When is it time to rethink the aggregate configuration of your OLAP server?
Proceedings of the VLDB Endowment
Index interactions in physical design tuning: modeling, analysis, and applications
Proceedings of the VLDB Endowment
Benchmarking adaptive indexing
TPCTC'10 Proceedings of the Second TPC technology conference on Performance evaluation, measurement and characterization of complex systems
Merging what's cracked, cracking what's merged: adaptive indexing in main-memory column-stores
Proceedings of the VLDB Endowment
Semi-automatic index tuning: keeping DBAs in the loop
Proceedings of the VLDB Endowment
Stochastic database cracking: towards robust adaptive indexing in main-memory column-stores
Proceedings of the VLDB Endowment
Concurrency control for adaptive indexing
Proceedings of the VLDB Endowment
Holistic indexing: offline, online and adaptive indexing in the same kernel
PhD '12 Proceedings of the on SIGMOD/PODS 2012 PhD Symposium
Proceedings of the 27th Annual ACM Symposium on Applied Computing
Adaptive indexing in modern database kernels
Proceedings of the 15th International Conference on Extending Database Technology
SMIX: self-managing indexes for dynamic workloads
Proceedings of the 25th International Conference on Scientific and Statistical Database Management
Workload management: a technology perspective with respect to self-* characteristics
Artificial Intelligence Review
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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.