From structured documents to novel query facilities
SIGMOD '94 Proceedings of the 1994 ACM SIGMOD international conference on Management of data
Storing semistructured data with STORED
SIGMOD '99 Proceedings of the 1999 ACM SIGMOD international conference on Management of data
Efficient evaluation of XML middle-ware queries
SIGMOD '01 Proceedings of the 2001 ACM SIGMOD international conference on Management of data
Proceedings of the 2002 ACM SIGMOD international conference on Management of data
Holistic twig joins: optimal XML pattern matching
Proceedings of the 2002 ACM SIGMOD international conference on Management of data
ICDT '03 Proceedings of the 9th International Conference on Database Theory
Relational Databases for Querying XML Documents: Limitations and Opportunities
VLDB '99 Proceedings of the 25th International Conference on Very Large Data Bases
Efficiently Publishing Relational Data as XML Documents
VLDB '00 Proceedings of the 26th 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
An Efficient Cost-Driven Index Selection Tool for Microsoft SQL Server
VLDB '97 Proceedings of the 23rd International Conference on Very Large Data Bases
Efficient Relational Storage and Retrieval of XML Documents
Selected papers from the Third International Workshop WebDB 2000 on The World Wide Web and Databases
XML and Object-Relational Database Systems - Enhancing Structural Mappings Based on Statistics
Selected papers from the Third International Workshop WebDB 2000 on The World Wide Web and Databases
The VLDB Journal — The International Journal on Very Large Data Bases
Oracle8i"The XML Enabled Data Management System
ICDE '00 Proceedings of the 16th International Conference on Data Engineering
DB2 Advisor: An Optimizer Smart Enough to Recommend its own Indexes
ICDE '00 Proceedings of the 16th International Conference on Data Engineering
ViST: a dynamic index method for querying XML data by tree structures
Proceedings of the 2003 ACM SIGMOD international conference on Management of data
From XML Schema to Relations: A Cost-Based Approach to XML Storage
ICDE '02 Proceedings of the 18th International Conference on Data Engineering
Integrating vertical and horizontal partitioning into automated physical database design
SIGMOD '04 Proceedings of the 2004 ACM SIGMOD international conference on Management of data
Efficient XML-to-SQL query translation: where to add the intelligence?
VLDB '04 Proceedings of the Thirtieth international conference on Very large data bases - Volume 30
Xpath on steroids: exploiting relational engines for xpath performance
Proceedings of the 2007 ACM SIGMOD international conference on Management of data
XML reconstruction view selection in XML databases: complexity analysis and approximation scheme
COCOA'10 Proceedings of the 4th international conference on Combinatorial optimization and applications - Volume Part II
Hi-index | 0.00 |
Much of business XML data has accompanying XSD specifications. In many scenarios, "shredding驴 such XML data into a relational storage is a popular paradigm. Optimizing evaluation of XPath queries over such XML data requires paying careful attention to both the logical and physical designs of the relational database where XML data is shredded. None of the existing solutions has taken into account physical design of the generated relational database. In this paper, we study the interplay of logical and physical design and conclude that 1) solving them independently leads to suboptimal performance and 2) there is substantial overlap between logical and physical designs: some well-known logical design transformations generate the same mappings as physical design. Furthermore, existing search algorithms are inefficient to search the extremely large space of logical and physical design combinations. We propose a search algorithm that carefully avoids searching duplicated mappings and utilizes the workload information to further prune the search space. Experimental results confirm the effectiveness of our approach.