Semantic partitioning as a basis for parallel I/O in database management systems

摘要

Modern applications such as ‘video on demand' require fast reading of complete files, which can be supported well by file striping. Many conventional applications, however, are only interested in some part of the available records. In order to avoid reading attributes irrelevant to such applications, each attribute could be stored in a separate (transposed) file. Aiming at I/O parallelism, byte-oriented striping could be applied to transposed files. However, such a fragmentation ignores the semantics of data. This fragmentation cannot be optimized by a database management system (DBMS) because a DBMS has to perform its tasks on the basis of data semantics. For example, queries must be translated into file operations using a scheme that maps a data model to a file system. However, details about files, such as the striping width, are invisible to a DBMS. Therefore, we propose to store each transposed file related to a composite type on a separate, independent disk drive, which means I/O parallelism tuned to a data model. As we also aim at system reliability and data availability, each transposed file must be duplicated on another drive. Consequently, a DBMS also has to guarantee correctness and completeness of the allocation of transposed files within an array of disk drives. As a solution independent of the underlying data model, we propose an abstract framework consisting of a meta model and a set of rules.