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Buffer Analysis for a Data Sharing Environment with Skewed Data Access
April 1994 (vol. 6 no. 2)
pp. 331-337

Examines the effect of skewed database access on the transaction response time in a multisystem data sharing environment, where each computing node has access to shared data on disks, and has a local buffer of recently accessed granules. Skewness in data access can increase data contention since most accesses go to few data items. For the same reason, it can also increase the buffer hit probability. We quantify the resultant effect on the transaction response time, which depends not only on the various system parameters but also on the concurrency control (CC) protocol. Furthermore, the CC protocol can give rise to rerun transactions that have different buffer hit probabilities. In a multisystem environment, when a data block gets updated by a system, any copies of that block in other systems' local buffers are invalidated. Combining these effects, we find that higher skew does not necessarily lead to worse performance, and that with skewed access, optimistic CC is more robust than pessimistic CC. Examining the buffer hit probability as a function of the buffer size, we find that the effectiveness of additional buffer allocation can be broken down into multiple regions that depend on the access frequency distribution.

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Index Terms:
transaction processing; buffer storage; concurrency control; distributed databases; protocols; buffer analysis; disk storage; skewed data access; skewed database access; transaction response time; multisystem data sharing environment; local buffer; recently accessed granules; data contention; buffer hit probability; concurrency control protocol; rerun transactions; data block updating; performance; optimistic concurrency control; pessimistic concurrency control; buffer size; robustness; additional buffer allocation; access frequency distribution; transaction processing; analytic model
A. Dan, D.M. Dias, P.S. Yu, "Buffer Analysis for a Data Sharing Environment with Skewed Data Access," IEEE Transactions on Knowledge and Data Engineering, vol. 6, no. 2, pp. 331-337, April 1994, doi:10.1109/69.277776
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