ACM Transactions on Database Systems (TODS)
On the selection of secondary indices in relational databases
Data & Knowledge Engineering
Improved query performance with variant indexes
SIGMOD '97 Proceedings of the 1997 ACM SIGMOD international conference on Management of data
Bitmap index design and evaluation
SIGMOD '98 Proceedings of the 1998 ACM SIGMOD international conference on Management of data
ICDE '97 Proceedings of the Thirteenth International Conference on Data Engineering
Discovering Frequent Closed Itemsets for Association Rules
ICDT '99 Proceedings of the 7th International Conference on Database Theory
Curio: A Novel Solution for Efficient Storage and Indexing in Data Warehouses
VLDB '99 Proceedings of the 25th 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
Multi-Dimensional Database Allocation for Parallel Data Warehouses
VLDB '00 Proceedings of the 26th International Conference on Very Large Data Bases
An Efficient Cost-Driven Index Selection Tool for Microsoft SQL Server
VLDB '97 Proceedings of the 23rd International Conference on Very Large Data Bases
Index Selection for Databases: A Hardness Study and a Principled Heuristic Solution
IEEE Transactions on Knowledge and Data Engineering
DB2 design advisor: integrated automatic physical database design
VLDB '04 Proceedings of the Thirtieth international conference on Very large data bases - Volume 30
Self-tuning database systems: a decade of progress
VLDB '07 Proceedings of the 33rd international conference on Very large data bases
An Integer Linear Programming Approach to Database Design
ICDEW '07 Proceedings of the 2007 IEEE 23rd International Conference on Data Engineering Workshop
SimulPh.D.: A Physical Design Simulator Tool
DEXA '09 Proceedings of the 20th International Conference on Database and Expert Systems Applications
Analyses of multi-level and multi-component compressed bitmap indexes
ACM Transactions on Database Systems (TODS)
Automatic selection of bitmap join indexes in data warehouses
DaWaK'05 Proceedings of the 7th international conference on Data Warehousing and Knowledge Discovery
Revisiting the partial data cube materialization
ADBIS'11 Proceedings of the 15th international conference on Advances in databases and information systems
Static and incremental selection of multi-table indexes for very large join queries
ADBIS'12 Proceedings of the 16th East European conference on Advances in Databases and Information Systems
Immune algorithm for bitmap join indexes
ICONIP'12 Proceedings of the 19th international conference on Neural Information Processing - Volume Part III
Intelligent Decision Technologies
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One of the fundamental tasks that data warehouse (DW) administrator needs to perform during the physical design is to select the right indexes to speed up her/his queries. Two categories of indexes are available and supported by the main DBMS vendors: (i) indexes defined on a single table and (ii) indexes defined on multiple tables such as join indexes, bitmap join indexes, etc. Selecting relevant indexes for a given workload is a NP-hard problem. A majority of studies on index selection problem was focused on single table indexes, where several types of algorithms were proposed: greedy search, genetic, linear programming, etc. Parallel to these research efforts, commercial DBMS gave the same attention to single table indexes, where automated tools and advisors generating recommended indexes for a particular workload and constraints are developed. Unfortunately, only few studies dealing with the problem of selecting bitmap join indexes are carried out. Due to the high complexity of this problem, these studies mainly focused on proposing pruning solutions of the search space by the means of data mining techniques. The lack of bitmap join index selection algorithms motivates our proposal. This paper proposes selection strategies for single and multiple attributes BJI. Intensive experiments are conducted comparing the proposed strategies using mathematical cost model and the obtained results are validated under Oracle using APB1 benchmark.