The invention relates to a multi-tenant resource optimization scheduling method facing different types of loads. The multi-tenant resource optimization scheduling method comprises the following steps: 1, submitting jobs by
system tenants and adding the jobs into a
job queue; 2, collecting job load information and sending the job load information to a resource manager; 3, judging different load types of the jobs according to the job load information by the resource manager, and sending type information to a
job scheduler; 4, carrying out job scheduling according to the different load types by the
job scheduler; if the job is a calculation intensive type job, scheduling at the node; if the job is an I / O intensive type job, delaying and waiting; and 5, collecting job scheduling decision-making information to a scheduling reconstruction decision-making device, reconstructing a target calculation node, and carrying out the job scheduling according to a final decision-making result. According to the method provided by the invention, a multi-tenant shared cluster is realized, so that the cost of establishing an independent cluster is reduced, and meanwhile, a plurality of tenants can share more
big data set resources. The better data locality is realized facing optimization of the different types of loads, and the balance between the equity and efficiency in a job scheduling process can be realized very well; and calculation performances of the whole cluster, such as
throughput rate and job responding time, are improved.