Autonomous Management of Soft Indexes

In recent years the support for index tuning as part of physical database design has gained focus in research and product development, which resulted in index and design advisors. Nevertheless, these tools provide a one-off solution for a continuous task and are not deeply integrated with the DBMS functionality by only applying the query optimizer for index recommendation and profit estimation and decoupling the decision about and execution of index configuration changes from the core system functionality. In this paper we propose an approach that continuously collects statistics for recommended indexes and based on this, repetitively solves the Index Selection Problem (ISP). A key novelty is the on-the-fly index generation during query processing implemented by new query plan operators IndexBuildScan and SwitchPlan. Finally, we present the implementation and evaluation of the introduced concepts as part of the PostgreSQL system.