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Analyzing Database Service Performance: Baseline Metrics and Future Projections

This case study explores the performance metrics of a database service utilizing a CPU and dual disks, monitored by DBMS and OS performance tools. With a baseline throughput of 1.33 TPS derived from 200 transactions over 150 seconds, we analyze CPU and disk usage (U_cpu, U_d1, U_d2). The study delves into how upgrading the disk subsystem would enhance performance. It also emphasizes the importance of understanding predicted performance changes in relation to workload intensity fluctuations over the next ten months, as illustrated in the provided data.

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Analyzing Database Service Performance: Baseline Metrics and Future Projections

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Presentation Transcript

  1. Case Study I: A Database Service Chapter 5

  2. Database Service Example • A CPU • Two disks • Two measurement tools: • A DBMS performance Monitor • An OS performance Monitor

  3. DBMS Performance Monitorlog file

  4. Co = 200 Txs • T = 150 sec • Xo = 200/150 = 1.33 tps

  5. Overall System throughput is 200/150=1.33tps • U_cpu, U_d1, and U_d2 are monitored by OS Performance Monitor, • What are? • U_cpu, c1 • U_cpu, c2 • U_cpu, c3 • ……

  6. This baseline model can be used to evaluate relevant "what-if“ scenarios. • It has already been noted that performance would improve by upgrading the disk subsystem. • Also, as the predicted workload intensity changes over time, an understanding of the predicted resulting performance is also important. • For example, suppose that the workload intensity is predicted to change over the next ten months as indicated in Table 5.7. (Note • that January's workload (i.e., X = 1.33 tps) is the baseline workload intensity assumed up to this point.)

  7. (0.865-0.56)/0.856 = 35%

  8. Exercise

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