MOCHA: A self-extensible database middleware system for distributed data sources

We present MOCHA, a new self-extensible database middleware system designed to interconnect distributed data sources. MOCHA is designed to scale to la rge environments and is based on the idea that some of the user-defined fun ctionality in the system should be deployed by the middleware system itself . This is realized by shipping Java code implementing either advanced data types or tailored query operators to remote data sources and have it execut ed remotely. Optimized query plans push the evaluation of powerful data-red ucing operators to the data source sites while executing data-inflating ope rators near the client's site. The Volume Reduction Factor is a new and mor e explicit metric introduced in this paper to select the best site to execu te query operators and is shown to be more accurate than the standard selec tivity factor alone. MOCHA has been implemented in Java and runs on top of Informix and Oracle. We present the architecture of MOCHA, the ideas behind it, and a performance study using scientific data and queries. The results of this study demonstrate that MOCHA provides a more flexible, scalable an d efficient framework for distributed query processing compared to those in existing middleware solutions.