Join synopses for approximate query answering
SIGMOD '99 Proceedings of the 1999 ACM SIGMOD international conference on Management of data
The Aqua approximate query answering system
SIGMOD '99 Proceedings of the 1999 ACM SIGMOD international conference on Management of data
Progressive approximate aggregate queries with a multi-resolution tree structure
SIGMOD '01 Proceedings of the 2001 ACM SIGMOD international conference on Management of data
On the Data Model and Access Method of Summary Data Management
IEEE Transactions on Knowledge and Data Engineering
Approximate Query Processing with Summary Tables in Statistical Databases
EDBT '92 Proceedings of the 3rd International Conference on Extending Database Technology: Advances in Database Technology
Approximate Queries and Representations for Large Data Sequences
ICDE '96 Proceedings of the Twelfth International Conference on Data Engineering
Approximate Query Processing Using Wavelets
VLDB '00 Proceedings of the 26th International Conference on Very Large Data Bases
Toward a Query Language on Simulation Mesh Data: An Object-oriented Approach
DASFAA '01 Proceedings of the 7th International Conference on Database Systems for Advanced Applications
Fast Approximate Query Answering Using Precomputed Statistics
ICDE '99 Proceedings of the 15th International Conference on Data Engineering
Simulation data as data streams
ACM SIGMOD Record
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AQSim is a system intended to enable scientists to query and analyze a large volume of scientific simulation data. The system uses the state of the art in approximate query processing techniques to build a novel framework for progressive data analysis. These techniques are used to define a multi-resolution index, where each node contains multiple models of the data. The benefits of these models are twofold: (1) they have compact representations, reconstructing only the information relevant to the analysis, and (2) the variety of models capture different aspects of the data which may be of interest to the user but are not readily apparent in their raw form. To be able to deal with the data interactively, AQSim allows the scientist to make an informed tradeoff between query response accuracy and time. In this paper, we present the framework of AQSim with a focus on its architectural design. We also show the results from an initial proof-of-concept prototype developed at LLNL. The presented framework is generic enough to handle more than just simulation data.