Using common subexpressions to speed up a set of queries is a well known and long studied problem. However, due to the isolation requirement, operating a database in the classic transactional way does not offer many applications to exploit the benefits of simultaneously computing a set of queries. In the opposite, many applications can be identified in the context of data warehousing, e. g. optimizing the incremental maintenance process of multiple dependent materialized views or the generation of application specific data marts. In the paper we discuss the problem whether it is always advisable to generate the most complete common predecessor for a given set of queries or to restrict a predecessor to a subset of all possible base tables. As we will see, this question cannot be answered without having knowledge about the cardinality of queries after aggregation. However, if we can rely on this information, we can come up with an optimal predecessor for a common set of queries.