Abstract
We study the problem of bulk loading a linear hash file; the problem is that a good hash function is able to distribute records into random locations in the file; however, performing a random disk access for each record can be costly and this cost increases with the size of the file. We propose a bulk loading algorithm that can avoid random disk accesses by reducing multiple accesses to the same location into a single access and reordering the accesses such that the pages are accessed sequentially. Our analysis shows that our algorithm is near-optimal with a cost roughly equal to the cost of sorting the dataset, thus the algorithm can scale up to very large datasets. Our experiments show that our method can improve upon the Berkeley DB load utility, in terms of running time, by two orders of magnitude and the improvements scale up well with the size of the dataset.
Access provided by Autonomous University of Puebla. Download to read the full chapter text
Chapter PDF
Similar content being viewed by others
Keywords
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
References
Ailamaki, A., DeWitt, D.J., Hill, M.D., Skounakis, M.: Weaving relations for cache performance. In: Proceedings of the VLDB Conference, Rome, Italy, pp. 169–180 (2001)
Amer-Yahia, S., Cluet, S.: A declarative approach to optimize bulk loading into databases. ACM Transactions on Database Systems 29(2), 233–281 (2004)
Böhm, C., Kriegel, H.: Efficient bulk loading of large high-dimensional indexes. In: International Conference on Data Warehousing and Knowledge Discovery, pp. 251–260 (1999)
Fenk, R., Kawakami, A., Markl, V., Bayer, R., Osaki, S.: Bulk loading a data warehouse built upon a ub-tree. In: Proceedings of of IDEAS Conference, Yokohoma, Japan, pp. 179–187 (2000)
Gray, J.: A conversation with Jim Gray. ACM Queue 1(4) (2003)
Hjaltason, G.R., Samet, H., Sussmann, Y.J.: Speeding up bulk-loading of quadtrees. In: Proceedings of the International ACM Workshop on Advances in Geographic Information Systems, Las Vegas, pp. 50–53 (1997)
Internet Archive, http://www.archive.org
Jagadish, H.V., Narayan, P.P.S., Seshadri, S., Sudarshan, S., Kanneganti, R.: Incremental organization for data recording and warehousing. In: Proc. of the VLDB Conference, Athens, pp. 16–25 (1997)
Knuth, D.: The Art of Computer Programming: vol III, Sorting and Searching, 3rd edn. Addison-Wesley, Reading (1998)
Labio, W., Wiener, J.L., Garcia-Molina, H., Gorelik, V.: Efficient resumption of interrupted warehouse loads. In: Proc. of the SIGMOD Conference, Dallas, pp. 46–57 (2000)
Larson, P.: Dynamic hash tables. Communications of the ACM 31(4), 446–457 (1988)
Rabin, M.O.: Fingerprinting by random polynomials. Technical Report TR-15-81, Department of Computer Science, Harvard University (1981)
Rafiei, D., Hu, C.: Bulk loading a linear hash file: extended version (under preparation)
Seltzer, M., Yigit, O.: A new hashing package for unix. In: USENIX, Dallas, pp. 173–184 (1991)
Wiener, J.L., Naughton, J.F.: OODB bulk loading revisited: The partitioned-list approach. In: Proceedings of the VLDB Conference, Zurich, Switzerland, pp. 30–41 (1995)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2006 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Rafiei, D., Hu, C. (2006). Bulk Loading a Linear Hash File. In: Tjoa, A.M., Trujillo, J. (eds) Data Warehousing and Knowledge Discovery. DaWaK 2006. Lecture Notes in Computer Science, vol 4081. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11823728_3
Download citation
DOI: https://doi.org/10.1007/11823728_3
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-37736-8
Online ISBN: 978-3-540-37737-5
eBook Packages: Computer ScienceComputer Science (R0)