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Home > Programming > Concurrency > Mastering Concurrency Programming with Java 8
Mastering Concurrency Programming with Java 8
Mastering Concurrency Programming with Java 8

Mastering Concurrency Programming with Java 8: Master the principles and techniques of multithreaded programming with the Java 8 Concurrency API

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Profile Icon Javier Fernández González
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Mastering Concurrency Programming with Java 8

Chapter 2. Managing Lots of Threads – Executors

When you implement a simple concurrent application, you create and execute a thread per concurrent task. This approach can have some important issues. Since Java version 5, the Java concurrency API includes the executor framework to improve the performance of concurrent applications with a lot of concurrent tasks. In this chapter, we will cover the following:

  • An introduction to executors
  • The first example – the k-nearest neighbors algorithm
  • The second example – concurrency in a client/server environment

An introduction to executors

The basic mechanism to implement a concurrent application in Java is:

  • A class that implements the Runnable interface: This is the code you want to implement in a concurrent way
  • An instance of the Thread class: This is the thread that is going to execute the code in a concurrent way

With this approach, you're responsible for creating and manning the Thread objects and implementing the mechanisms of synchronization between the threads. However, it can have some problems, especially with those applications with a lot of concurrent tasks. If you create too many threads, you can degrade the performance of your application or even hang the entire system.

Java 5 included the executor framework, to solve these problems and provide an efficient solution, which would be easier for the programmers to use than the traditional concurrency mechanisms.

In this chapter, we will introduce the basic characteristics of the executor framework by implementing the following two...

First example – the k-nearest neighbors algorithm

The k-nearest neighbors algorithm is a simple machine-learning algorithm used for supervised classification. The main components of this algorithm are:

  • A train dataset: This dataset is formed by instances with one or more attributes that define every instance and a special attribute that determines the example or label of the instance
  • A distance metric: This metric is used to determine the distance (or similarity) between the instances of the train dataset and the new instances you want to classify
  • A test dataset: This dataset is used to measure the behavior of the algorithm

When it has to classify an instance, it calculates the distance against this instance and all the instances of the train dataset. Then, it takes the k-nearest instances and looks at the tag of those instances. The tag with the most instances is the tag assigned to the input instance.

In this chapter, we are going to work with the Bank Marketing dataset of the UCI Machine...

The second example – concurrency in a client/server environment

The client/server model is a software architecture in which applications are split into two parts: the server part that provides resources (data, operations, printer, storage, and so on) and the client part that uses the resources provided by the server. Traditionally, this architecture was used in the enterprise world, but with the boom of the Internet, it is still an actual topic. You can see a web application as a client/server application where the server part is the backend part of the application that is executed in a web server and the web navigator executes the client part of the application. SOA (short for Service-Oriented Architecture) is an other example of client/server architecture where the web services exposed are the server part and the different clients that consume them are the client part.

In a client/server environment, we usually have one server and a lot of clients that use the services provided...

Comparing the two solutions

Now it's time to test the serial and concurrent servers and see which has a better performance. We have automatized the tests implementing four classes that make queries to the servers. These classes are:

  • SerialClient: This implements a possible client of the serial server. It makes nine requests using the query message and a query using the report message. It repeats the process 10 times, so it request 90 queries and 10 reports.
  • MultipleSerialClients: This class simulates the existence of several clients at the same time. For this, we create a thread per SerialClient and execute them at the same time to see the performance of the server. We have tested from one to five concurrent clients.
  • ConcurrentClient: It is analogue to the SerialClient class, but it calls the concurrent server instead of the serial one.
  • MultipleConcurrentClients: It is analogue to the MultipleSerialClients class, but it calls the concurrent server instead of the serial one.

To test the...

Other methods of interest

Throughout the pages of this chapter, we have used some classes of the Java concurrency API to implement basic functionalities of the executor framework. These classes also have other interesting methods. In this section, we collate some of them.

