Equi-depth multidimensional histograms
SIGMOD '88 Proceedings of the 1988 ACM SIGMOD international conference on Management of data
Mining association rules between sets of items in large databases
SIGMOD '93 Proceedings of the 1993 ACM SIGMOD international conference on Management of data
Mining quantitative association rules in large relational tables
SIGMOD '96 Proceedings of the 1996 ACM SIGMOD international conference on Management of data
Improved histograms for selectivity estimation of range predicates
SIGMOD '96 Proceedings of the 1996 ACM SIGMOD international conference on Management of data
Wavelet-based histograms for selectivity estimation
SIGMOD '98 Proceedings of the 1998 ACM SIGMOD international conference on Management of data
Self-tuning histograms: building histograms without looking at data
SIGMOD '99 Proceedings of the 1999 ACM SIGMOD international conference on Management of data
SIGMOD '85 Proceedings of the 1985 ACM SIGMOD international conference on Management of data
Mining frequent patterns without candidate generation
SIGMOD '00 Proceedings of the 2000 ACM SIGMOD international conference on Management of data
Global optimization of histograms
SIGMOD '01 Proceedings of the 2001 ACM SIGMOD international conference on Management of data
Database System Implementation
Database System Implementation
Access path selection in a relational database management system
SIGMOD '79 Proceedings of the 1979 ACM SIGMOD international conference on Management of data
Accurate estimation of the number of tuples satisfying a condition
SIGMOD '84 Proceedings of the 1984 ACM SIGMOD international conference on Management of data
A Query Processing Strategy for the Decomposed Storage Model
Proceedings of the Third International Conference on Data Engineering
Maintenance of Discovered Association Rules in Large Databases: An Incremental Updating Technique
ICDE '96 Proceedings of the Twelfth International Conference on Data Engineering
Mining Frequent Itemsets Using Support Constraints
VLDB '00 Proceedings of the 26th International Conference on Very Large Data Bases
Storage and Querying of E-Commerce Data
Proceedings of the 27th International Conference on Very Large Data Bases
Fast Algorithms for Mining Association Rules in Large Databases
VLDB '94 Proceedings of the 20th International Conference on Very Large Data Bases
Selectivity Estimation Without the Attribute Value Independence Assumption
VLDB '97 Proceedings of the 23rd International Conference on Very Large Data Bases
Effective and efficient semantic web data management over DB2
Proceedings of the 2008 ACM SIGMOD international conference on Management of data
Modeling and Querying E-Commerce Data in Hybrid Relational-XML DBMSs
ER '08 Proceedings of the 27th International Conference on Conceptual Modeling
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Electronic commerce is emerging as a major application area for database systems. A large number of e-commerce sites provide electronic product catalogs that allow users to search products of interest.Due to the constant evolution and the high sparsity of e-commerce data, most commercial e-commerce systems use the so-called vertical schema for data storage. However, query processing for data stored using vertical schema is extremely slow because current RDBMS, especially its cost-based query optimizer, is designed to deal with traditional horizontal schema efficiently.Most e-commerce systems would like to offer advanced parametric search capabilities to their users. However, most searches are expected to be on-line which means that the query execution should be very fast. RDBMSs require new capabilities and enhancements before they can satisfy the search performance criteria against vertical schema. The tightly-coupled enhancements and additions to a DBMS require considerable amount of work and may take a long time to be accomplished. In this paper, we describe an alternative approach called SAL, a Search Assistant Layer that can be implemented outside a database engine to accommodate the urgent need for efficient parametric search on e-commerce data. Our experimental results show that dramatic performance improvement is provided by SAL for search queries.