Resource scheduler algorithm based on statistical optimization under Hadoop
Hadoop下基于统计最优的资源调度算法

There are node stability problems in a heterogeneous cloud clusters. The heterogeneous resources' differences in computing ability will lead to prominent sync issues of job' task, and a unsteady node will make the task which is running in the node been backup or been recount. The two problems above will seriously affect the execution of the cluster's jobs progress. According to the situation, now using the Hadoop workbench with statistical method, this paper put forward a kind of resource scheduling algorithm which marked and dropped the less computing resources node and instability node rightly , letting cluster scheduling resources better stability node as much as possible. The experimental results show that, the algorithm can reduce the jobs cycle time in a certain degree, and improve the efficiency of the cluster and throughput.