TY - JOUR
T1 - Performance analysis on sorting algorithms in cloud computing environment
AU - Ding, Yucheng
AU - Zhuge, Qingfeng
AU - Sha, Xingmian
PY - 2014/4
Y1 - 2014/4
N2 - With the rapid increase of data amount in cloud computing environment, it is an urgent need to study how to analysis and process those data fast and effectively. How to sort large scale data efficiently in cloud computing environment is a significant problem. Whether the widely used sorting algorithms can achieve high-performance and how many cloud computing resources they consume are concerned problems. This paper studies and implements several efficient sorting algorithms, including Radix sort, Quicksort and Sample sort, based on Hadoop, analyzes and compares the efficiency, consumption of CPU resources, memory consumption and communication between machines. Through a large number of experiments, it's found that compared to Radix sort and Quicksort, Sample sort has the advantages of higher sorting speed, higher load balancing and lower CPU consumption. This result provides a valid basis and foundation for designing more efficient, energy-saving algorithms in cloud computing environment.
AB - With the rapid increase of data amount in cloud computing environment, it is an urgent need to study how to analysis and process those data fast and effectively. How to sort large scale data efficiently in cloud computing environment is a significant problem. Whether the widely used sorting algorithms can achieve high-performance and how many cloud computing resources they consume are concerned problems. This paper studies and implements several efficient sorting algorithms, including Radix sort, Quicksort and Sample sort, based on Hadoop, analyzes and compares the efficiency, consumption of CPU resources, memory consumption and communication between machines. Through a large number of experiments, it's found that compared to Radix sort and Quicksort, Sample sort has the advantages of higher sorting speed, higher load balancing and lower CPU consumption. This result provides a valid basis and foundation for designing more efficient, energy-saving algorithms in cloud computing environment.
KW - Cloud computing
KW - Hadoop
KW - MapReduce
KW - Sorting algorithm
UR - https://www.scopus.com/pages/publications/84901599390
U2 - 10.11835/j.issn.1000-582X.2014.04.009
DO - 10.11835/j.issn.1000-582X.2014.04.009
M3 - 文章
AN - SCOPUS:84901599390
SN - 1000-582X
VL - 37
SP - 58
EP - 64
JO - Chongqing Daxue Xuebao/Journal of Chongqing University
JF - Chongqing Daxue Xuebao/Journal of Chongqing University
IS - 4
ER -