Journal ArticleDOI
Physical design refinement: The ‘merge-reduce’ approach
Nicolas Bruno,Surajit Chaudhuri +1 more
TLDR
This article proposes a transformational architecture that is based upon two novel primitive operations, called merging and reduction, that help refine a configuration, treating indexes and materialized views in a unified way, as well as succinctly explain the refinement process to DBAs.Abstract:
Physical database design tools rely on a DBA-provided workload to pick an “optimal” set of indexes and materialized views. Such tools allow either creating a new such configuration or adding new structures to existing ones. However, these tools do not provide adequate support for the incremental and flexible refinement of existing physical structures. Although such refinements are often very valuable for DBAs, a completely manual approach to refinement can lead to infeasible solutions (e.g., excessive use of space). In this article, we focus on the important problem of physical design refinement and propose a transformational architecture that is based upon two novel primitive operations, called merging and reduction. These operators help refine a configuration, treating indexes and materialized views in a unified way, as well as succinctly explain the refinement process to DBAs.read more
Citations
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Proceedings Article
Self-tuning database systems: a decade of progress
TL;DR: This paper primarily focuses on the problem of automated physical database design, and discusses advances in self-tuning database systems over the past decade based on the experience in the AutoAdmin project at Microsoft Research.
Proceedings ArticleDOI
An Online Approach to Physical Design Tuning
Nicolas Bruno,Surajit Chaudhuri +1 more
TL;DR: Algorithms that are always-on and continuously modify the current physical design reacting to changes in the query workload are designed, which have low overhead and take into account storage constraints, update statements, and the cost to create temporary physical structures.
Book
Materialized Views
Rada Chirkova,Jun Yang +1 more
TL;DR: This monograph provides an accessible introduction and reference to materialized views, explains its core ideas, highlights its recent developments, and points out its sometimes subtle connections to other research topics in databases.
Proceedings ArticleDOI
An architecture for recycling intermediates in a column-store
TL;DR: This paper studies an architecture that harvests the by-products of the operator-at-a-time paradigm in a column store system using a lightweight mechanism, the recycler, and indicates the potentials of recycling intermediates and charters a route for further development of database kernels.
Journal ArticleDOI
Merging what's cracked, cracking what's merged: adaptive indexing in main-memory column-stores
TL;DR: In this article, a family of hybrid algorithms for adaptive indexing in column-store database systems is presented, and compared with traditional full index lookup and scan of unordered data.
References
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TL;DR: This paper will concern you to try reading problem solving methods in artificial intelligence as one of the reading material to finish quickly.
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Journal ArticleDOI
A methodology for the real world
Gregory J. Chaitin,Marc Alan Auslander,Ashok K. Chandra,John Cocke,Martin Edward Hopkins,Peter Willy Markstein +5 more
TL;DR: Preliminary results of an experimental implementation in a PL/I optimizing compiler suggest that global register allocation approaching that of hand-coded assembly language may be attainable.
Proceedings Article
Automated Selection of Materialized Views and Indexes in SQL Databases
TL;DR: This paper presents an end-to-end solution to the problem of selecting materialized views and indexes for SQL databases, and describes results of extensive experimental evaluation that demonstrate the effectiveness of the techniques.