Implementing data cubes efficiently
SIGMOD '96 Proceedings of the 1996 ACM SIGMOD international conference on Management of data
A progressive view materialization algorithm
Proceedings of the 2nd ACM international workshop on Data warehousing and OLAP
A general framework for the view selection problem for data warehouse design and evolution
Proceedings of the 3rd ACM international workshop on Data warehousing and OLAP
Building the Data Warehouse,3rd Edition
Building the Data Warehouse,3rd Edition
Achieving scalability in OLAP materialized view selection
Proceedings of the 5th ACM international workshop on Data Warehousing and OLAP
ICDE '97 Proceedings of the Thirteenth International Conference on Data Engineering
Materialized Views Selection in a Multidimensional Database
VLDB '97 Proceedings of the 23rd International Conference on Very Large Data Bases
Materialized View Selection for Multidimensional Datasets
VLDB '98 Proceedings of the 24rd International Conference on Very Large Data Bases
Automated Selection of Materialized Views and Indexes in SQL Databases
VLDB '00 Proceedings of the 26th International Conference on Very Large Data Bases
Improving query response time in scientific databases using data aggregation -a case study
DEXA '96 Proceedings of the 7th International Workshop on Database and Expert Systems Applications
Selection of Views to Materialize in a Data Warehouse
IEEE Transactions on Knowledge and Data Engineering
Algorithm for selection of materialized views: based on a costs model
ENC '07 Proceedings of the Eighth Mexican International Conference on Current Trends in Computer Science
Data mining-based materialized view and index selection in data warehouses
Journal of Intelligent Information Systems
Clustering-based materialized view selection in data warehouses
ADBIS'06 Proceedings of the 10th East European conference on Advances in Databases and Information Systems
An evolutionary approach to materialized views selection in a datawarehouse environment
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
Materialised view construction in data warehouse for decision making
International Journal of Business Information Systems
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A data warehouse stores historical data to support analytical query processing. These analytical queries are long and complex and processing these against a large data warehouse consumes a lot of time. As a result, the query response time is high. One way to reduce this time is by selecting views that are likely to answer a large number of future queries and storing them in a data warehouse. This problem is referred to as view selection. Several view selection algorithms have been proposed with most of these being focused around HRUA. HRUA considers the size of the views to select the most beneficial view for materialization. The views selected using HRUA, though beneficial with respect to size, may be unable to account for large numbers of queries and thus making them an unnecessary overhead. The algorithm proposed in this paper attempts to address this problem by considering query frequency, along with the size, of the view to select Top-K views for materialization. The proposed algorithm, in each iteration, computes the profit, defined in terms of size and query frequency, and then selects the most profitable view for materialization. As a result, the views selected are beneficial with respect to size and have the ability to answer future queries. Further, experimental results show that the proposed algorithm, in comparison to HRUA, is able to select views capable of answering larger number of queries against a slight increase in the total cost of evaluating all the views. This in turn would result in efficient decision making.