A Survey: Computing Iceberg Queries
Abstract
Knowledge discovery, tasks are deals with huge no of records. Queries are needed to identify unique attributes values and their aggregate that is above a predefined threshold from this huge number of records. This type of queries is called iceberg queries. Iceberg queries requires huge amount of main memory and takes longer time to answer the query. As computer system has limited amount of main memory, the processing of iceberg queries is a challenging task. This paper discusses different methods that are in literature for processing iceberg queries , we also explore pros and cons of these methods and future scope.
About this article
Keywords
- Aggregation functions
- Bitmap Index
- Iceberg Queries
- Anti monotone
- Bit map Numbers .
References
[1]. M. Fang, N. Shivakumar, H. Garcia-Molina, R. Motwani, and J.D. Ullman, “Computing Iceberg Queries Efficiently”, Proc. Int’l Conf. Very Large Data Bases (VLDB), pp. 299-310, 1998.
[2]. Whang, K.Y., B.T.V. Zanden and H.M. Taylor, “Alinear-time probabilistic counting algorithm for database applications”, ACM Trans. Database Syst., 15: 208-229, 1990.
[3]. J.Bae and S.Lee. ”Partitioning algorithms for the computation of average iceberg queries.” Proc. Second Intl Conf. Data Warehousing and Knowl-edge Discovery (DaWaK), pp. 276-286, 2000.
[4]. K.P. Leela, P.M. Tolani, and J.R. Haritsa, “On Incorporating Iceberg Queries in Query Processors”, Proc. Intl Conf. Data-base Systems for Advances Applications (DASFAA), pp. 431-442, 2004.
[5]. J. Han, J. Pei, G. Dong, and K. Wang, “Efficient Computation of Iceberg Cubes with Complex Measures”, Proc. ACM SIGMOD Int’l Conf. Management of Data, pp. 1-12, 2001.
[6]. B.He,H-I.Hsia,Z.Liu,Y.Huang and Y.Chen, “Efficent computing Iceberg queries using compresed bitmap index”, IEEE TRANSACTION ON KNOWLEDGE AND DATA ENGINEERING,2012
[7]. Vuppu shanker et al .”Effective Iceberg Query Evaluation by Deferring Push and Pop Operations”,IJAC, ISSN:2051-0845, Vol.36, Issue.2.2015
[8]. Vuppu shanker et al,” Cache Based Evaluation of Iceberg Queries”, ICCCT-2014 IEEE,2014
[9]. Vuppu shanker et al, “Answering Iceberg Queries Efficiently Using Check Point Mechanism”,IJAC , Vol.46, Issue.2,2015
[10].Pallam Ravi et al “COMPUTING ICEBERG QUERIES HAVING NON ANTI MONOTONE CONSTRAINS WITH BIT MAP NUMBER”, JATIT,Vol. 8. No. 2 -- 2016
[11].Kale Sarika Prakash et al,”Tracking Pointer and Look Ahead Matching Strategy to Evaluate Iceberg Query”,JCS,2017
[12].Y.Cui, W.Perrizo ”Aggregate Function Computation and Iceberg Query-ing in Vertical Database”,Computers and Their Applications,2006
[13].Vuppu shanker et al, “Efficient iceberg evaluation in Distributed databases by Developing Deferred Strategies”,2016
[14].K.S. Beyer and R. Ramakrishnan, “Bottom-Up Computation of Sparse and Iceberg CUBEs”, Proc. ACM SIGMOD Int’l Conf. Management of Data, pp. 359-370, 1999.
[15].C.Y. Chan and Y.E. Ioannidis, “Bitmap Index Design and Evaluation”, Proc. ACM SIGMOD Intl Conf. Management of Data, 1998.
F. Deliege and T.B. Pedersen, “Position List Word Aligned Hybrid: Optimizing Space and Performance for Compressed Bitmaps”, Proc. Intl Conf. Extending Database Technology (EDBT), pp. 228-239, 2010.2.