On-line analytical processing on large databases managed by computational grids

Management of large data repositories integrated into the grid poses new challenges for grid research. There already exist several successful data grid projects addressing processing files storing large volumes of scientific data and projects developing services for accessing remote relational and XML databases. However, so far, no effort was devoted to on-line analytical processing (OLAP), an essential support for modern decision support systems. We present our approach to the design and implementation of a grid-enabled OLAP server, which is one functional building block of the GridMiner system, a novel infrastructure for knowledge discovery in grid databases. We present the global architecture model of our solution, describe how the OLAP components are integrated into the GridMiner system, and present the software architecture of our first prototype. The OLAP components were implemented in Java on top of the software toolkit Globus 3.