- Mastering Concurrency Programming with Java 8
- Table of Contents
- Mastering Concurrency Programming with Java 8
- Credits
- About the Author
- About the Reviewers
- www.PacktPub.com
- Preface
- 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
- Identify the correct independent tasks
- Implement concurrency at the highest possible level
- Take scalability into account
- Use thread-safe APIs
- Never assume an execution order
- Prefer local thread variables over static and shared when possible
- Find the more easily 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
- 2. Managing Lots of Threads – Executors
- 3. Getting the Maximum from Executors
- 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 common classes
- A best-matching algorithm – the serial version
- A best-matching algorithm – the first concurrent version
- A best-matching algorithm – the second concurrent version
- The word exists algorithm – a serial version
- The word exists algorithm – the concurrent version
- Comparing the solutions
- The second example – creating an inverted index for a collection of documents
- Summary
- 5. Running Tasks Divided into Phases – The Phaser Class
- 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
- 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
- 8. Processing Massive Datasets with Parallel Streams – The Map and Collect Model
- 9. Diving into Concurrent Data Structures and Synchronization Utilities
- 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
- The k-nearest neighbors' algorithm
- Building an inverted index of a collection of documents
- A best-matching algorithm for words
- A genetic algorithm
- A keyword extraction algorithm
- A k-means clustering algorithm
- A filtering data algorithm
- Searching an inverted index
- A numeric summarization algorithm
- A search algorithm without indexing
- A recommendation system using the Map and Collect model
- Summary
- 11. Testing and Monitoring Concurrent Applications
- Index
Author
Javier Fernández González
Reviewers
Antonio Gomes Rodrigues
Bradley Symons
Tagir Valeev
Commissioning Editor
Dipika Gaonkar
Acquisition Editor
Tushar Gupta
Content Development Editor
Shali Deeraj
Technical Editor
Gaurav Suri
Copy Editor
Dipti Mankame
Project Coordinator
Kinjal Bari
Proofreaders
Safis Editing
Indexers
Priya Sane
Graphics
Kirk D'Penha
Production Coordinator
Shantanu N. Zagade
Cover Work
Shantanu N. Zagade
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