Integrating query processing with parallel languages

Abstract

In this thesis we propose new techniques for using parallel languages to improve query processing. Optimizing a query plan and its particular implementation is important for efficient processing on modern systems. First, we present our work on a parallel representation of queries using partitioned global address space languages that enables new optimizations. Next, we propose future work on cooperative optimization of query plans and imperative programs in the context of parallel applications that include queries.