The Executors class provides other methods to create ThreadPoolExecutor objects. These methods are:

  • newCachedThreadPool(): This method creates a ThreadPoolExecutor object that reuses a worker-thread if it's idle, but it creates a new one if it's necessary. There is no maximum number of worker-threads.
  • newSingleThreadExecutor(): This method creates a ThreadPoolExecutor object that uses only a single worker-thread. The tasks you send to the executor are stored in a queue until the worker-thread can execute them.
  • The CountDownLatch class provides the following additional methods:
    • await(long timeout, TimeUnit unit): It waits till the internal counter arrives to zero of pass the time specified in the parameters. If the...

An introduction to executors

The basic mechanism to implement a concurrent application in Java is:

  • A class that implements the Runnable interface: This is the code you want to implement in a concurrent way

  • An instance of the Thread class: This is the thread that is going to execute the code in a concurrent way

With this approach, you're responsible for creating and manning the Thread objects and implementing the mechanisms of synchronization between the threads. However, it can have some problems, especially with those applications with a lot of concurrent tasks. If you create too many threads, you can degrade the performance of your application or even hang the entire system.

Java 5 included the executor framework, to solve these problems and provide an efficient solution, which would be easier for the programmers to use than the traditional concurrency mechanisms.

In this chapter, we will introduce the basic characteristics of the executor framework by implementing the following two examples...

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Key benefits

  • Implement concurrent applications using the Java 8 Concurrency API and its new components
  • Improve the performance of your applications or process more data at the same time, taking advantage of all of your resources.
  • Construct real-world examples related to machine learning, data mining, image processing, and client/server environments

Description

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.

Who is this book for?

If you are a competent Java developer with a good understanding of concurrency but have no knowledge of how to effectively implement concurrent programs or use streams to make processes more efficient, then this book is for you.

What you will learn

  • Design concurrent applications by converting a sequential algorithm into a concurrent one
  • Discover how to avoid all the possible problems you can get in concurrent algorithms
  • Use the Executor framework to manage concurrent tasks without creating threads
  • Extend and modify Executors to adapt their behavior to your needs
  • Solve problems using the divide and conquer technique and the Fork/Join framework
  • Process massive data sets with parallel streams and Map/Reduce implementation
  • Control data-race conditions using concurrent data structures and synchronization mechanisms
  • Test and monitor concurrent applications

Product Details

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Publication date : Feb 29, 2016
Length: 430 pages
Edition : 1st
Language : English
ISBN-13 : 9781785885464
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Oracle
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Programming
Languages :
Java
Concepts :
Concurrency

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Publication date : Feb 29, 2016
Length: 430 pages
Edition : 1st
Language : English
ISBN-13 : 9781785885464
Vendor :
Oracle
Category :
Programming
Languages :
Java
Concepts :
Concurrency

