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Using DJL.AI For Deep Learning Based Sentiment Analysis in NiFi DataFlow

Using DJL.AI For Deep Learning Based Sentiment Analysis in NiFi DataFlow 


Introduction:

I will be talking about this processor at Apache Con @ Home 2020 in my "Apache Deep Learning 301" talk with Dr. Ian Brooks.

Sometimes you want your Deep Learning Easy and in Java, so let's do that with DJL in a custom Apache NiFi processor running in CDP Data Hubs.

Grab the Source:

https://github.com/tspannhw/nifi-djlsentimentanalysis-processor

Grab the Recent Release NAR to install to your NiFi lib directories:

https://github.com/tspannhw/nifi-djlsentimentanalysis-processor/releases/tag/1.2

Example Run

probnegative
0.99
No value set
probnegativeperc
99.44
No value set
probpositive
0.01
No value set
probpositiveperc
0.56
No value set
rawclassification
[class: "Negative", probability: 0.99440, class: "Positive", probability: 0.00559]

Demo Data Source

https://newsapi.org/v2/everything?q=cloudera&apiKey=REGISTERFORAKEY



Reference:


Deep Learning Note:   

The pretrained model is DistilBERT model trained by HuggingFace using PyTorch.


Tip


Make sure you have 1-2 GB of RAM extra for your NiFi instance for running each DJL processor.   If you have a lot of text, run more nodes and/or RAM.   Make sure you have at least 8 cores per Deep Learning process.   I prefer JDK 11 for this.


See Also:   https://www.datainmotion.dev/2019/12/easy-deep-learning-in-apache-nifi-with.html



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