Abstract: Hadoop develops open-source software for reliable,scalable,distributed computing.MapReduce is a programming model and an associated implementation for processing large data sets.Because the built-in Hadoop scheduler cannot handle the different type and deadline based jobs,we proposed a scheduler algorithm based on type specific and deadline.We specified these jobs into CPU-bound and I/O-bound and gave priority to jobs according to the deadline.The results of experiments show that the proposed algorithm not only makes full use of the cluster’s CPU and I/O resource,but also meets the jobs’ deadline.If the deadline is almost the same at a period of time,the algorithm is the best.But if jobs’ deadlines from one queue are all shorter than another queue,the efficiency of the algorithm achieves the minimum.

Key words: Scheduler algorithm,Deadline,Job-type,MapReduce,Hadoop