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Mastering Concurrency Programming with Java 8

Mastering Concurrency Programming with Java 8

By : Javier Fernández González
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Mastering Concurrency Programming with Java 8

Mastering Concurrency Programming with Java 8

3 (4)
By: Javier Fernández González

Overview of this book

Concurrency programming allows several large tasks to be divided into smaller sub-tasks, which are further processed as individual tasks that run in parallel. All the sub-tasks are combined together once the required results are achieved; they are then merged to get the final output. The whole process is very complex. This process goes from the design of concurrent algorithms to the testing phase where concurrent applications need extra attention. Java includes a comprehensive API with a lot of ready-to-use components to implement powerful concurrency applications in an easy way, but with a high flexibility to adapt these components to your needs. The book starts with a full description of design principles of concurrent applications and how to parallelize a sequential algorithm. We'll show you how to use all the components of the Java Concurrency API from basics to the most advanced techniques to implement them in powerful concurrency applications in Java. You will be using real-world examples of complex algorithms related to machine learning, data mining, natural language processing, image processing in client / server environments. Next, you will learn how to use the most important components of the Java 8 Concurrency API: the Executor framework to execute multiple tasks in your applications, the phaser class to implement concurrent tasks divided into phases, and the Fork/Join framework to implement concurrent tasks that can be split into smaller problems (using the divide and conquer technique). Toward the end, we will cover the new inclusions in Java 8 API, the Map and Reduce model, and the Map and Collect model. The book will also teach you about the data structures and synchronization utilities to avoid data-race conditions and other critical problems. Finally, the book ends with a detailed description of the tools and techniques that you can use to test a Java concurrent application.
Table of Contents (13 chapters)
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12
Index

First example - a keyword extraction algorithm


In this section, you are going to use a phaser to implement a keyword extraction algorithm. The main purpose of these kinds of algorithms is to extract the words from a text document or a collection of documents, which define the document or the document inside the collection, better. These terms can be used to summarize the documents, cluster them, or to improve the information search process.

The most basic algorithm to extract the keywords of the documents in a collection (but it's still commonly used nowadays) is based on the TF-IDF measure where:

  • Term Frequency (TF) is the number of times that a d appears in a document.
  • Document Frequency (DF) is the number of documents that contain a word. The Inverse Document Frequency (IDF) measures the information that word provides to distinguish a document from others. If a word is very common, its IDF will be low, but if the word appears in only a few documents, its IDF will be high.

The TF-IDF of the...

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