The framework for approximate queries on simulation data

Information Sciences

Volumn 157, Issue 1-4, 2003, Pages 3-20

  Lee, B ^a   Critchlow, T ^b   Abdulla, G ^b   Baldwin, C ^b   Kamimura, R ^b   Musick, R ^c   Snapp, R ^a   Tang, N ^b  

^a University of Vermont   (United States)

^b LAWRENCE LIVERMORE NATIONAL LABORATORY   (United States)

^c iKuni Inc   (United States)

Author keywords

Approximate query; Multi model data reduction; Multi resolution index

Indexed keywords

APPROXIMATION THEORY; COMPUTER SIMULATION; DATA REDUCTION; METADATA; QUERY LANGUAGES;

MULTI-RESOLUTION INDEX;

INFORMATION SCIENCE;

EID: 0242334176     PISSN: 00200255     EISSN: None     Source Type: Journal    
DOI: 10.1016/S0020-0255(03)00185-3     Document Type: Article

References (20)

1. Eighth NASA Goddard Space Flight Center Conference on Mass Storage Systems and Technologies in cooperation with Seventeenth IEEE Symposium on Mass Storage Systems, College Park, MD, USA, March 27-30, 2000. Available from 〉 〉http://esdis-it.gsfc.nasa.gov/MSST/conf2000〈
2. Hellerstein J. Data Engineering Bulletin. Data Reduction Techniques. 20(4):1997;. (special issue).
3. B. Lee, R. Snapp, R. Musick, Toward a query language on simulation mesh data: an object-oriented approach, in: Proc. Int. Conf. Database Systems for Advanced Applications, 2001, pp. 242-249.
4. Chen M.C., McNamee L.P. On the data model and access method of summary data management. IEEE Transactions on Knowledge and Data Engineering. 1(4):1989;519-529.
5. H. Shatkay, S.B. Zdonik, Approximate queries and representations for large data sequences, in: Proc. Int. Conf. Data Engineering, 1996, pp. 536-545.
6. S. Abad-Mota, Approximate query processing with summary tables in statistical databases, in: Proc. Int. Conf. Extending Data Base Technology, 1992, pp. 499-515.
7. V. Poosala, V. Ganti, Fast approximate query answering using precomputed statistics, in: Proc. Int. Conf. Data Engineering, 1999, p. 252.
8. K. Chakrabarti, M.N. Garofalakis, R. Rastogi, K. Shim, Approximate query processing using wavelets, in: Proc. Int. Conf. Very Large Database, 2000, pp. 111-122.
9. AQUA Project Home Page, Lucent Technologies. Available from 〉 http://www.bell-labs.com/project/aqua/〈
10. S. Acharya, P.B. Gibbons, V. Poosala, S. Ramaswamy, The aqua approximate query answering system, in: Proc. ACM SIGMOD Int. Conf. Management of Data, 1999, pp. 574-576.
11. S. Acharya, P.B. Gibbons, V. Poosala, S. Ramaswamy, Join synopses for approximate query answering, in: Proc. ACM SIGMOD Int. Conf. Management of Data, 1999, pp. 275-286.
12. Silo Documentation Version 4.0, Lawrence Livermore National Laboratory, Livermore, CA. Available from 〈 http://www.llnl.gov/meshtv/manuals.html〉.
13. The Common Data Format, The National Space Science Data Center, Greenbelt, MD. Available from 〈 http://nssdc.gsfc.nasa.gov/cdf/cdf_home.html〉
14. NetCDF, University Corporation for Atmospheric Research. Available from 〉 http://www.unidata.ucar.edu/packages/netcdf/index.html〈
15. The NCSA HDF Home Page, The National Center for Supercomputing Applications, University of Illinois at Urbana-Champaign, IL. Available from 〉 http://hdf.ncsa.uiuc.edu〈
16. S. Goil, N. Harsha, A. Choudhary, MAFIA: efficient and scalable subspace clustering for very large datasets, Technical Report CPDC-TR-9906-010, Northwestern University, 1999.
17. Antoniadis A., Oppenheim G. Wavelets and Statistics. Springer-Verlag, 1995
18. Härdle W.et al. Wavelets, Approximation, and Statistical Applications. 1998;Springer-Verlag.
19. M. Bertram, M. Duchaineau, B. Hamann, K. Joy, Lifted bicubic subdivision-surface wavelets for geometry reconstruction, in: Proc. SIGGRAPH, 2000.
20. I. Lazaridis, S. Mehrota, Progressive approximate aggregate queries with a multi-resolution tree structure, in: Proc. ACM SIGMOD Int. Conf. Management of Data, 2001.