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From Conrad Crampton <>
Subject Spark or custom processor?
Date Thu, 02 Jun 2016 10:41:27 GMT
Any advice on ‘best’ architectural approach whereby some processing function has to be
applied to every flow file in a dataflow with some (possible) output based on flowfile content.
e.g. inspect log files for specific ip then send message to syslog

approach 1
Output port from NiFi -> Spark listens to that stream -> processes and outputs accordingly
Advantages – scale spark job on Yarn, decoupled (reusable) from NiFi
Disadvantages – adds complexity, decoupled from NiFi.

Approach 2
Custom processor -> PutSyslog
Advantages – reuse existing NiFi processors/ capability, obvious flow (design intent)
Disadvantages – scale??

Any comments/ advice/ experience of either approaches?


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