage Systems and Technologies
Applying Database Support for Large Scale Data Driven Science in Distributed Environments
GRID '03 Proceedings of the 4th International Workshop on Grid Computing
An Approach for Automatic Data Virtualization
HPDC '04 Proceedings of the 13th IEEE International Symposium on High Performance Distributed Computing
Servicing range queries on multidimensional datasets with partial replicas
CCGRID '05 Proceedings of the Fifth IEEE International Symposium on Cluster Computing and the Grid (CCGrid'05) - Volume 2 - Volume 02
Cooperative caching: using remote client memory to improve file system performance
OSDI '94 Proceedings of the 1st USENIX conference on Operating Systems Design and Implementation
ConSMutate: SQL mutants for guiding concolic testing of database applications
ICFEM'12 Proceedings of the 14th international conference on Formal Engineering Methods: formal methods and software engineering
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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 multidimensional space. We evaluate our strategies in two scenarios involving range queries. The first scenario represents the case in which queries have overlapping regions of interest, such as those arising from an exploratory analysis of the dataset by multiple users. In the second scenario, queries represent adjacent rectilinear sections that capture an irregular subregion in the multi-dimensional space. This scenario corresponds to a case where the user wants to query and retrieve a spatial feature from the dataset. We propose cost models and an algorithm for optimizing such queries. Our results using queries for subsetting and analysis of medical image datasets show that effective use of partial replicas can result in reduction in query execution times.