Real-time distributed job scheduler with job self-scheduling

Abstract

Methods and systems for improving the performance of a distributed job scheduler using job self-scheduling and job stealing are described. The distributed job scheduler may schedule jobs to be run among data storage nodes within a cluster. Each node in the cluster may make a localized decision regarding which jobs should be executed by the node by periodically polling candidate jobs from a table of candidate jobs stored using a distributed metadata store. Upon completion of a job, the job may self-schedule another instance of itself if the next instance of the job should be run before the next polling of candidate jobs by the node that ran the completed job. The node may attempt to steal one or more jobs from a second node within the cluster if a job queue length for a job queue associated with the node falls below a queue length threshold.