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Characteristics of production database workloads and the TPC benchmarks

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3 Author(s)
Hsu, W.W. ; IBM Research Division, Almaden Research Center, 650 Harry Road, San Jose, California 95120, USA ; Smith, A.J. ; Young, H.C.

There has been very little empirical analysis of any real production database workloads. Although the Transaction Processing Performance Council benchmarks C (TPC-C™) and D (TPC-D™) have become the standard benchmarks for on-line transaction processing and decision support systems, respectively, there has not been any major effort to systematically analyze their workload characteristics, especially in relation to those of real production database workloads. In this paper, we examine the characteristics of the production database workloads of ten of the world's largest corporations, and we also compare them to TPC-C and TPC-D. We find that the production workloads exhibit a wide range of behavior. In general, the two TPC benchmarks complement one another in reflecting the characteristics of the production workloads, but some aspects of real workloads are still not represented by either of the benchmarks. Specifically, our analysis suggests that the TPC benchmarks tend to exercise the following aspects of the system differently than the production workloads: concurrency control mechanism, workload-adaptive techniques, scheduling and resource allocation policies, and I/O optimizations for temporary and index files. We also re-examine Amdahl's rule of thumb for a typical data processing system and discover that both the TPC benchmarks and the production workloads generate on the order of 0.5 to 1.0 bit of logical I/O per instruction, surprisingly close to the much earlier figure.

Note: The Institute of Electrical and Electronics Engineers, Incorporated is distributing this Article with permission of the International Business Machines Corporation (IBM) who is the exclusive owner. The recipient of this Article may not assign, sublicense, lease, rent or otherwise transfer, reproduce, prepare derivative works, publicly display or perform, or distribute the Article.  

Published in:

IBM Systems Journal  (Volume:40 ,  Issue: 3 )