Organizational
Topic: Self-Tuning Databases
Selfoptimizing database systems are one of the most exciting areas of
interest in current database research. One of the reasons is the
growing volume and the dynamics of data which have to be administered.
There are also new application fields like "knowledge discovery in databases", which accomplishes several tasks of analysis at the same time
on the data. That makes a manual optimization, for example the access
paths (indices, etc..), ever more difficult. A solution for this is the
automatic adaptation of system parameters, which is called Self-Tuning.
More Recent Readings
We are trying to keep this Web site up to date with links to publications
published during or after the seminar.
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Guy M. Lohman, Roberta J. Cochrane,
Hamid Pirahesh, Latha Colby,
Daniel C. Zilio, Calisto Zuzarte,
Sam Lightstone, Wenbin Ma,
Eric Alton,
Dongming Liang, Jarek Gryz, Gary Valentin
Recommending Materialized Views and Indexes with the IBM DB2 Design
Advisor
Topics of the seminar
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19.11.2003
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Martin Erxleben
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State-of-the-Art
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Robert Müller
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Projects from
Microsoft & IBM
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[1], [2], [3],
[4], [5], [6] |
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26.11.2003
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Marcel Giard
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Index Selection
tools in Microsoft SQL Server and IBM DB2
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03.12.2003
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Robert Rübner
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Automated Selection
of Materialized Views and Indexes for SQL Databases
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Andreas Winter
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An Evolutionary
Approach to Materialized Views Selection in a Data Warehouse Environment
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[9] |
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10.12.2003
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Rainer Habrecht
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Runtime Statistics
- Self-tuning Histograms
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[10], [11], [12],
[13], [14] |
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Anja Hildebrandt
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14.01.2004
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Mathias Körbs
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Data-Placement
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[15] |
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Thomas Heutling
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Data-Placement
- Physical Database Design for Data Warehouse
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[16], [17] |
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21.01.2004
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Andre Riedel
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Memory Managment
- Goal-Oriented Buffer Management Revisited
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[18] |
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Sangeetha Sivaprakasam
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Memory
Management for Data Servers
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[18], [19] |
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28.01.2004
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Stefan Gerdelbracht
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The COMFORT
- Automatic Tuning Project
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[20] |
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Lakshmi Dhevi Baskar
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Towards
a Self-tuning - RISC-Style Database System
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[20], [21] |
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References:
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| [1] |
David Lomet, Roger Barga, Surajit Chaudhuri, Paul Larson:
„The
Microsoft Database Research Group" |
| [2] |
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| [3] |
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| [4] |
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| [5] |
Sam S. Lightstone, Guy M. Lohmann, Danny Zilio:
"Toward
Autonomic COmputing with DB2 Universal Database" |
| [6] |
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| [7] |
G. Lohman, G. Valentin, D. Zilio, M. Zuliani, A Skelly:
"DB2 Advisor:
An optimizer smart enough to recommend its own indexes"
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| [8] |
Baralis, Paraboschi, Teniente:
"Materialized
View Selection in a Multidimensional Database" |
| [9] |
Chuan Zhang, Xin Yao, Jian Yang:
"An
Evolutionary Approach to Materialized Views Selection in a Data Warehouse
Environment" |
| [10] |
Ashraf Aboulnaga, Surajit Chaudhuri:
"Self-tuning
histograms: building histograms without looking at data" |
| [11] |
Nicolas Bruno, Surajit Chaudhuri, Luis Gravano:
"STHoles: a multidimensional
workload-aware histogram" |
| [12] |
Chung-Min Chen, Nick Roussopoulos:
"Adaptive
selectivity estimation using query feedback" |
| [13] |
M. Muralikrishna, David J. DeWitt:
"Equi-depth histograms for estimating selectivity factors for
multi-dimensional queries" |
| [14] |
Viswanath Poosala, Yannis E. Ioannidis:
"Selectivity
estimation without the attribute value independence assumption" |
| [15] |
S. Agrawal, S. Chaudhuri, A. Das, V. Narasayya:
"Automating
layout of relational databases" |
| [16] |
W. J. Labio, D. Quass, B. Adelberg:
"Physical
database design for data warehouse" |
| [17] |
W. J. Labio, D. Quass, B. Adelberg:
"Physical database
design for data darehouse – the vis problem. Technical Report" |
| [18] |
K. P. Brown, M. J. Carey, M. Livny:
"Goal-Oriented
Buffer Management Revisited" |
| [19] |
Chen,C.M.,Roussopoulos:
"Adaptive
database buffer allocation using query feedback" |
| [20] |
G.Weikum, C.Hasse, A.Moenkeberg, P.Zabback:
"The
COMFORT Automatic Tuning Project" |
| [21] |
A.Geppert, K.R.Dittrich:
"Towards New Construction Paradigm For Persistent Systems" |
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