This is the first of a three year continuing award. The increasing size and decreasing cost of semiconductor memory has prompted research into databases which are memory resident. These Main Memory DataBase (MMDB) systems are aimed at high throughput applications such as airline reservation systems, phone switching databases, and other real time systems where the availability of the memory resident data is crucial. To achieve this high availability with volatile RAM requires a backup archive database on disk as well as efficient algorithms to checkpoint the database to the archive and to recover it from the archive to main memory after a system failure. It has been shown that MMDB systems often perform better with deferred update techniques where data to be updated is first placed in a special nonvolatile shadow area and only at transaction commit time is placed in main memory. The authors are investigating both checkpointing and reloading of MMDB databases with the use of more conventional immediate update (IU) techniques as well as deferred update (DU) strategies. The best checkpointing approaches are to be determined as are partial reloading strategies. A partial reload allows the database to be brought online after a system failure faster because not all of the MMDB is reloaded prior to bringing the system up. This research represents the first examination of techniques for partial reloading of MMDB systems. Due to the volatility of RAM, the high throughput needs of MMDB applications, and the potential for partial reloading to dramatically increase the uptime of database systems, the results and impact of this research are both widespread and significant.
