Adapting materialized views after redefinitions
SIGMOD '95 Proceedings of the 1995 ACM SIGMOD international conference on Management of data
View maintenance in a warehousing environment
SIGMOD '95 Proceedings of the 1995 ACM SIGMOD international conference on Management of data
On-line warehouse view maintenance
SIGMOD '97 Proceedings of the 1997 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
Evolvable view environment (EVE): non-equivalent view maintenance under schema changes
SIGMOD '99 Proceedings of the 1999 ACM SIGMOD international conference on Management of data
Maintaining data warehouses over changing information sources
Communications of the ACM
The Strobe algorithms for multi-source warehouse consistency
DIS '96 Proceedings of the fourth international conference on on Parallel and distributed information systems
SchemaSQL - A Language for Interoperability in Relational Multi-Database Systems
VLDB '96 Proceedings of the 22th International Conference on Very Large Data Bases
The SDCC Framework For Integrating Existing Algorithms for Diverse Data Warehouse Maintenance Tasks
IDEAS '99 Proceedings of the 1999 International Symposium on Database Engineering & Applications
View Maintenance after View Synchronization
IDEAS '99 Proceedings of the 1999 International Symposium on Database Engineering & Applications
A Transactional Model for Data Warehouse Maintenance
ER '02 Proceedings of the 21st International Conference on Conceptual Modeling
Multiversion-based view maintenance over distributed data sources
ACM Transactions on Database Systems (TODS)
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Data warehouses (DW) are an emerging technology to support high-level decision making by gathering information from several distributed information sources (ISs) into one materialized repository. In dynamic environments such as the web, DWs must be maintained in order to stay up-to-date. Recent maintenance algorithms tackle this problem of DW management under concurrent data updates (DU), whereas the EVE system is the first to handle (non-concurrent schema changes) (SC) of ISs. However, the concurrency of schema changes by different ISs as well as the concurrency of interleaved SC and DU still remain unexplored problems. In this paper, we propose a solution framework called DyDa that successfully addresses both problems. The DyDa framework detects concurrent SCs by the broken query scheme and conflicting concurrent DUs by a local timestamp scheme. The two-layered architecture of the DyDa framework separates the concerns for concurrent DU and concurrent SC handling without imposing any restrictions on the autonomy nor on the concurrent execution of the ISs. This DyDa solution is currently being implemented within the EVE data warehousing system.