Setting the Task Priority

Scenario

The resource contention scenarios of a cluster are as follows:

1. Submit two jobs (Job 1 and Job 2) with lower priorities.
2. Some tasks of running Job 1 and Job 2 are in the running state. However, some tasks are pending due to resource deficiency because the capacity of cluster or queue resources is limited.
3. Submit a job (Job 3) with a higher priority. In this case, after the running tasks of Job 1 and Job 2 are complete, their resources will be released and then allocated to the pending tasks of Job 3.
4. After Job 3 is complete, its resources will be released and then allocated to Job 1 and Job 2.

Users can use capacity scheduler of ResourceManager to set the task priority in Yarn because the task priority is implemented by the capacity scheduler of ResourceManager.

Procedure

Set the mapreduce.job.priority parameter and use CLI or API to set the task priority.

• Through the CLI

  When submitting tasks, add the -Dmapreduce.job.priority=<priority> parameter.

  <priority> can be set to any of the following values:

  • VERY_HIGH
  • HIGH
  • NORMAL
  • LOW
  • VERY_LOW
• Through the API

  You can also set the task priority through the API.

  Set Configuration.set("mapreduce.job.priority", <priority>) or Job.setPriority(JobPriority priority).