ACM SIGMOD Record
TPC releases new benchmark: TPC-C
ACM SIGMETRICS Performance Evaluation Review
Making B+- trees cache conscious in main memory
SIGMOD '00 Proceedings of the 2000 ACM SIGMOD international conference on Management of data
ICDE '95 Proceedings of the Eleventh International Conference on Data Engineering
Automatic physical design tuning: workload as a sequence
Proceedings of the 2006 ACM SIGMOD international conference on Management of data
DB2 design advisor: integrated automatic physical database design
VLDB '04 Proceedings of the Thirtieth international conference on Very large data bases - Volume 30
Automatic SQL tuning in oracle 10g
VLDB '04 Proceedings of the Thirtieth international conference on Very large data bases - Volume 30
Autonomous Management of Soft Indexes
ICDEW '07 Proceedings of the 2007 IEEE 23rd International Conference on Data Engineering Workshop
On-Line Index Selection for Shifting Workloads
ICDEW '07 Proceedings of the 2007 IEEE 23rd International Conference on Data Engineering Workshop
Poster session: Constrained dynamic physical database design
ICDEW '08 Proceedings of the 2008 IEEE 24th International Conference on Data Engineering Workshop
Self-selecting, self-tuning, incrementally optimized indexes
Proceedings of the 13th International Conference on Extending Database Technology
Merging what's cracked, cracking what's merged: adaptive indexing in main-memory column-stores
Proceedings of the VLDB Endowment
Partitioning techniques for fine-grained indexing
ICDE '11 Proceedings of the 2011 IEEE 27th International Conference on Data Engineering
Stochastic database cracking: towards robust adaptive indexing in main-memory column-stores
Proceedings of the VLDB Endowment
SMIX Live -- A Self-Managing Index Infrastructure for Dynamic Workloads
ICDE '12 Proceedings of the 2012 IEEE 28th International Conference on Data Engineering
An Improved Indirect Time-domain Technique on Lower Frequency Antenna
ICCIS '12 Proceedings of the 2012 Fourth International Conference on Computational and Information Sciences
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As databases accumulate growing amounts of data at an increasing rate, adaptive indexing becomes more and more important. At the same time, applications and their use get more agile and flexible, resulting in less steady and less predictable workload characteristics. Being inert and coarse-grained, state-of-the-art index tuning techniques become less useful in such environments. Especially the full-column indexing paradigm results in many indexed but never queried records and prohibitively high storage and maintenance costs. In this paper, we present Self-Managing Indexes, a novel, adaptive, fine-grained, autonomous indexing infrastructure. In its core, our approach builds on a novel access path that automatically collects useful index information, discards useless index information, and competes with its kind for resources to host its index information. Compared to existing technologies for adaptive indexing, we are able to dynamically grow and shrink our indexes, instead of incrementally enhancing the index granularity.