Scaling Access to Heterogeneous Data Sources with DISCO

Accessing many data sources aggravates prob lems for users of heterogeneous distributed databases Database administrators must deal with fragile mediators that is mediators with schemas and views that must be sig ni cantly changed to incorporate a new data source When implementing translators of queries from mediators to data sources database implementors must deal with data sources that do not support all the functionality required by me diators Application programmers must deal with graceless failures for unavailable data sources Queries simply return failure and no further information when data sources are unavailable for query processing The Distributed Informa tion Search COmponent Disco addresses these problems Data modeling techniques manage the connections to data sources and sources can be added transparently to the users and applications The interface between mediators and data sources exibly handles di erent query languages and dif ferent data source functionality Query rewriting and op timization techniques rewrite queries so they are e ciently evaluated by sources Query processing and evaluation se mantics are developed to process queries over unavailable data sources In this article we describe a the distributed mediator architecture of Disco b the data model and its modeling of data source connections c the interface to un derlying data sources and the query rewriting process and d query processing semantics We describe several advan tages of our system