Automated Selection of Materialized Views and Indexes for SQL Databases Sanjay Agrawal Surajit Chaudhuri Vivek Narasayya Microsoft Research Microsoft Research Microsoft Research
[email protected] [email protected] [email protected] Abstract large number of recent papers in this area, most of the Automatically selecting an appropriate set of prior work considers the problems of index selection and materialized views and indexes for SQL materialized view selection in isolation. databases is a non-trivial task. A judicious choice Although indexes and materialized views are similar, must be cost-driven and influenced by the a materialized view is much richer in structure than an workload experienced by the system. Although index since a materialized view may be defined over there has been work in materialized view multiple tables, and can have selections and GROUP BY selection in the context of multidimensional over multiple columns. In fact, an index can logically be (OLAP) databases, no past work has looked at considered as a special case of a single-table, projection the problem of building an industry-strength tool only materialized view. This richness of structure of for automated selection of materialized views materialized views makes the problem of selecting and indexes for SQL workloads. In this paper, materialized views significantly more complex than that we present an end-to-end solution to the problem of index selection. We therefore need innovative of selecting materialized views and indexes. We techniques for dealing with the large space of potentially describe results of extensive experimental interesting materialized views that are possible for a given evaluation that demonstrate the effectiveness of set of SQL queries and updates over a large schema.