RLH: Bitmap compression technique based on run-length and Huffman encoding

Information Systems

Volumn 34, Issue 4-5, 2009, Pages 400-414

  Stabno, Michał ^a   Wrembel, Robert ^a  

^a POZNAN UNIVERSITY OF TECHNOLOGY   (Poland)

Author keywords

BBC; Bitmap compression; Bitmap index; Huffman encoding; RLH; Run length encoding; WAH

Indexed keywords

BBC; BITMAP COMPRESSION; BITMAP INDEX; HUFFMAN ENCODING; RLH; RUN-LENGTH ENCODING; WAH;

DATA WAREHOUSES; PARTICLE DETECTORS;

ENCODING (SYMBOLS);

EID: 65249167570     PISSN: 03064379     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.is.2008.11.002     Document Type: Article

References (39)

1. Amir A., Benson G., and Farach M. Let sleeping files lie: pattern matching in z-compressed files. Journal of Computer and Systems Sciences 52 2 (1996) 299-307
2. Antoshenkov G., and Ziauddin M. Query processing and optimization in Oracle RDB. VLDB Journal 5 4 (1996) 229-237
3. T. Apaydin, G. Canahuate, H. Ferhatosmanoglu, A.S. Tosun, Approximate encoding for direct access and query processing over compressed bitmaps, in: Proceedings of International Conference on Very Large Data Bases (VLDB), 2006.
4. C. Chan, Y. Ioannidis, Bitmap index design and evaluation, in: Proceedings of ACM SIGMOD International Conference on Management of Data, 1998.
5. Davis K.C., and Gupta A. Indexing in data warehouses: bitmaps and beyond. In: Wrembel R., and Koncilia C. (Eds). Data Warehouses and OLAP: Concepts, Architectures and Solutions (2007), Idea Group Inc. 179-202 ISBN 1-59904-364-5
6. de Moura E.S., Navarro G., Ziviani N., and Bayeza-Yates R. Fast and flexible word searching on compressed text. ACM Transactions on Information Systems 18 2 (2000) 113-139
7. Elias P. Universal codeword sets and representations of the integers. IEEE Transactions on Information Theory 21 2 (1975) 194-203
8. M. Farach, M. Thorup, String matching in Lempel-Ziv compressed strings, in: Proceedings of ACM Annual Symposium on the Theory of Computing, 1995.
9. Golomb S.W. Run-length encodings. IEEE Transactions on Information Theory 12 3 (1966) 399-401
10. D.A. Huffman, A method for the construction of minimum-redundancy codes, in: Proceedings of the Institute of Radio Engineers, 1952.
11. D. Johnson, S. Krishnan, J. Chhugani, S. Kumar, S. Venkatasubramanian, Compressing large boolean matrices using reordering techniques, in: Proceedings of International Conference on Very Large Data Bases (VLDB), 2004.
12. N. Koudas, Space efficient bitmap indexing, in: Proceedings of ACM Conference on Information and Knowledge Management (CIKM), 2000.
13. Navarro G., de Moura E.S., Neubert M., Ziviani N., and Baeza-Yates R. Adding compression to block addressing inverted indexes. Information Retrieval 3 1 (2000) 49-77
14. O'Neil P. Model 204 architecture and performance. International Workshop on High Performance Transactions Systems, Lecture Notes in Computer Science vol. 359 (1987), Springer, Berlin
15. E. O'Neil, P. O'Neil, K. Wu, Bitmap index design choices and their performance implications, Research Report, Lawrence Berkeley National Laboratory, 2007.
16. P. O'Neil, The set query benchmark, retrieved October 27, 2008, from 〈http://www.cs.umb.edu/poneil/SetQBM.pdf〉.
17. P. O'Neil, D. Quass, Improved query performance with variant indexes, in: Proceedings of ACM SIGMOD International Conference on Management of Data, 1997.
18. A. Pinar, T. Tao, H. Ferhatosmanoglu, Compressing bitmap indices by data reorganization, in: Proceedings of International Conference on Data Engineering (ICDE), 2005.
