# Research on Job Scheduling Algorithm in Hadoop

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4 Y. Xia et al. /Journal of Computational Information Systems 7:6 () average error rate of node E(%) E=-.6*Exp(((l-.387)^)/-.384)+.69*l Node load L(%) Fig. Node Load Effect on the Average Error Rate of Node If E j is the average fail rate of node j actually received in the improved algorithm experiment, then the Node Health Degree is defined as E j / f (l j ).Nodes can be classified according to Health Degree as table below: Table Classification of the Nodes According to Health Degree Node E j / f(l j ) Range Health node E j / f(l j ). Subhealthy node.<e j / f(l j ).5 Unhealthy node.5<e j / f(l j ) 3.4. Algorithm Description Between job pools this algorithm (FS-HD) uses Fair scheduling algorithm, a better strategy which has been proven. In job pool the job scheduling algorithm based on Health Degree of node is described as follows: ) When an idle task slot can be used, a pool is chosen according to the Fair scheduler; ) if the node on which the idle task is located is healthy, then go to 5; 3) if the node on which the idle task is located is sub healthy, characteristic variables of the node are separately multiplied by the reciprocal of Health Degree of node, then go to 5; 4) if the node on which the idle task is located is unhealthy, then go to 8,and set timer on node,its Health Degree is multiplied by.9 every x minutes until it reaches the state of sub healthy; 5) Computing Euclidean distances between characteristic variables of job task and characteristic variables of node, sorting them from small to large; 6) Choosing an appropriate job according to Delay Scheduler in the sorted set; 7) Assigning the task of a chosen job to a task slot to run; 8) Finish. In step 4, generally the timer interval of unhealthy node is set to 5, when the node Health Degree reaches sub health, the node can be schedule again. In step 5, the computational method of Euclidean distance is M ldle M usage D= ( Cldle Cusage) + ( Ildle Iusage) + ( ) (3) M In step 6, Delay Scheduler is used so that the algorithm achieves higher locality. ldle

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