ACM Transactions on Database Systems (TODS)
Extending relational database technology for new applications
IBM Systems Journal
Multiple-query optimization at algorithm-level
Data & Knowledge Engineering
Workload scheduling for multiple query processing
Information Processing Letters
Advanced compiler design and implementation
Advanced compiler design and implementation
Compiling object-oriented data intensive applications
Proceedings of the 14th international conference on Supercomputing
Efficient and extensible algorithms for multi query optimization
SIGMOD '00 Proceedings of the 2000 ACM SIGMOD international conference on Management of data
Capacity Planning and Performance Modeling: From Mainframes to Client-Server Systems
Capacity Planning and Performance Modeling: From Mainframes to Client-Server Systems
Efficient execution of multiple query workloads in data analysis applications
Proceedings of the 2001 ACM/IEEE conference on Supercomputing
Processing large-scale multi-dimensional data in parallel and distributed environments
Parallel Computing - Parallel data-intensive algorithms and applications
Common Subexpression Processing in Multiple-Query Processing
IEEE Transactions on Knowledge and Data Engineering
Titan: A High-Performance Remote Sensing Database
ICDE '97 Proceedings of the Thirteenth International Conference on Data Engineering
Batch Scheduling in Parallel Database Systems
Proceedings of the Ninth International Conference on Data Engineering
Multiple Query Processing in Deductive Databases using Query Graphs
VLDB '86 Proceedings of the 12th International Conference on Very Large Data Bases
Compiler and Runtime Analysis for Efficient Communication in Data Intensive Applications
Proceedings of the 2001 International Conference on Parallel Architectures and Compilation Techniques
IPDPS '03 Proceedings of the 17th International Symposium on Parallel and Distributed Processing
Parallel aggregation on multi-dimensional scientific datasets
Parallel aggregation on multi-dimensional scientific datasets
Compiler techniques for data parallel applications using very large multi-dimensional datasets
Compiler techniques for data parallel applications using very large multi-dimensional datasets
Event dissemination via group-aware stream filtering
Proceedings of the second international conference on Distributed event-based systems
Group-aware stream filtering for bandwidth-efficient data dissemination
International Journal of Parallel, Emergent and Distributed Systems - Best Papers from the WWASN2007 Workshop
Towards collaborative data reduction in stream-processing systems
International Journal of Communication Networks and Distributed Systems
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Data analysis applications in areas as diverse as remote sensing and telepathology require operating on and processing very large datasets. For such applications to execute efficiently, careful attention must be paid to the storage, retrieval, and manipulation of the datasets. This paper addresses the optimizations performed by a high performance database system that processes groups of data analysis requests for these applications, which we call queries. The system performs end-to-end processing of the requests, formulated as PostgreSQL declarative queries. The queries are converted into imperative descriptions, multiple imperative descriptions are merged into a single execution plan, the plan is optimized to decrease execution time via common compiler optimization techniques, and, finally, the plan is optimized to decrease memory consumption. The last two steps are experimentally shown to effectively reduc the amount of time required while conserving memory space as a group of queries is processed by the database.