Semantics and implementation of schema evolution in object-oriented databases
SIGMOD '87 Proceedings of the 1987 ACM SIGMOD international conference on Management of data
The Gem–Stone data management system
Object-oriented concepts, databases, and applications
Primitives for schema updates in an Object-Oriented Database System: a proposal
Computer Standards & Interfaces - Special volume on the Object-Oriented Database Task Group
The object database standard: ODMG 2.0
The object database standard: ODMG 2.0
SERF: schema evolution through an extensible, re-usable and flexible framework
Proceedings of the seventh international conference on Information and knowledge management
SERF: ODMG-based generic re-structuring facility
SIGMOD '99 Proceedings of the 1999 ACM SIGMOD international conference on Management of data
Updating Distributed Materialized Views
IEEE Transactions on Knowledge and Data Engineering
Extending Logging for Database Snapshot Refresh
VLDB '87 Proceedings of the 13th International Conference on Very Large Data Bases
Implementing Lazy Database Updates for an Object Database System
VLDB '94 Proceedings of the 20th International Conference on Very Large Data Bases
Advanced Principles for Changing Schemas of Object Databases
CAiSE ;96 Proceedings of the 8th International Conference on Advances Information System Engineering
Correctness of Lazy Database Updates for Object Database Systems
Proceedings of the Sixth International Workshop on Persistent Object Systems
Modeling data warehouse schema evolution over extended hierarchy semantics
Journal on Data Semantics XIII
Optimising schema evolution operation sequences in object databases for data evolution
ER'12 Proceedings of the 31st international conference on Conceptual Modeling
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More than ever before schema transformation is a prevalent problem that needs to be addressed to accomplish for example the migration of legacy systems to the newer OODB systems, the generation of structured web pages from data in database systems, or the integration of systems with different native data models. Such schema transformations are typically composed of a sequence of schema evolution operations. The execution of such sequences can be very time-intensive, possibly requiring many hours or even days and thus effectively making the database unavailable for unacceptable time spans. While researchers have looked at the deferred execution approach for schema evolution in an effort to improve availability of the system, to the best of our knowledge ours is the first effort to provide a direct optimization strategy for a sequence of changes. In this paper, we propose heuristics for the iterative elimination and cancellation of schema evolution primitives as well as for the merging of database modifications of primitives such that they can be performed in one efficient transformation pass over the database. In addition we show the correctness of our optimization approach, thus guaranteeing that the initial input and the optimized output schema evolution sequence produce the same final schema and data state. We provide proof of the algorithm's optimality by establishing the confluence property of our problem search space, i.e., we show that the iterative application of our heuristics always terminates and converges to a unique minimal sequence. Moreover, we have conducted experimental studies that demonstrate the performance gains achieved by our proposed optimization technique over previous solutions.