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Table of Contents

12 Chapters
1. The First Step – Concurrency Design Principles Chevron down icon Chevron up icon
1. The First Step – Concurrency Design Principles
Basic concurrency concepts
Possible problems in concurrent applications
A methodology to design concurrent algorithms
Java concurrency API
Concurrency design patterns
The Java memory model
Tips and tricks to design concurrent algorithms
Summary
2. Managing Lots of Threads – Executors Chevron down icon Chevron up icon
2. Managing Lots of Threads – Executors
An introduction to executors
First example – the k-nearest neighbors algorithm
The second example – concurrency in a client/server environment
Comparing the two solutions
Other methods of interest
Summary
3. Getting the Maximum from Executors Chevron down icon Chevron up icon
3. Getting the Maximum from Executors
Advanced characteristics of executors
The first example – an advanced server application
The second example – executing periodic tasks
Additional information about executors
Summary
4. Getting Data from the Tasks – The Callable and Future Interfaces Chevron down icon Chevron up icon
4. Getting Data from the Tasks – The Callable and Future Interfaces
Introducing the Callable and Future interfaces
First example – a best-matching algorithm for words
The second example – creating an inverted index for a collection of documents
Summary
5. Running Tasks Divided into Phases – The Phaser Class Chevron down icon Chevron up icon
5. Running Tasks Divided into Phases – The Phaser Class
An introduction to the Phaser class
First example – a keyword extraction algorithm
The second example – a genetic algorithm
Summary
6. Optimizing Divide and Conquer Solutions – The Fork/Join Framework Chevron down icon Chevron up icon
6. Optimizing Divide and Conquer Solutions – The Fork/Join Framework
An introduction to the Fork/Join framework
The first example – the k-means clustering algorithm
The second example – a data filtering algorithm
The third example – the merge sort algorithm
Other methods of the Fork/Join framework
Summary
7. Processing Massive Datasets with Parallel Streams – The Map and Reduce Model Chevron down icon Chevron up icon
7. Processing Massive Datasets with Parallel Streams – The Map and Reduce Model
An introduction to streams
The first example – a numerical summarization application
The second example – an information retrieval search tool
Summary
8. Processing Massive Datasets with Parallel Streams – The Map and Collect Model Chevron down icon Chevron up icon
8. Processing Massive Datasets with Parallel Streams – The Map and Collect Model
Using streams to collect data
The first example – searching data without an index
The second example – a recommendation system
The third example – common contacts in a social network
Summary
9. Diving into Concurrent Data Structures and Synchronization Utilities Chevron down icon Chevron up icon
9. Diving into Concurrent Data Structures and Synchronization Utilities
Concurrent data structures
Synchronization mechanisms
Summary
10. Integration of Fragments and Implementation of Alternatives Chevron down icon Chevron up icon
10. Integration of Fragments and Implementation of Alternatives
Big-block synchronization mechanisms
An example of a document clustering application
Implementation of alternatives with concurrent programming
Summary
11. Testing and Monitoring Concurrent Applications Chevron down icon Chevron up icon
11. Testing and Monitoring Concurrent Applications
Monitoring concurrency objects
Monitoring concurrency applications
Testing concurrency applications
Summary
Index Chevron down icon Chevron up icon
Index

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Customer reviews

Rating distribution
Full star icon Full star icon Full star icon Empty star icon Empty star icon 3
(4 Ratings)
5 star 25%
4 star 25%
3 star 0%
2 star 25%
1 star 25%
Paulo S. Jan 24, 2017
Full star icon Full star icon Full star icon Full star icon Full star icon 5
Very good book with some complex examples. Better than show just simple and unreal sample code.
Amazon Verified review Amazon
Fernando Sánchez Nov 20, 2016
Full star icon Full star icon Full star icon Full star icon Empty star icon 4
El contenido del libro es muy bueno. Quizás los ejemplos son de un nivel demasiado alto. La complejidad de los mismos a veces perjudica a la claridad de la explicación de los conceptos de concurrencia.
Amazon Verified review Amazon
Obaid Salikeen Feb 24, 2017
Full star icon Full star icon Empty star icon Empty star icon Empty star icon 2
There are a ton of code examples to understand apis however for understanding some basic concurrency concepts you might need to browse internet since this book touches more on apis/code (my opinion), the material could have been more engaging meaning I really had to make an effort to continue reading,,
Amazon Verified review Amazon
David Durham Sep 16, 2016
Full star icon Empty star icon Empty star icon Empty star icon Empty star icon 1
The codes samples are overly complicated with too much focus on example usage algorithms rather than the concurrency features of java8.
Amazon Verified review Amazon

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About the author

Profile icon Javier Fernández González
Javier Fernández González
Javier Fernandez is a software architect with almost 15 years experience with Java technologies. He has worked as a teacher, researcher, programmer, analyst, writer and now as an architect in all types of projects related to Java, especially J2EE. As a teacher, has taught over 1000 hours of training in basic Java, J2EE and Struts framework. As a researcher, has worked in the field of information retrieval developing applications for processing large amounts of data in Java and has participated as co-author on several journal articles and conference presentations. In recent years, has worked on developing J2EE web applications for various clients from different sectors (public administration, insurance, healthcare, transportation, ...). Currently he works as a software architect at Capgemini developing and maintaining applications for an insurance company. He is the author of the book Java 7 Concurrency Cookbook.
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