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Document the state by adding a label to the FLIP page with one of "discussion", "accepted", "released", "rejected".
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Please keep the discussion on the mailing list rather than commenting on the wiki (wiki discussions get unwieldy fast).
Motivation
Currently, ResourceManager will only start a a new worker when there's resource requirements from job. But the Flink cluster only requests Task Managers (TMs) when there is a resource requirement, and idle TMs are released after a certain period of time. However, in certain scenarios, it is necessary to maintain a certain amount of slots as soon as ResourceManager is started. And these slots should not release even if all slots are free. Here are some scenarios which can benefit from this proposal:
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we need to improve the efficiency of job execution by maintaining a certain number of available resources in the system. For example:
For session clusters running short lived-jobs like OLAP, we should treat session clusters as a long-running service. Having running workers all the time can greatly improve the service stability and reduce the job's cold-start latency;
For application mode, batch job might be scheduled stage by stage. If the next region requires more resources, it might take more time to pull up required resources. If users actually know how many resources are needed when
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running a single job, initialize all workers when cluster starts can speed up
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the resource allocation process;
Public Interfaces
Public Interfaces
A public interface is any change to the following:
Option name | Default Value |
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slotmanager.number-of-slots.min | 0 |
slotmanager.min-total-resource.cpu | no default value, it can be derived from slotmanager.number-of-slots.min |
slotmanager.min-total-resource.memory | no default value, it can be derived from slotmanager.number-of-slots.min |
Notice: Like the maximum resource options, the minimum resource options will also be invalidated in standalone clusters.
Proposed Changes
Minimum required resource check in DefaultResourceAllocationStrategy
The minimum resource allocation limitation will be implemented in the DefaultResourceAllocationStrategy of FineGrainedSlotManager.
Each time when SlotManager need needs to reconcile the cluster resources or fulfill job resource requirements, the DefaultResourceAllocationStrategy will check if the minimum resource requirement has been fulfilled. If it is not, DefaultResourceAllocationStrategy will add PendingTaskManagers to the ResourceAllocationResult/ResourceReconcileResult request new PendingTaskManagers and FineGrainedSlotManager will allocate new worker resources accordingly.
Notice: The minimum resource limitation will be fulfilled in the best effort manner. The unfulfilled request will be retried in the next resource check but will not block job scheduling.
Resource stability check in SlotManagerConfiguration
After minimum required resource options is are introduced, user users can configure both minimum and maximum required resource resources in SlotManager, which might lead to worker resource oscillation. Here is an example:
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taskmanager.numberOfTaskSlots: 5 slotmanager.number-of-slots.min: 11 slotmanager.number-of-slots.max: 14 |
In this case, the min minimum required worker number derived from DefaultResourceAllocationStrategy is 3 but this will exceed the max total resource limit, which is 14 slots.
To Avoid avoid this oscillation, we need to check the worker number derived from minimum and maximum resource configuration is consistent before starting the SlotManagerSlotManager.
Notice: The resource stability check will be disabled when the minimum resource option is 0 which is set as default.
Compatibility, Deprecation, and Migration Plan
- What impact (if any) will there be on existing users? No
Test Plan
UT & Manually verify that the min resource
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limitation is working as expected.
Rejected Alternatives
If there are alternative ways of accomplishing the same thing, what were they? The purpose of this section is to motivate why the design is the way it is and not some other way.