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Given a replicated database, a divergent design tunes the indexes in eachreplica differently in order to specialize it for a specific subset of theworkload. This specialization brings significant performance gains compared tothe common practice of having the same indexes in all replicas, but requiresthe development of new tuning tools for database administrators. In this paperwe introduce RITA (Replication-aware Index Tuning Advisor), a noveldivergent-tuning advisor that offers several essential features not found inexisting tools: it generates robust divergent designs that allow the system toadapt gracefully to replica failures; it computes designs that spread the loadevenly among specialized replicas, both during normal operation and whenreplicas fail; it monitors the workload online in order to detect changes thatrequire a recomputation of the divergent design; and, it offers suggestions toelastically reconfigure the system (by adding/removing replicas oradding/dropping indexes) to respond to workload changes. The key technicalinnovation behind RITA is showing that the problem of selecting an optimaldesign can be formulated as a Binary Integer Program (BIP). The BIP has arelatively small number of variables, which makes it feasible to solve itefficiently using any off-the-shelf linear-optimization software. Experimentalresults demonstrate that RITA computes better divergent designs compared toexisting tools, offers more features, and has fast execution times.

RITA: An Index-Tuning Advisor for Replicated Databases