ABSTRACT

Modern information architectures place business logic in an application server and per-sistent objects in a relational DBMS. To effectively realize such architectures, we must surmount the problem of effectively fetching objects from DBMS to the application server. Object access patterns are not random; they are driven by applications and user behaviors. Naive implementations retrieve objects from the DBMS as such objects are requested by the application, costing a DBMS roundtrip for each query. This fact, coupled with the growing performance bottleneck of computer storage systems, has resulted in a significant amount of research improving object access behavior through predicting future access objects because throughput will continue to improve but latency will not. Latency will be an ever-increasing component of object access cost. In turn, object access cost is usually the bottleneck for modern high performance systems. This yields unacceptably poor performance when application server submits sequence of relational queries to DBMSs. A reasonable approach would be to generate prefetch queries that retrieve objects that would later be requested by the application. However, whereas some prefetch queries would be beneficial, some would not. Distinguishing between them is nontrivial in practice, because commer-cial DBMSs do not expose efficient query response-time estimators. First, there is no standardize