[FLINK-3543] Introduce ResourceManager component

• Type: New Feature
• Status: Closed
• Priority: Major
• Resolution: Implemented
• Affects Version/s: 1.1.0
• Fix Version/s: 1.1.0
• Component/s: Runtime / Coordination
• Assignee: Maximilian Michels
• Reporter: Maximilian Michels
• Created: 29/Feb/16 16:49
• Updated: 02/Oct/19 17:43
• Resolved: 19/May/16 10:25

Description

So far the JobManager has been the central instance which is responsible for resource management and allocation.

While thinking about how to integrate Mesos support in Flink, people from the Flink community realized that it would be nice to delegate resource allocation to a dedicated process. This process may run independently of the JobManager which is a requirement for proper integration of cluster allocation frameworks like Mesos.

This has led to the idea of creating a new component called the ResourceManager. Its task is to allocate and maintain resources requested by the JobManager. The ResourceManager has a very abstract notion of resources.

Initially, we thought we could make the ResourceManager deal with resource allocation and the registration/supervision of the TaskManagers. However, this approach proved to add unnecessary complexity to the runtime. Registration state of TaskManagers had to be kept in sync at both the JobManager and the ResourceManager.

That's why StephanEwen and me changed the ResourceManager's role to simply deal with the resource acquisition. The TaskManagers still register with the JobManager which informs the ResourceManager about the successful registration of a TaskManager. The ResourceManager may inform the JobManager of failed TaskManagers. Due to the insight which the ResourceManager has in the resource health, it may detect failed TaskManagers much earlier than the heartbeat-based monitoring of the JobManager.

At this stage, the ResourceManager is an optional component. That means the JobManager doesn't depend on the ResourceManager as long as it has enough resources to perform the computation. All bookkeeping is performed by the JobManager. When the ResourceManager connects to the JobManager, it receives the current resources, i.e. task manager instances, and allocates more containers if necessary. The JobManager adjusts the number of containers through the SetWorkerPoolSize method.

In standalone mode, the ResourceManager may be deactivated or simply use the StandaloneResourceManager which does practically nothing because we don't need to allocate resources in standalone mode.

In YARN mode, the ResourceManager takes care of communicating with the Yarn resource manager. When containers fail, it informs the JobManager and tries to allocate new containers. The ResourceManager runs as an actor within the same actor system as the JobManager. It could, however, also run independently. The independent mode would be the default behavior for Mesos where the framework master is expected to just deal with resource allocation.

The attached figures depict the message flow between ResourceManager, JobManager, and TaskManager.

Issue Links

• is related to: FLINK-1984 Integrate Flink with Apache Mesos
• relates to: FLINK-3667 Generalize client<->cluster communication

Sub-Tasks

• ResourceManager runtime components: Closed
• ResourceManager: YARN integration: Closed
• Create documentation on the new ResourceManager component: Resolved