ACM Transactions on Database Systems (TODS)
Randomized algorithms for optimizing large join queries
SIGMOD '90 Proceedings of the 1990 ACM SIGMOD international conference on Management of data
EDBT '94 Proceedings of the 4th international conference on extending database technology: Advances in database technology
Workload scheduling for multiple query processing
Information Processing Letters
Caching multidimensional queries using chunks
SIGMOD '98 Proceedings of the 1998 ACM SIGMOD international conference on Management of data
Cost-based optimization of decision support queries using transient-views
SIGMOD '98 Proceedings of the 1998 ACM SIGMOD international conference on Management of data
Efficient and extensible algorithms for multi query optimization
SIGMOD '00 Proceedings of the 2000 ACM SIGMOD international conference on Management of data
Pipelining in multi-query optimization
PODS '01 Proceedings of the twentieth ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
Cache investment: integrating query optimization and distributed data placement
ACM Transactions on Database Systems (TODS)
Optimizing Queries with Materialized Views
ICDE '95 Proceedings of the Eleventh International Conference on Data Engineering
Anatomy of a Mudular Multiple Query Optimizer
VLDB '88 Proceedings of the 14th International Conference on Very Large Data Bases
Dynamic Caching of Query Results for Decision Support Systems
SSDBM '99 Proceedings of the 11th International Conference on Scientific and Statistical Database Management
Evaluation of RDF queries via equivalence
Frontiers of Computer Science: Selected Publications from Chinese Universities
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Abstract--In this paper, we propose a novel demand-driven caching framework, called cache-on-demand (CoD). In CoD, intermediate/final answers of existing running queries are viewed as virtual caches that can be materialized if they are beneficial to incoming queries. Such an approach is essentially nonspeculative: the exact cost of investment and the return on investment are known, and the cache is certain to be reused! We address several issues for CoD to be realized. We also propose three optimizing strategies: Conform-CoD, Scramble-CoD, and Integrated-CoD. Conform-CoD and Scramble-CoD are based on a two-phase optimization framework, while Integrated-CoD operates in a single-phase framework. We conducted extensive performance study to evaluate the effectiveness of these algorithms. Our results show that all the CoD-based schemes can provide substantial performance improvement when compared with a predictive scheme and a no-caching scheme.