Optimized parallel sets for data intensive applications

An extension of a general-purpose programming language (gpPL) is presented. It enables parallelism, persistence and query optimization based on sets. The authors demonstrate that in gpPLs the primitive “set” can be generalised for the needs of database and expert system applications. Side-effect free declarative queries, based on set expressions, can be optimized and executed in parallel. Individual optimization and parallelization are integral parts of the language system and compiler. Very different combinations of persistent or volatile, and parallel or sequential, and optimized or non-optimized implementations are possible. This is eased by the fact that a great part of the implementation is located outside the compiler with the help of predefined interfaces. Different algebras, optimizers or algorithms can be considered. The same program can be executed without modification in various systems or platforms