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Extending Sparkflows with Custom Processors

Sparkflows now has close to 150 Processors for Machine Learning, NLP, ETL, Entity Resolution, OCR, Handling Unstructured Data etc.

But, the amazing thing about Sparkflows is that any user can add their own Custom Processors. Enterprises are finding that by doing so, they start with the rich set of existing ~150 Processors, and can focus on add those core Processors only which apply to their Business.

Writing New Processors

This github repo guides you through writing New Processors:

The master branch is for Spark 1.6.X and the spark-2.x branch is for Spark 2.X.

It has a number of example Processors. You can take any of them and build your own.

Get started with your own Processors. Why not contribute your Processors to the community by making them public.

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1 Comment

Innovation of the data is the configuration of data by presenting the spark flow and the flow of other beautiful material. The blog is about the custom processing at the eve of by reviewing the other component factor detail wise.

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