Book Image

Mastering Concurrency Programming with Java 8

By : Javier Fernández González
Book Image

Mastering Concurrency Programming with Java 8

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 (18 chapters)
Mastering Concurrency Programming with Java 8
About the Author
About the Reviewers

The first example – searching data without an index

In Chapter 7, Processing Massive Datasets with Parallel Streams – The Map and Reduce Model, you learned how to implement a search tool to look for the documents similar to an input query using an inverted index. This data structure makes the search operation easier and faster, but there will be situations where you will have to make a search operation over a big set of data and you won't have an inverted index to help you. In these cases, you have to process all the elements of the dataset to get the correct results. In this example, you will see one of these situations and how the reduce() method of the Stream API can help you.

To implement this example, you will use a subset of the Amazon product co-purchasing network metadata that includes information about 548,552 products sold by Amazon, which includes title, salesrank, and the lists of similar products, categories, and reviews. You can download this dataset from https://snap.stanford...