Most queries in a collection of queries, also called a query workload, to some degree have parts of their intermediate execution steps in common. These intermediate exe- cution steps, also called subexpressions, provide the opportunity to further optimize query workload execution in addition to the already existing query optimization done by the DBMS. A lot of research has been done into this topic however most of that research is either proprietary or just not applicable to big query workloads. In this thesis I developed a simple yet effictive heuristic algorithm to quickly find common subexpressions and materialize them to disk using open source software with results showing a significant increase in performance.