  Indices and materialized views are physical structures that accelerate data
access in data warehouses. However, these data structures generate some
maintenance overhead. They also share the same storage space. The existing
studies about index and materialized view selection consider these structures
separately. In this paper, we adopt the opposite stance and couple index and
materialized view selection to take into account the interactions between them
and achieve an efficient storage space sharing. We develop cost models that
evaluate the respective benefit of indexing and view materialization. These
cost models are then exploited by a greedy algorithm to select a relevant
configuration of indices and materialized views. Experimental results show that
our strategy performs better than the independent selection of indices and
materialized views.
