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Extracting JavaDoc documentation from source files using JavaParser

A lot of people are using JavaParser for the most different goals. One of these is extracting documentation. In this short post we will see how you can print all the JavaDoc comments associated to classes or interfaces. Code is available on GitHub: https://github.com/ftomassetti/javadoc-extractor Getting all the Javadoc comments for classes We are reusing DirExplorer, a supporting class presented in the introduction ...

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Processing Image Documents on MapR at Scale

There has been a lot of research in document image processing over the past 20 years, but not much research has been done in terms of parallel processing. Some of the solutions proposed for parallel processing have been to create threads of execution for each image, or to use GNU Parallel. In this blog post, you will learn how to ...

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What is software architecture?

What is software architecture? In the previous article “What is architecture?” we stated that architecture is about: Structural elements Connective elements Let us talk about these with regard to a software system.  In our next article we’ll talk about good and bad architecture. Structural elements Structural elements in software are layers that support other layers in the system: the language ...

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Spring boot and Cache Abstraction

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Caching is a major ingredient of most applications, and as long as we try to avoid disk access it will stay strong. Spring has great support for caching with a wide range of configurations. You can start as simple as you want and progress to something much more customizable. This would be an example with the simplest form of caching ...

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DMN runtime example with Drools

As announced last year, Drools 7.0 will have full runtime support for DMN models at compliance level 3. The runtime implementation is, at the time of this blog post, feature complete and the team now is working on nice to have improvements, bug fixes and user friendliness. Unfortunately, we will not have full authoring capabilities in time for the 7.0 release, but ...

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3 Steps to Cloud Operations Happiness with CloudForms

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There areThis week it was announced that the newest addition to the Cloud Suite management layer, CloudForms 4.2, was available for all to enjoy. many cool and new things to get excited about with over 1800 improvements added to the product. CloudForms is the Cloud management platform for the Cloud Suite product, providing you with the ability to deploy it federated across ...

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Dev and Ops Continue to Revisit Their Roles in the Enterprise in 2017

Want to know Learn More? Download the Whitepaper from AppDynamics: 10 Things Your CIO Should Know About DevOps If there are two departments that have undergone huge changes in recent years, it’s development and operations, and 2017 looks likely to see this trend continue. What’s on the horizon for the often dev-centric DevOps teams and operations in particular? A test ...

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[MEGA DEAL] Big Data Mastery with Hadoop Bundle (89% off)

Tame Massive Data Sets with 44 Hours of Extensive Hadoop Training Hey fellow geeks, This week, on our JCG Deals store, we have an extreme offer. We are offering the Big Data Mastery with Hadoop Bundle for only $49 instead of the original price of $453, yeap that is a massive 89% off. Taming Big Data with MapReduce & Hadoop ...

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Microservice using AWS Serverless Application Model and Couchbase

Amazon Web Services introduced Serverless Application Model, or SAM, a couple of months ago. It defines simplified syntax for expressing serverless resources. SAM extends AWS CloudFormation to add support for API Gateway, AWS Lambda and Amazon DynamoDB. This blog will show how to create a simple microservice using SAM. Of course, we’ll use Couchbase instead of DynamoDB! This blog will also use the ...

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Monitoring Real-Time Uber Data Using Spark Machine Learning, Streaming, and the Kafka API (Part 2)

This post is the second part in a series where we will build a real-time example for analysis and monitoring of Uber car GPS trip data. If you have not already read the first part of this series, you should read that first. The first post discussed creating a machine learning model using Apache Spark’s K-means algorithm to cluster Uber data based ...

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