MapReduce is a popular framework for processing large datasets in parallel over a cluster. It has gained wide attention for its high scalability, reliability and low cost. However, its performance may be degraded by excessive network traffic when processing jobs, for such two problems as data locality in reduce task scheduling and partitioning skew. We propose a Minimum Transmission Cost Reduce task Scheduler (MTCRS) based on sampling evaluation to solve the two problems. The MTCRS takes the waiting time of each reduce task and the transmission cost set as indicators to decide appropriate launching locations for Reduce tasks. The transmission cost set is computed by a mathematical model, in which the parameters are the sizes and the locations of intermediate data partitions generated by Average Reservoir Sampling (ARS) algorithm. The experiments show that the MTCRS reduces network traffic by 8.4% compared with Fair scheduler.
목차
Abstract 1. Introduction 1.1. Data Locality in Reduce Tasks Scheduling 1.2. Partitioning Skew 2. Background and Related Work 2.1. The Process from Job Submission to Job Launching 2.2. Typical Network Topology of Hadoop Cluster 2.3. Research on Task Scheduling 3. The Design of the New Reduce Task Scheduler 3.1. ARS Sampling Algorithm 3.2. Transmission Cost Mathematical Model 3.3. MTCRS 4. Experiments and Evaluation 4.1. Environment and Datasets 4.2. ARS 4.3. MTCRS 5. Conclusion and Future Work Acknowledgements References
보안공학연구지원센터(IJDTA) [Science & Engineering Research Support Center, Republic of Korea(IJDTA)]
설립연도
2006
분야
공학>컴퓨터학
소개
1. 보안공학에 대한 각종 조사 및 연구
2. 보안공학에 대한 응용기술 연구 및 발표
3. 보안공학에 관한 각종 학술 발표회 및 전시회 개최
4. 보안공학 기술의 상호 협조 및 정보교환
5. 보안공학에 관한 표준화 사업 및 규격의 제정
6. 보안공학에 관한 산학연 협동의 증진
7. 국제적 학술 교류 및 기술 협력
8. 보안공학에 관한 논문지 발간
9. 기타 본 회 목적 달성에 필요한 사업
간행물
간행물명
International Journal of Database Theory and Application
간기
격월간
pISSN
2005-4270
수록기간
2008~2016
십진분류
KDC 505DDC 605
이 권호 내 다른 논문 / International Journal of Database Theory and Application Vol.8 No.1