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SIGMETRICS '90 Proceedings of the 1990 ACM SIGMETRICS conference on Measurement and modeling of computer systems
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IEEE Transactions on Computers
Goal-oriented buffer management revisited
SIGMOD '96 Proceedings of the 1996 ACM SIGMOD international conference on Management of data
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SIGMOD '97 Proceedings of the 1997 ACM SIGMOD international conference on Management of data
An optimality proof of the LRU-K page replacement algorithm
Journal of the ACM (JACM)
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IEEE/ACM Transactions on Networking (TON)
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The VLDB Journal — The International Journal on Very Large Data Bases
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IEEE Transactions on Computers
Optimal Buffer Allocation in A Multi-Query Environment
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CASCON '01 Proceedings of the 2001 conference of the Centre for Advanced Studies on Collaborative research
Goal-oriented dynamic buffer pool management for data base systems
ICECCS '95 Proceedings of the 1st International Conference on Engineering of Complex Computer Systems
Scalable Service Differentiation in a Shared Storage Cache
ICDCS '03 Proceedings of the 23rd International Conference on Distributed Computing Systems
Techniques for automatically sizing multiple buffer pools in DB2
CASCON '03 Proceedings of the 2003 conference of the Centre for Advanced Studies on Collaborative research
Dynamic Partitioning of Shared Cache Memory
The Journal of Supercomputing
Dynamic tracking of page miss ratio curve for memory management
ASPLOS XI Proceedings of the 11th international conference on Architectural support for programming languages and operating systems
Joint Power Management of Memory and Disk
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OSDI '02 Proceedings of the 5th symposium on Operating systems design and implementationCopyright restrictions prevent ACM from being able to make the PDFs for this conference available for downloading
Automatic Diagnosis of Performance Problems in Database Management Systems
ICAC '05 Proceedings of the Second International Conference on Automatic Computing
CAR: Clock with Adaptive Replacement
FAST '04 Proceedings of the 3rd USENIX Conference on File and Storage Technologies
Continuous resource monitoring for self-predicting DBMS
MASCOTS '05 Proceedings of the 13th IEEE International Symposium on Modeling, Analysis, and Simulation of Computer and Telecommunication Systems
A page fault equation for modeling the effect of memory size
Performance Evaluation
Adaptive self-tuning memory in DB2
VLDB '06 Proceedings of the 32nd international conference on Very large data bases
SQL memory management in Oracle9i
VLDB '02 Proceedings of the 28th international conference on Very Large Data Bases
A study of replacement algorithms for a virtual-storage computer
IBM Systems Journal
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KES '09 Proceedings of the 13th International Conference on Knowledge-Based and Intelligent Information and Engineering Systems: Part II
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Data & Knowledge Engineering
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Computer Science - Research and Development
A cache miss equation for partitioning an NDN content store
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An equation-based Heap Sizing Rule
Performance Evaluation
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Current businesses rely heavily on efficient access to their databases. Manual tuning of these database systems by performance experts is increasingly infeasible: For small companies, hiring an expert may be too expensive; for large enterprises, even an expert may not fully understand the interaction between a large system and its multiple changing workloads. This trend has led major vendors to offer tools that automatically and dynamically tune a database system. Many database tuning knobs concern the buffer pool for caching data and disk pages. Specifically, these knobs control the buffer allocation and thus the cache miss probability, which has direct impact on performance. Previous methods for automatic buffer tuning are based on simulation, black-box control, gradient descent, and empirical equations. This article presents a new approach, using calculations with an analytically-derived equation that relates miss probability to buffer allocation; this equation fits four buffer replacement policies, as well as twelve datasets from mainframes running commercial databases in large corporations. The equation identifies a buffer-size limit that is useful for buffer tuning and powering down idle buffers. It can also replace simulation in predicting I/O costs. Experiments with PostgreSQL illustrate how the equation can help optimize online buffer partitioning, ensure fairness in buffer reclamation, and dynamically retune the allocation when workloads change. It is also used, in conjunction with DB2's interface for retrieving miss data, for tuning DB2 buffer allocation to achieve targets for differentiated service.