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Mastering Concurrency Programming with Java 9, Second Edition

You're reading from   Mastering Concurrency Programming with Java 9, Second Edition Fast, reactive and parallel application development

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Product type Paperback
Published in Jul 2017
Publisher Packt
ISBN-13 9781785887949
Length 516 pages
Edition 2nd Edition
Languages
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Author (1):
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Javier Fernández González Javier Fernández González
Author Profile Icon Javier Fernández González
Javier Fernández González
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Toc

Table of Contents (14) Chapters Close

Preface 1. The First Step - Concurrency Design Principles FREE CHAPTER 2. Working with Basic Elements - Threads and Runnables 3. Managing Lots of Threads - Executors 4. Getting the Most from Executors 5. Getting Data from Tasks - The Callable and Future Interfaces 6. Running Tasks Divided into Phases - The Phaser Class 7. Optimizing Divide and Conquer Solutions - The Fork/Join Framework 8. Processing Massive Datasets with Parallel Streams - The Map and Reduce Model 9. Processing Massive Datasets with Parallel Streams - The Map and Collect Model 10. Asynchronous Stream Processing - Reactive Streams 11. Diving into Concurrent Data Structures and Synchronization Utilities 12. Testing and Monitoring Concurrent Applications 13. Concurrency in JVM - Clojure and Groovy with the Gpars Library and Scala

The second example - an information retrieval search tool


According to Wikipedia (https://en.wikipedia.org/wiki/Information_retrieval), information retrieval is:

"The activity obtaining information resources relevant to an information need from a collection of information resources"

Usually, the information resources are a collection of documents and the information needed is a set of words, which summarizes our need. To do a quick search over the document collection, we use a data structure named inverted index. It stores all the words of the document collection, and for each word, a list of the documents that contains that word. In Chapter 5, Getting Data From the Tasks - The Callable and Future Interfaces, you constructed an inverted index of a document collection constructed with the Wikipedia pages with information about movies to construct a set of 100,673 documents. We have converted each Wikipedia page into a text file. This inverted index is stored in a text file where each line contains...

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