Scheduling Hadoop Jobs to Meet Deadlines

User constraints such as deadlines are important requirements that are not considered by existing cloud-based data processing environments such as Hadoop. In the current implementation, jobs are scheduled in FIFO order by default with options for other priority based schedulers. In this paper, we extend real time cluster scheduling approach to account for the two-phase computation style of MapReduce. We develop criteria for scheduling jobs based on user specified deadline constraints and discuss our implementation and preliminary evaluation of a Deadline Constraint Scheduler for Hadoop which ensures that only jobs whose deadlines can be met are scheduled for execution.

• Type: Journal
• Year: 2010
• Where: CLOUDCOM
• Authors: Kamal Kc, Kemafor Anyanwu
• Keywords: CLOUDCOM 2010, Data Processing Environments, Deadline Constraint Scheduler, Distributed And Parallel Computing, Priority Based Schedulers