Materialized View Selection Using Iterative Improvement

A data warehouse is designed for the purpose of answering analytical queries, posed on them for decision making. The complex and exploratory nature of analytical queries which, when processed against large historical information in the data warehouse, consume a lot of time for processing. As a result, the query response time is high. Materialized views provide an alternative platform to address this problem of poor query response time. These views store aggregated and summarized information separately from a data warehouse with the aim of answering analytical queries. All views cannot be materialized, as the number of views is exponential in respect of number of dimensions. Also, optimal view selection is an NP-Complete Problem. Several view selection algorithms exist with most selecting views empirically or based on heuristics like greedy or evolutionary. In this paper, an algorithm based on iterative improvement, a randomized search heuristic technique for selecting top-K views for materialization is proposed. It is shown that the proposed algorithm, in comparison to a well known greedy algorithm, is able to select comparatively better quality views for higher dimensional data sets.

[1]  Jérôme Darmont,et al.  Data mining-based materialized view and index selection in data warehouses , 2007, Journal of Intelligent Information Systems.

[2]  Michael Lawrence,et al.  Multiobjective genetic algorithms for materialized view selection in OLAP data warehouses , 2006, GECCO '06.

[3]  Jeffrey D. Ullman,et al.  Implementing data cubes efficiently , 1996, SIGMOD '96.

[4]  Nick Roussopoulos,et al.  Materialized views and data warehouses , 1998, SGMD.

[5]  Jérôme Darmont,et al.  Clustering-Based Materialized View Selection in Data Warehouses , 2006, ADBIS.

[6]  T. V. Vijay Kumar,et al.  A Query Answering Greedy Algorithm for Selecting Materialized Views , 2010, ICCCI.

[7]  Frada Burstein,et al.  Australian Journal of Information Systems , 2001 .

[8]  Neeraj Jain,et al.  Mining information for constructing materialised views , 2010, Int. J. Inf. Commun. Technol..

[9]  Jian Yang,et al.  Algorithms for Materialized View Design in Data Warehousing Environment , 1997, VLDB.

[10]  Nagwa M. El-Makky,et al.  Algorithms for selecting materialized views in a data warehouse , 2005, The 3rd ACS/IEEE International Conference onComputer Systems and Applications, 2005..

[11]  Rada Chirkova,et al.  A formal perspective on the view selection problem , 2002, The VLDB Journal.

[12]  Sartaj Sahni,et al.  Information Systems, Technology and Management - Third International Conference, ICISTM 2009, Ghaziabad, India, March 12-13, 2009. Proceedings , 2009, ICISTM.

[13]  T. V. Vijay Kumar,et al.  Materialized Views Selection for Answering Queries , 2010, ICDEM.

[14]  Cheng-Yan Kao,et al.  Materialized view selection using genetic algorithms in a data warehouse system , 1999, Proceedings of the 1999 Congress on Evolutionary Computation-CEC99 (Cat. No. 99TH8406).

[15]  Xin Yao,et al.  Evolving materialized views in data warehouse , 1999, Proceedings of the 1999 Congress on Evolutionary Computation-CEC99 (Cat. No. 99TH8406).

[16]  John F. Roddick,et al.  Advances and Research Directions in Data-Warehousing Technology , 1999, Australas. J. Inf. Syst..

[17]  Sartaj Sahni,et al.  Information Intelligence, Systems, Technology and Management - 5th International Conference, ICISTM 2011, Gurgaon, India, March 10-12, 2011. Proceedings , 2011, ICISTM.

[18]  Elena Baralis,et al.  Materialized Views Selection in a Multidimensional Database , 1997, VLDB.

[19]  Surajit Chaudhuri,et al.  Automated Selection of Materialized Views and Indexes in SQL Databases , 2000, VLDB.

[20]  T. V. Vijay Kumar,et al.  Proposing Candidate Views for Materialization , 2010, ICISTM.

[21]  T. V. Vijay Kumar,et al.  Selection of Views for Materialization Using Size and Query Frequency , 2011 .

[22]  Gang Luo,et al.  Partial Materialized Views , 2007, 2007 IEEE 23rd International Conference on Data Engineering.

[23]  Matteo Golfarelli,et al.  View materialization for nested GPSJ queries , 2000, DMDW.

[24]  Timos K. Sellis,et al.  Data Warehouse Configuration , 1997, VLDB.

[25]  T. V. Vijay Kumar,et al.  A View Recommendation Greedy Algorithm for Materialized Views Selection , 2011, ICISTM.

[26]  Xin Yao,et al.  An evolutionary approach to materialized views selection in a data warehouse environment , 2001, IEEE Trans. Syst. Man Cybern. Part C.

[27]  Kamalakar Karlapalem,et al.  View Relevance Driven Materialized View Selection in Data Warehousing Environment , 2002, Australasian Database Conference.

[28]  T. V. Vijay Kumar,et al.  Greedy Views Selection Using Size and Query Frequency , 2011 .

[29]  Neeraj Jain,et al.  Selection of Frequent Queries for Constructing Materialized Views in Data Warehouse , 2010 .

[30]  Sartaj Sahni,et al.  Simulated Annealing and Combinatorial Optimization , 1986, DAC 1986.

[31]  Ziyu Lin,et al.  User-Oriented Materialized View Selection , 2007, 7th IEEE International Conference on Computer and Information Technology (CIT 2007).

[32]  Yannis E. Ioannidis,et al.  Randomized algorithms for optimizing large join queries , 1990, SIGMOD '90.

[33]  Ford Lumban Gaol,et al.  Information Technology and Mobile Communication , 2011 .

[34]  Inderpal Singh Mumick,et al.  Selection of Views to Materialize in a Data Warehouse , 2005, IEEE Trans. Knowl. Data Eng..

[35]  Srija Unnikrishnan,et al.  Advances in Computing, Communication, and Control , 2011 .

[36]  Jennifer Widom,et al.  Research problems in data warehousing , 1995, CIKM '95.

[37]  Jeffrey D. Ullman,et al.  Index selection for OLAP , 1997, Proceedings 13th International Conference on Data Engineering.

[38]  Wolfgang Lehner,et al.  Improving query response time in scientific databases using data aggregation -a case study , 1996, Proceedings of 7th International Conference and Workshop on Database and Expert Systems Applications: DEXA 96.

[39]  T. V. Vijay Kumar,et al.  A Reduced Lattice Greedy Algorithm for Selecting Materialized Views , 2009, ICISTM.

[40]  W. H. Inmon,et al.  Building the data warehouse , 1992 .

[41]  Kalyani Devi,et al.  Frequent queries identification for constructing materialized views , 2011, 2011 3rd International Conference on Electronics Computer Technology.

[42]  Rajkumar Kannan,et al.  Data Engineering and Management , 2012, Lecture Notes in Computer Science.

[43]  Karthik Ramachandran,et al.  A Hybrid Approach for Data Warehouse View Selection , 2006, Int. J. Data Warehous. Min..

[44]  Ashish Gupta,et al.  Generalized Projections: A Powerful Approach To Aggregation , 1995 .