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Mastering Java for Data Science

You're reading from   Mastering Java for Data Science Analytics and more for production-ready applications

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Product type Paperback
Published in Apr 2017
Publisher Packt
ISBN-13 9781782174271
Length 364 pages
Edition 1st Edition
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Author (1):
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Alexey Grigorev Alexey Grigorev
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Alexey Grigorev
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Microservices

Java is a very common platform choice for running production code for many applications across many domains. When data scientists create a model for existing applications, Java is a natural choice, since it can be seamlessly integrated into the code. This case is straightforward, you create a separate package, implement your models there, and make sure other packages use it. Another possible option is packaging the code into a separate JAR file, and include it as a Maven dependency.

But there is a different architectural approach for combining multiple components of a large system--the microservices architecture. The main idea is that a system should be composed of small independent units with their own lifecycle--their development, testing, and deployment cycles are independent of all other components.

These microservices typically communicate via REST API, which is based on HTTP. It is based on four...

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