We present a mechanism for updating views in Object DataBase Systems (ODBS). Starting from an existing view data model, chronologically in line with [AB91, ADdS94, dS95a], we extend it to provide data update ability. Updates to

We present a framework for designing, in a declarative and flexible way, efficient migration programs and an undergoing implementation of a migration tool called RelO0 whose targets are any ODBC compliant system on the relational side and the 02 system on the object side. The framework consists of (i) a declarative language to specify database trans- formations from relations to objects, but also physical properties on the object database (clustering and sorting) and (ii) an algebra-based program rewriting technique which optimizes the migration processing time while taking into account physical properties and transaction decomposition. To achieve

Applications such as warehouse maintenance need to load large data volumes regularly. The efficiency of loading depends on the resources that are available at the source and at the target systems. Our work aims to understand the performance criteria that are involved in bulk loading data into a database and devise tailored optimization strategies. Unlike commercial systems and previous research on the same topic, our approach follows the fundamental database principle of physical-logical independence. A loading program is represented as a sequence of algebraic expressions. This abstraction enables the use of appropriate algebraic rewritings to optimize a loading program and of a cost model that takes into consideration efficiency criteria such as the processing times at the source and target systems and the bandwidth between them. A slow loading program may be preferable if it does not slow down other applications by consuming too much memory. Thus, we view the problem of optimizing a loading program as finding a compromise between several efficiency criteria. The ability to represent loading programs in an algebra and performance criteria in a cost model has two very desirable properties: reusability and efficiency. Database programmers do not have to write loading programs by hand. In addition, tuning loading programs becomes easier since programmers have a better control on the performance criteria specified in the cost model. The algebra captures data transformations that would have been

We present novel optimization techniques for bulk loading into databases. The aim of this work is to capture, understand and optimize different performance criteria (e.g., elapsed time, bandwidth, memory consumption) when populating a database with a large amount of data. This work applies to many applications where large amounts of data are manipulated: datawarehouses, replicated databases, etc. As opposed to commercial systems [Ora96, Obj, O2T96, Gem, Exe97, Pac91] and previous research work on the same topic [Fon97, WN95, WN96, WJLG00], our approach follows the fundamental database principle of physical-logical independence. A bulk loading program is represented as a sequence of algebraic expressions; it is optimized using equivalences, physical organization directives (e.g. cluster specifications on target data) and a cost model that captures efficiency requirements (e.g., is bandwidth more important than processing time at the source system?); from the optimized algebraic expressions, code is generated. This approach offers two very desirable properties: true efficiency and reusability. (i) There is not one good way to measure the efficiency of a bulk loading program. For instance, a program that runs slowly may be preferable to one that runs very fast because it does not slow down other applications by consuming lots of memory. By allowing users to specify their efficiency requirements, we make sure that they are satisfied. (ii) The optimization phase is not specific to one system or even one data model. The optimizer that we implemented can in fact be used for loading data from and to any structured support (e.g., relational or object databases, any file with a known grammar). We validated our approach by an implementation of a complete environ...