ACM Transactions on Database Systems (TODS)
An overview of data warehousing and OLAP technology
ACM SIGMOD Record
Improved query performance with variant indexes
SIGMOD '97 Proceedings of the 1997 ACM SIGMOD international conference on Management of data
Faster joins, self-joins and multi-way joins using join indices
Data & Knowledge Engineering - Special issue: next generation information technologies and systems
View indexing in relational databases
ACM Transactions on Database Systems (TODS)
A Framework for Join Pattern Indexing in Intelligent Database Systems
IEEE Transactions on Knowledge and Data Engineering
Physical Database Design for Data Warehouses
ICDE '97 Proceedings of the Thirteenth International Conference on Data Engineering
ICDE '97 Proceedings of the Thirteenth International Conference on Data Engineering
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
Answering Queries with Aggregation Using Views
VLDB '96 Proceedings of the 22th International Conference on Very Large Data Bases
VLDB '97 Proceedings of the 23rd International Conference on Very Large Data Bases
Algorithms for Materialized View Design in Data Warehousing Environment
VLDB '97 Proceedings of the 23rd International Conference on Very Large Data Bases
PartJoin: An Efficient Storage and Query Execution for Data Warehouses
DaWaK 2000 Proceedings of the 4th International Conference on Data Warehousing and Knowledge Discovery
CASCON '12 Proceedings of the 2012 Conference of the Center for Advanced Studies on Collaborative Research
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Index selection is one of the most important decisions in designing a data warehouse (DW). In this paper, we present a framework for a class of graph join indices used for indexing queries defined on materialized views. We develop storage cost needed for these indices, and query processing strategies using them. We formulate the graph join index selection problem, and present algorithms which can provide good query performance under limited storage space for the indices. We also evaluate these algorithms to show their utilities by using an example taken from Informix white paper.