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Ephemeral means that we do not know the state of Spark before, during, or after the invocation, we just care that the job was submitted, executed and results came back, no state of any type is kept. Data, or reference to data, is passed in the invocation, and the results captured and stored in the flowfile.

The best use case for this processor is when you want to launch ephemeral jobs for processing in Spark with a predictable start and finish cycles, rather than long running jobs. Since the processor will launch-and-wait for spark to finish, it means a thread will be allocated to wait until spark returns, no interaction happens while the Spark job is running.

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Github Repo URL
Github account name diegobaez
Repo name NiFi-SnapSpark
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Revision #:
1 of 1
Last update:
‎10-31-2016 01:13 PM
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