  Materialized views and indexes are physical structures for accelerating data
access that are casually used in data warehouses. However, these data
structures generate some maintenance overhead. They also share the same storage
space. Most existing studies about materialized view and index selection
consider these structures separately. In this paper, we adopt the opposite
stance and couple materialized view and index selection to take view-index
interactions into account and achieve efficient storage space sharing.
Candidate materialized views and indexes are selected through a data mining
process. We also exploit cost models that evaluate the respective benefit of
indexing and view materialization, and help select a relevant configuration of
indexes and materialized views among the candidates. Experimental results show
that our strategy performs better than an independent selection of materialized
views and indexes.
