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Locking performance in centralized databases
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Source ACM Transactions on Database Systems (TODS) archive
Volume 10 ,  Issue 4  (December 1985) table of contents
Pages: 415 - 462  
Year of Publication: 1985
ISSN:0362-5915
Authors
Y. C. Tay  National Univ. of Singapore, Kent Ridge, Republic of Singapore
Nathan Goodman  Harvard Univ., Cambridge, MA
R. Suri  Harvard Univ., Cambridge, MA
Publisher
ACM  New York, NY, USA
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Downloads (6 Weeks): 10,   Downloads (12 Months): 63,   Citation Count: 58
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ABSTRACT

An analytic model is used to study the performance of dynamic locking. The analysis uses only the steady-state average values of the variables. The solution to the model is given by a cubic, which has exactly one valid root for the range of parametric values that is of interest. The model's predictions agree well with simulation results for transactions that require up to twenty locks. The model separates data contention from resource contention, thus facilitating an analysis of their separate effects and their interaction. It shows that systems with a particular form of nonuniform access, or with shared locks, are equivalent to systems with uniform access and only exclusive locks. Blocking due to conflicts is found to impose an upper bound on transaction throughput; this fact leads to a rule of thumb on how much data contention should be permitted in a system. Throughput can exceed this bound if a transaction is restarted whenever it encounters a conflict, provided restart costs and resource contention are low. It can also be exceeded by making transactions predeclare their locks. Raising the multiprogramming level to increase throughput also raises the number of restarts per completion. Transactions should minimize their lock requests, because data contention is proportional to the square of the number of requests. The choice of how much data to lock at a time depends on which part of a general granularity curve the system sees.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

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CITED BY  58

Collaborative Colleagues:
Y. C. Tay: colleagues
Nathan Goodman: colleagues
R. Suri: colleagues