The invention relates to a distributed cluster
resource scheduling method based on a user operation process. The method comprises the following steps: firstly, analyzing an execution sequence constraint relationship among sub-jobs included in the job, and determining a serial-parallel execution sequence of the sub-jobs; and according to the execution sequence of the sub-jobs, performing logic allocation of resources for the sub-jobs and predicting the
execution time of each sub-job under the
resource allocation, and further predicting the
execution time of the job by calculating a key path in the job process. Usually, the job submitted by the user has the constraint of the
completion time, so that the predicted job
completion time can be used as a basis whether the cluster can provide services for the user in time or not. Experiments prove that compared with a default
resource allocation algorithm of Spark, the
algorithm provided by the invention can shorten the job
execution time by 16.81%. According to the
algorithm provided by the invention, the
degree of parallelism of sub-job operation can be improved, the job execution time is shortened, and the improvement of the
service quality of mechanisms such as a cloud service platform, a supercomputing center and a
data center is facilitated.