Manage cluster capacity with queues
You can manage your cluster capacity using queues to balance resource requirements of multiple applications from various users.
You can use the Capacity Scheduler to share cluster resources using FIFO (first-in, first-out) queues. YARN allows you to configure queues to own a fraction of the capacity of each cluster, and this specified queue capacity is fulfilled dynamically from the available nodes.
Users can submit applications to different queues at multiple levels in the queue hierarchy if the capacity is available on the nodes in the cluster. Because total cluster capacity can vary, capacity configuration values are expressed using percentages.
You can specify the
capacity property to allocate a
floating-point percentage values of cluster capacity to a queue. The following
properties divide the cluster resources between the Engineering, Support, and Marketing
organizations in a 6:1:3 ratio (60%, 10%, and 30%).
To specify the capacity property based on this example, add the following values for the root queue:
- In Cloudera Manager, select the YARN service.
- Click the Configuration tab.
- Search for scheduler.
In Capacity Scheduler Configuration Advanced Configuration Snippet
(Safety Valve)add the following:
Name: yarn.scheduler.capacity.root.engineering.capacity Value: 60
Name: yarn.scheduler.capacity.root.support.capacity Value: 10
Name: yarn.scheduler.capacity.root.marketing.capacity Value: 30
If you want the Engineering group to split its capacity between the Development and QA sub-teams in a 1:4 ratio. You can set the following property values:
Name: yarn.scheduler.capacity.root.engineering.development.capacity Value: 20
Name: yarn.scheduler.capacity.root.engineering.qa.capacity Value: 80
If you want the Engineering, Support, and Marketing organizations to use a specified absolute value for each resource type, you can set the following property values where the Engineering, Support, and Marketing queues are each allocated 10 GB of memory and 12 vcores:
Name: yarn.scheduler.capacity.root.engineering.capacity Value: [memory=10240,vcores=12]
Name: yarn.scheduler.capacity.root.support.capacity Value: [memory=10240,vcores=12]
Name: yarn.scheduler.capacity.root.marketing.capacity Value: [memory=10240,vcores=12]
- If you want to enable resource elasticity, specify the maximum capacity as a floating-point percentage value of resources allocated for a
queue. You have to set the maximum capacity to be higher than or equal to the
absolute capacity for each queue. Setting this value to -1 sets maximum capacity to
100%. In the following example, the maximum capacity of the Engineering queue is set
Name: yarn.scheduler.capacity.root.engineering.maximum-capacity Value: 70