Optimizer and parallel engine extensions for handling expensive methods based on large objects

Object-relational database systems allow users to define new types and functions. This typing extension allows structural semantics to be applied to new data types (non-SQL92 data types). However, defining new, large, complex objects within a tuple is not always practical. Practicality alone requires that large object data structures be used. This implies that predicate evaluation can be performed on tuple columns that are physically stored outside of a tuple´s physical record. This out-of-line storage mechanism is commonly used today for column values that are physically large (implemented with a large object descriptor in the tuple pointing to a large object data structure). This type of predicate-based evaluation presents new optimizer and run-time challenges to the database system on clustered and massively parallel processor shared-nothing architectures