Abstract: Calculations to be performed on a massive data set may be delegated to a plurality of local servers for parallel processing. Each local server advances through a subset of database objects to determine if the objects are relevant to the calculation. If so, the objects' data is used as an operand to the calculation to generate intermediate results at the local server. The intermediate results of the various local servers are transmitted to a central server, which generates final results and transmits them back to the local servers. The local servers write the final results into each object in its respective subset, where relevant. The method is efficient because each object in the database is opened at most twice. Opening and closing database objects often involve transfers from bulk storage and, therefore, are some of the most time-consuming operations that computer systems perform.

Abstract: Calculations to be performed on a massive data set may be delegated to a plurality of local servers for parallel processing. Each local server advances through a subset of database objects to determine if the objects are relevant to the calculation. If so, the objects' data is used as an operand to the calculation to generate intermediate results at the local server. The intermediate results of the various local servers are transmitted to a central server, which generates final results and transmits them back to the local servers. The local servers write the final results into each object in its respective subset, where relevant. The method is efficient because each object in the database is opened at most twice. Opening and closing database objects often involve transfers from bulk storage and, therefore, are some of the most time-consuming operations that computer systems perform.