Earticle

초록

영어

As the access speed gap between DRAM and storage devices such as hard disk drives is ever widening, the I/O module dominantly becomes the system bottleneck. Meanwhile, the map-reduce parallel programming model has been actively studied for the last few years. In this paper, we will show empirically show that flash memory based SSD(Solid State Drive) is very beneficial when used as local storage devices in IO-intensive map-reduce applications (e.g. sorting) using Hadoop open source platform. Specifically, we present that external sorting algorithm in Hadoop with SSD can outperform the algorithm run with hard disk by more than 3. In addition, we also demonstrate that the power consumption can be drastically reduced when SSDs are used.

목차

Abstract
 1. Introduction
 2. Hadoop Structure
 3. SSD (Solid State Disk)
 4. Performance Test
  4.1. Sort Benchmark
  4.2. Join Benchmark
  4.3. Optimizing Hadoop
  4.4. Other Benchmarks
  4.5. Electricity Consumption
 5. Conclusion
 Acknowledgements
 References

키워드

저자

• Seok-Hoon Kang [ Dept of Computer Engineering, Sungkyunkwan University, Korea ]
• Dong-Hyun Koo [ Dept of Computer Engineering, Sungkyunkwan University, Korea ]
• Woon-Hak Kang [ Dept of Computer Engineering, Sungkyunkwan University, Korea ]
• Sang-Won Lee [ Dept of Computer Engineering, Sungkyunkwan University, Korea ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Control and Automation

• 간기

  월간

• pISSN

  2005-4297

• 수록기간

  2008~2016

• 십진분류

  KDC 505 DDC 605