Non first normal form relations: An algebra allowing data restructuring
Journal of Computer and System Sciences
Maintaining views incrementally
SIGMOD '93 Proceedings of the 1993 ACM SIGMOD international conference on Management of data
Research problems in data warehousing
CIKM '95 Proceedings of the fourth international conference on Information and knowledge management
Incremental maintenance of views with duplicates
SIGMOD '95 Proceedings of the 1995 ACM SIGMOD international conference on Management of data
The BUCKY object-relational benchmark
SIGMOD '97 Proceedings of the 1997 ACM SIGMOD international conference on Management of data
A first course in database systems
A first course in database systems
Incremental View Maintenance By Base Relation Tagging in Distributed Databases
Distributed and Parallel Databases
SQL: 1999, formerly known as SQL3
ACM SIGMOD Record
Informix guide to SQL
Object-Relational DBMSs: Tracking the Next Great Wave
Object-Relational DBMSs: Tracking the Next Great Wave
Oracle8 Database Design Using Uml Object Modeling
Oracle8 Database Design Using Uml Object Modeling
The Implementation of POSTGRES
IEEE Transactions on Knowledge and Data Engineering
Incremental Recomputation of Active Relational Expressions
IEEE Transactions on Knowledge and Data Engineering
IEEE Transactions on Knowledge and Data Engineering
Maintaining Temporal Views over Non-Temporal Information Sources for Data Warehousing
EDBT '98 Proceedings of the 6th International Conference on Extending Database Technology: Advances in Database Technology
Graph Structured Views and Their Incremental Maintenance
ICDE '98 Proceedings of the Fourteenth International Conference on Data Engineering
Incremental Maintenance for Materialized Views over Semistructured Data
VLDB '98 Proceedings of the 24rd International Conference on Very Large Data Bases
On Restructuring Nested Relations in Partitioned Normal Form
VLDB '90 Proceedings of the 16th International Conference on Very Large Data Bases
Of Objects and Databases: A Decade of Turmoil
VLDB '96 Proceedings of the 22th International Conference on Very Large Data Bases
Incremental Maintenance of Externally Materialized Views
VLDB '96 Proceedings of the 22th International Conference on Very Large Data Bases
View Maintenance in Object-Oriented Databases
DEXA '96 Proceedings of the 7th International Conference on Database and Expert Systems Applications
Incremental Maintenance of Materialized Views
DEXA '97 Proceedings of the 8th International Conference on Database and Expert Systems Applications
Implementing Incremental View Maintenance in Nested Data Models
DBLP-6 Proceedings of the 6th International Workshop on Database Programming Languages
Incremental Maintenance of Nested Relational Views
IDEAS '99 Proceedings of the 1999 International Symposium on Database Engineering & Applications
Typed Abstract State Machines for data-intensive applications
Knowledge and Information Systems
Hi-index | 0.00 |
View materialization is an important way of improving the performance of query processing. When an update occurs to the source data from which a materialized view is derived, the materialized view has to be updated so that it is consistent with the source data. This update process is called view maintenance . The incremental method of view maintenance, which computes the new view using the old view and the update to the source data, is widely preferred to full view recomputation when the update is small in size. In this paper we investigate how to incrementally maintain views in object-relational (OR) databases. The investigation focuses on maintaining views defined in OR-SQL, a language containing the features of object referencing, inheritance, collection, and aggregate functions including user-defined set aggregate functions. We propose an architecture and algorithms for incremental OR view maintenance. We implement all algorithms and analyze the performance of them in comparison with full view recomputation. The analysis shows that the algorithms significantly reduce the cost of updating a view when the size of an update to the source data is relatively small.