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https://issues.apache.org/jira/browse/YARN-2362?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Ram Venkatesh updated YARN-2362:
Description:
Cluster configuration:
Total memory: 8GB
yarn.scheduler.minimum-allocation-mb 256
yarn.scheduler.capacity.maximum-am-resource-percent 1 (100%, test only config)
App 1 makes a request for 4.6 GB, succeeds, app transitions to RUNNING state.
It subsequently makes a request for 4.6 GB, which cannot be granted and it
waits.
App 2 makes a request for 1 GB - never receives it, so the app stays in the
ACCEPTED state for ever.
I think this can happen in leaf queues that are near capacity.
The fix is likely in LeafQueue.java assignContainers near line 861, where it
returns if the assignment would exceed queue capacity, instead of checking if
requests for other active applications can be met.
{code:title=LeafQueue.java|borderStyle=solid}
// Check queue max-capacity limit
if (!assignToQueue(clusterResource, required)) {
-return NULL_ASSIGNMENT;
+break;
}
{code}
With this change, the scenario above allows App 2 to start and finish while App
1 continues to wait.
I have a patch available, but wondering if the current behavior is by design.
was:
Cluster configuration:
Total memory: 8GB
yarn.scheduler.minimum-allocation-mb 256
yarn.scheduler.capacity.maximum-am-resource-percent 1 (100%, test only config)
App 1 makes a request for 4.6 GB, succeeds, app transitions to RUNNING state.
It subsequently makes a request for 4.6 GB, which cannot be granted and it
waits.
App 2 makes a request for 1 GB - never receives it, so the app stays in the
ACCEPTED state for ever.
I think this can happen in leaf queues that are near capacity.
The fix is likely in LeafQueue.java assignContainers near line 861, where it
returns if the assignment would exceed queue capacity, instead of checking if
requests for other active applications can be met.
// Check queue max-capacity limit
if (!assignToQueue(clusterResource, required)) {
-return NULL_ASSIGNMENT;
+break;
}
With this change, the scenario above allows App 2 to start and finish while App
1 continues to wait.
I have a patch available, but wondering if the current behavior is by design.
Capacity Scheduler apps with requests that exceed capacity can starve pending
apps
--
Key: YARN-2362
URL: https://issues.apache.org/jira/browse/YARN-2362
Project: Hadoop YARN
Issue Type: Bug
Components: capacityscheduler
Affects Versions: 2.4.1
Reporter: Ram Venkatesh
Cluster configuration:
Total memory: 8GB
yarn.scheduler.minimum-allocation-mb 256
yarn.scheduler.capacity.maximum-am-resource-percent 1 (100%, test only config)
App 1 makes a request for 4.6 GB, succeeds, app transitions to RUNNING state.
It subsequently makes a request for 4.6 GB, which cannot be granted and it
waits.
App 2 makes a request for 1 GB - never receives it, so the app stays in the
ACCEPTED state for ever.
I think this can happen in leaf queues that are near capacity.
The fix is likely in LeafQueue.java assignContainers near line 861, where it
returns if the assignment would exceed queue capacity, instead of checking if
requests for other active applications can be met.
{code:title=LeafQueue.java|borderStyle=solid}
// Check queue max-capacity limit
if (!assignToQueue(clusterResource, required)) {
-return NULL_ASSIGNMENT;
+break;
}
{code}
With this change, the scenario above allows App 2 to start and finish while
App 1 continues to wait.
I have a patch available, but wondering if the current behavior is by design.
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