Object-relational databases extend the capabilities of the relational databases by allowing definition of new data types and methods to operate on these data types while retaining most of the relational model semantics. In this paper, we examine issues related to parallel processing of queries in object-relational model with respect to efficient storage and retrieval of large objects. We extend the concept of collective I/O and other related techniques like request merging and data sieving for I/O in the database domain to achieve high performance in retrieval of large objects and their use in efficient query processing. The I/O optimization problem is dealt in query executor, access methods as well as in the low level runtime system. We also propose a new technique pooled striping for efficient storage and retrieval of large objects on multiple disks.

Gzipped Postscript version of the paper