View maintenance in a warehousing environment
SIGMOD '95 Proceedings of the 1995 ACM SIGMOD international conference on Management of data
Incremental maintenance of views with duplicates
SIGMOD '95 Proceedings of the 1995 ACM SIGMOD international conference on Management of data
Efficient maintenance of materialized mediated views
SIGMOD '95 Proceedings of the 1995 ACM SIGMOD international conference on Management of data
Algorithms for deferred view maintenance
SIGMOD '96 Proceedings of the 1996 ACM SIGMOD international conference on Management of data
Efficient view maintenance at data warehouses
SIGMOD '97 Proceedings of the 1997 ACM SIGMOD international conference on Management of data
The TSIMMIS Approach to Mediation: Data Models and Languages
Journal of Intelligent Information Systems - Special issue: next generation information technologies and systems
How to roll a join: asynchronous incremental view maintenance
SIGMOD '00 Proceedings of the 2000 ACM SIGMOD international conference on Management of data
DyDa: data warehouse maintenance in fully concurrent environments
SIGMOD '01 Proceedings of the 2001 ACM SIGMOD international conference on Management of data
Data integration: a theoretical perspective
Proceedings of the twenty-first ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
The EVE Approach: View Synchronization in Dynamic Distributed Environments
IEEE Transactions on Knowledge and Data Engineering
Optimizing Queries Across Diverse Data Sources
VLDB '97 Proceedings of the 23rd International Conference on Very Large Data Bases
Schema Mapping as Query Discovery
VLDB '00 Proceedings of the 26th International Conference on Very Large Data Bases
Generic Schema Matching with Cupid
Proceedings of the 27th International Conference on Very Large Data Bases
Materialized View Maintenance Using Version Numbers
DASFAA '99 Proceedings of the Sixth International Conference on Database Systems for Advanced Applications
The CVS Algorithm for View Synchronization in Evolvable Large-Scale Information Systems
EDBT '98 Proceedings of the 6th International Conference on Extending Database Technology: Advances in Database Technology
Piazza: data management infrastructure for semantic web applications
WWW '03 Proceedings of the 12th international conference on World Wide Web
View Maintenance after View Synchronization
IDEAS '99 Proceedings of the 1999 International Symposium on Database Engineering & Applications
Proceedings of the 2003 ACM SIGMOD international conference on Management of data
Detection and Correction of Conflicting Source Updates for View Maintenance
ICDE '04 Proceedings of the 20th International Conference on Data Engineering
Incremental Maintenance of Schema-Restructuring Views in SchemaSQL
IEEE Transactions on Knowledge and Data Engineering
Multiversion-based view maintenance over distributed data sources
ACM Transactions on Database Systems (TODS)
Semantic adaptation of schema mappings when schemas evolve
VLDB '05 Proceedings of the 31st international conference on Very large data bases
Mapping adaptation under evolving schemas
VLDB '03 Proceedings of the 29th international conference on Very large data bases - Volume 29
Metadata management in a multiversion data warehouse
Journal on data semantics VIII
DWEVOLVE: a requirement based framework for data warehouse evolution
ACM SIGSOFT Software Engineering Notes
Hi-index | 0.00 |
Data integration over multiple heterogeneous data sources has become increasingly important for modern applications. The integrated data is usually stored as materialized views to allow better access, performance, and high availability. In loosely coupled environments, such as the Data Grid, the data sources are autonomous. Hence, the source updates can be concurrent and cause erroneous results during view maintenance. State-of-the-art maintenance strategies apply compensating queries to correct such errors, making the restricting assumption that all source schemata remain static over time. However, in such dynamic environments, the data sources may change not only their data but also their schema. Consequently, either the maintenance queries or the compensating queries may fail. In this paper, we propose a novel framework called DyDa that overcomes these limitations and handles both source data updates and schema changes. We identify three types of maintenance anomalies, caused by either source data updates, data-preserving schema changes, or non-data-preserving schema changes. We propose a compensation algorithm to solve the first two types of anomalies. We show that the third type of anomaly is caused by the violation of dependencies between maintenance processes. Then, we propose dependency detection and correction algorithms to identify and resolve the violations. Put together, DyDa extends prior maintenance solutions to solve all types of view maintenance anomalies. The experimental results show that DyDa imposes a minimal overhead on data update processing while allowing for the extended functionality to handle concurrent schema changes.