Book description
Master the principles to make applications robust, scalable and responsive
About This Book
- Implement concurrent applications using the Java 9 Concurrency API and its new components
- Improve the performance of your applications and process more data at the same time, taking advantage of all of your resources
- Construct real-world examples related to machine learning, data mining, natural language processing, and more
Who This Book Is For
This book is for competent Java developers who have basic understanding of concurrency, but knowledge of effective implementation of concurrent programs or usage of streams for making processes more efficient is not required
What You Will Learn
- Master the principles that every concurrent application must follow
- See how to parallelize a sequential algorithm to obtain better performance without data inconsistencies and deadlocks
- Get the most from the Java Concurrency API components
- Separate the thread management from the rest of the application with the Executor component
- Execute phased-based tasks in an efficient way with the Phaser components
- Solve problems using a parallelized version of the divide and conquer paradigm with the Fork / Join framework
- Find out how to use parallel Streams and Reactive Streams
- Implement the ?map and reduce? and ?map and collect? programming models
- Control the concurrent data structures and synchronization mechanisms provided by the Java Concurrency API
- Implement efficient solutions for some actual problems such as data mining, machine learning, and more
In Detail
Concurrency programming allows several large tasks to be divided into smaller sub-tasks, which are further processed as individual tasks that run in parallel. Java 9 includes a comprehensive API with lots of ready-to-use components for easily implementing powerful concurrency applications, but with high flexibility so you can adapt these components to your needs.
The book starts with a full description of the design principles of concurrent applications and explains how to parallelize a sequential algorithm. You will then be introduced to Threads and Runnables, which are an integral part of Java 9's concurrency API. You will see how to use all the components of the Java concurrency API, from the basics to the most advanced techniques, and will implement them in powerful real-world concurrency applications.
The book ends with a detailed description of the tools and techniques you can use to test a concurrent Java application, along with a brief insight into other concurrency mechanisms in JVM.
Style and approach
This is a complete guide that implements real-world examples of algorithms related to machine learning, data mining, and natural language processing in client/server environments. All the examples are explained using a step-by-step approach.
Table of contents
- Preface
-
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
-
Tips and tricks for designing concurrent algorithms
- Identifying the correct independent tasks
- Implementing concurrency at the highest possible level
- Taking scalability into account
- Using thread-safe APIs
- Never assume an execution order
- Preferring local thread variables over static and shared when possible
- Finding the easier parallelizable version of the algorithm
- Using immutable objects when possible
- Avoiding deadlocks by ordering the locks
- Using atomic variables instead of synchronization
- Holding locks for as short a time as possible
- Taking precautions using lazy initialization
- Avoiding the use of blocking operations inside a critical section
- Summary
- Working with Basic Elements - Threads and Runnables
- Managing Lots of Threads - Executors
- Getting the Most from Executors
-
Getting Data from 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
- Running Tasks Divided into Phases - The Phaser Class
-
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
-
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
- An introduction to the reduction operation
- The first approach - full document query
- The second approach - reduced document query
- The third approach - generating an HTML file with the results
- The fourth approach - preloading the inverted index
- The fifth approach - using our own executor
- Getting data from the inverted index - the ConcurrentData class
- Getting the number of words in a file
- Getting the average tfxidf value in a file
- Getting the maximum and minimum tfxidf values in the index
- The ConcurrentMain class
- The serial version
- Comparing the solutions
- Summary
- Processing Massive Datasets with Parallel Streams - The Map and Collect Model
- Asynchronous Stream Processing - Reactive Streams
- Diving into Concurrent Data Structures and Synchronization Utilities
- Testing and Monitoring Concurrent Applications
- Concurrency in JVM - Clojure and Groovy with the Gpars Library and Scala
Product information
- Title: Mastering Concurrency Programming with Java 9 - Second Edition
- Author(s):
- Release date: July 2017
- Publisher(s): Packt Publishing
- ISBN: 9781785887949
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