Opportunities For Reducing Energy Consumption in DBMS

1. Opportunities For Reducing Energy Consumption in DBMS Meikel Poess Oracle Corporation

2. Analytical Power Consumption Model • Based on nameplate power consumption • Nameplate power is conservative estimate • Model adjusts nameplate to yield realistic numbers • Estimates peak power consumption during steady state workload • Developed for OLTP and Decision Support workloads • Validated with measured power numbers of TPC-C, TPC-E and TPC-H benchmark results • Power estimates are very close to measured numbers • Performed long term study on 64 x86 based systems Meikel Poess

3. Energy Consumption Of TPC-C Systems • Slope of 0.86 • 6x increase over 7 years • 40% lower than performance increase in the same period • Slope of 0.4 • 2.6x increase over 7 years • Power consumption is increasing Meikel Poess

4. Power Performance Analysis • x-axis: performance [Q/h] • y-axis: Total Power [KWh] • 6 different configurations • 6 disks • 14 disks • 32 disks • 100 disks • SSDs • In-Memory • Shows energy efficiency of systems • Power-Performance Quadrant Meikel Poess

5. Impact of Performance Techniques To Power-Performance • Shows impact of compression to Power-Performance • 5 different configurations • 6 disks • 14 disks • 32 disks • 100 disks • SSDs • Each configuration defines a vector • Vector indicates • how much performance was gained • how much power was saved • Other techniques • CPU speed adjustment • Power-Performance Quadrant Meikel Poess

6. Research Questions • Data placement • What data to store on fast vs. slow disks or on SSDs or when to keep it in Memory? • Can data be placed intelligently depending on a dynamic workload • Power Management • If we can improve system performance at a higher rate than we need to increase power consumption, what do we do with the idle resources? • Service level agreements • How can we incorporate power aspects into service level agreements? Meikel Poess