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Chapter 16. Distributed Execution
Red Hat JBoss Data Grid provides distributed execution through a standard JDK
ExecutorService interface. Tasks submitted for execution are executed on an entire cluster of JBoss Data Grid nodes, rather than being executed in a local JVM.
JBoss Data Grid's distributed task executors can use data from JBoss Data Grid cache nodes as input for execution tasks. As a result, there is no need to configure the cache store for intermediate or final results. As input data in JBoss Data Grid is already load balanced, tasks are also automatically balanced, therefore there is no need to explicitly assign tasks to specific nodes.
In JBoss Data Grid's distributed execution framework:
- Each
DistributedExecutorServiceis bound to a single cache. Tasks submitted have access to key/value pairs from that particular cache if the task submitted is an instance ofDistributedCallable. - Every
Callable,Runnable, and/orDistributedCallablesubmitted must be eitherSerializableorExternalizable, in order to prevent task migration to other nodes each time one of these tasks is performed. The value returned from aCallablemust also beSerializableorExternalizable.
16.1. Distributed Executor Service Copia collegamentoCollegamento copiato negli appunti!
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DistributedExecutorService controls the execution of DistributedCallable, and other Callable and Runnable, classes on the cluster. These instances are tied to a specific cache that is passed in upon instantiation:
DistributedExecutorService des = new DefaultExecutorService(cache);
DistributedExecutorService des = new DefaultExecutorService(cache);
It is only possible to execute a
DistributedTask against a subset of keys if DistributedCallable is extended, as discussed in Section 16.2, “DistributedCallable API”. If a task is submitted in this manner to a single node, then JBoss Data Grid will locate the nodes containing the indicated keys, migrate the DistributedCallable to this node, and return a NotifyingFuture. Alternatively, if a task is submitted to all available nodes in this manner then only the nodes containing the indicated keys will receive the task.
Once a
DistributedTask has been created it may be submitted to the cluster using any of the below methods:
- The task can be submitted to all available nodes and key/value pairs on the cluster using the
submitEverywheremethod:des.submitEverywhere(task)
des.submitEverywhere(task)Copy to Clipboard Copied! Toggle word wrap Toggle overflow - The
submitEverywheremethod can also take a set of keys as an argument. Passing in keys in this manner will submit the task only to available nodes that contain the indicated keys:des.submitEverywhere(task, $KEY)
des.submitEverywhere(task, $KEY)Copy to Clipboard Copied! Toggle word wrap Toggle overflow - If a key is specified, then the task will be executed on a single node that contains at least one of the specified keys. Any keys not present locally will be retrieved from the cluster. This version of the
submitmethod accepts one or more keys to be operated on, as seen in the following examples:des.submit(task, $KEY) des.submit(task, $KEY1, $KEY2, $KEY3)
des.submit(task, $KEY) des.submit(task, $KEY1, $KEY2, $KEY3)Copy to Clipboard Copied! Toggle word wrap Toggle overflow - A specific node can be instructed to execute the task by passing the node's
Addressto thesubmitmethod. The below will only be executed on the cluster'sCoordinator:des.submit(cache.getCacheManager().getCoordinator(), task)
des.submit(cache.getCacheManager().getCoordinator(), task)Copy to Clipboard Copied! Toggle word wrap Toggle overflow Note
By default tasks are automatically balanced, and there is typically no need to indicate a specific node to execute against.