class GraphRuntime extends AnyRef
Execute a pipeline.
The graph runtime executes a pipeline.
If the specified graph is open, it will be closed. If it is not valid, an exception is thrown.
Constructing the runtime builds the network of Akka actors. If for some reason you decide not
to run the pipeline, you must call stop
to tear it down.
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new
GraphRuntime(graph: Graph, runtime: RuntimeConfiguration)
A graph runtime.
A graph runtime.
- graph
The graph to execute.
- runtime
Runtime context information for the execution.
Value Members
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final
def
!=(arg0: Any): Boolean
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final
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def
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def
equals(arg0: Any): Boolean
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def
exception: Option[Throwable]
Returns an optional exception raised during execution.
Returns an optional exception raised during execution.
If the pipeline execution halts because an uncaught exception is thrown, the exception is available from here after the pipeline finishes.
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def
finalize(): Unit
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def
finish(cause: Exception): Unit
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- protected[com.jafpl.runtime]
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def
finish(): Unit
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def
finished: Boolean
Returns true if the pipeline execution has finished.
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final
def
getClass(): Class[_]
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- val graph: Graph
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def
hashCode(): Int
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def
inputs: Map[String, DataProvider]
A map of the inputs that the pipeline expects.
A map of the inputs that the pipeline expects.
This mapping from names (strings) to com.jafpl.steps.DataConsumers is the set of inputs that the pipeline expects from the outside world. If you do not provide an input, an empty sequence of items will be provided.
- returns
A map of the expected inputs.
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final
def
isInstanceOf[T0]: Boolean
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def
lastMessageAge: Long
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val
logger: Logger
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final
def
ne(arg0: AnyRef): Boolean
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def
noteMessageTime(): Unit
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def
notify(): Unit
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final
def
notifyAll(): Unit
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def
outputs: Map[String, DataConsumerProxy]
A map of the outputs that the pipeline produces.
A map of the outputs that the pipeline produces.
This mapping from names (strings) to com.jafpl.steps.DataConsumerProxys is the set of outputs that the pipeline. If you do not call the
setProvider
method, the output will be discarded.- returns
A map of the expected inputs.
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def
run(): Unit
Runs the pipeline.
Runs the pipeline.
This method will block until pipeline execution finishes.
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def
runInBackground(): Unit
Runs the pipeline.
Runs the pipeline.
This method starts execution of the pipeline and then returns immediately. The pipeline will continue to run in other threads.
To determine if execution has completed, check the
finished
value. - val runtime: RuntimeConfiguration
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def
started: Boolean
Returns true if the pipeline execution has started.
- def stop(): Unit
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final
def
synchronized[T0](arg0: ⇒ T0): T0
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def
toString(): String
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def
wait(): Unit
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def
wait(arg0: Long, arg1: Int): Unit
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final
def
wait(arg0: Long): Unit
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def
waitForPipeline(): Unit
Wait for pipeline execution to complete.
Wait for pipeline execution to complete.
If you start a pipeline in the background and then wish to block until execution completes, call this method.
Just Another Fine Pipeline Language
This is a pipeline framework. It’s built on top of Akka actors to support arbitrary data flow pipelines. It is wholly agnostic to the kinds of data that flow through the pipelines and the implementations of the steps that process them.
See http://jafpl.com/ for more general information.