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<p>Coupling multiple computing nodes for transaction processing has become increasingly attractive for reasons of capacity, cost, and availability. This paper presents a comparison of robustness (in terms of performance) of three different architectures for transaction processing. In the shared nothing (SN) architecture, neither disks nor memories are shared. In the shared disk (SD) architecture, all disks are accessible from all nodes, whereas in the shared intermediate memory (SIM) architecture, a shared intermediate level of memory is introduced. Coupling multiple nodes inevitably introduces certain interferences and overheads, which take on different forms and magnitudes under the different architectures. Affinity clustering, which attempts to partition the transactions into affinity clusters according to their database reference patterns, can be employed to reduce the coupling degradation under the different architectures, though in different ways. However, the workload may not be partitionable into N affinity clusters of equal size, where N is the number of nodes in the coupled system, so that the load can be evenly spread over all nodes. In addition to balancing the load, we need to maintain a large fraction of data references within the database affiliated with the affinity cluster. These become increasingly harder to achieve for large values of N. In this paper, we examine the impact of affinity on the performance of these three different coupling architectures.</p>
transaction processing; performance evaluation; database theory; distributed databases; software reliability; performance analysis; affinity clustering; transaction processing coupling architecture; multiple computing nodes; capacity; cost; availability; shared nothing architecture; disks; memories; shared disk architecture; shared intermediate memory; transaction partitioning; database reference patterns; affinity clusters; load balancing; data references; coupling architecture performance

P. Yu and A. Dan, "Performance Analysis of Affinity Clustering on Transaction Processing Coupling Architecture," in IEEE Transactions on Knowledge & Data Engineering, vol. 6, no. , pp. 764-786, 1994.
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