19. F. Reiss, K. Stockinger, K. Wu, A. Shoshani, J.M. Hellerstein, Efficient analysis of live and historical streaming data and its application to cybersecurity, Research Report, Lawrence Berkeley National Laboratory, 2006.
20. D. Rinfret, P. O'Neil, E. O'Neil, Bit-sliced index arithmetic, in: Proceedings of ACM SIGMOD International Conference on Management of Data, 2001.
21. D. Rotem, K. Stockinger, K. Wu, Optimizing candidate check costs for bitmap indices, in: Proceedings of ACM Conference on Information and Knowledge Management (CIKM), 2005.
22. Rotem D., Stockinger K., and Wu K. Optimizing I/O costs of multi-dimensional queries using bitmap indices. Proceedings of International Conference on Database and Expert Systems Applications (DEXA), Lecture Notes in Computer Science vol. 3588 (2005), Springer, Berlin
23. F. Scholer, H.E. Williams, J. Yiannis, J. Zobel, Compression of inverted indexes for fast query evaluation, in: Proceedings of International ACM SIGIR Conference, 2002.
24. Scientific Data Management Research Group, FastBit: An efficient compressed bitmap index technology, retrieved November 10, 2006, from 〈http://sdm.lbl.gov/fastbit/〉.
25. M. Stabno, R. Wrembel, RLH: Bitmap compression technique based on run-length and Huffman encoding, in: Proceedings of ACM International Workshop on Data Warehousing and OLAP (DOLAP), 2007.
26. Stockinger K., and Wu K. Bitmap indices for data warehouses. In: Wrembel R., and Koncilia C. (Eds). Data Warehouses and OLAP: Concepts, Architectures and Solutions (2007), Idea Group Inc. 157-178 ISBN 1-59904-364-5
27. Stockinger K., Wu K., and Shoshani A. Evaluation strategies for bitmap indices with binning. Proceedings of International Conference on Database and Expert Systems Applications (DEXA), Lecture Notes in Computer Science vol. 3180 (2004), Springer, Berlin
28. Vitter J.S. Dynamic Huffman coding. ACM Transactions on Mathematical Software 15 2 (1989) 158-167
29. A.N. Vo, A. Moffat, Compressed inverted files with reduced decoding overheads, in: Proceedings of International ACM SIGIR Conference, 1998.
30. Williams H., and Zobel J. Compressing integers for fast file access. Computer Journal 42 3 (1999) 193-201
31. Witten I.H., Moffat A., and Bell T.C. Managing Gigabytes: Compressing and Indexing Documents and Images (1999), Morgan Kaufmann Publishers, Los Altos, CA
32. K. Wu, E.J. Otoo, A. Shoshani, Compressing bitmap indexes for faster search operations, in: Proceedings of International Conference on Scientific and Statistical Database Management (SSDBM), 2002.
33. K. Wu, E.J. Otoo, A. Shoshani, An efficient compression scheme for bitmap indices, Research Report, Lawrence Berkeley National Laboratory, 2004.
34. K. Wu, E. J. Otoo, A. Shoshani, On the performance of bitmap indices for high cardinality attributes, in: Proceedings of International Conference on Very Large Data Bases (VLDB), 2004.
35. Wu K., Otoo E.J., and Shoshani A. Optimizing bitmap indices with efficient compression. ACM Transactions on Database Systems (TODS) 31 1 (2006) 1-38
36. K. Wu, P. Yu, Range-based bitmap indexing for high cardinality attributes with skew, in: International Computer Software and Applications Conference (COMPSAC), 1998.
37. M. Wu, A. Buchmann, Encoded bitmap indexing for data warehouses, in: Proceedings of International Conference on Data Engineering (ICDE), 1998.
38. Ziv J., and Lempel A. A universal algorithm for sequential data compression. IEEE Transactions on Information Theory 23 3 (1977) 337-343
39. Ziviani N., de Moura E.S., Navarro G., and Bayeza-Yates R. Compression: a key for next-generation text retrieval systems. IEEE Computer 33 11 (2000) 37-44