Mastering concurrency programming with java 9 : perfect the art of faster and more effective programming with parallel and reactive streams

Mastering concurrency programming with java 9 perfect the art of faster and more effective programming with parallel and reactive streams

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 re...

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Detalles Bibliográficos
Otros Autores: Gonzalez, Javier Fernandez, author (author)
Formato: Libro electrónico
Idioma:Inglés
Publicado: Birmingham, England ; Mumbai, [India] : Packt 2017.
Edición:Second edition
Materias:
Java (Computer program language)
Ver en Biblioteca Universitat Ramon Llull:https://discovery.url.edu/permalink/34CSUC_URL/1im36ta/alma991009630504006719
Tabla de Contenidos:
  • Cover
  • Copyright
  • Credits
  • About the Author
  • About the Reviewer
  • www.PacktPub.com
  • Customer Feedback
  • Table of Contents
  • Preface
  • Chapter 1: The First Step - Concurrency Design Principles
  • Basic concurrency concepts
  • Concurrency versus parallelism
  • Synchronization
  • Immutable object
  • Atomic operations and variables
  • Shared memory versus message passing
  • Possible problems in concurrent applications
  • Data race
  • Deadlock
  • Livelock
  • Resource starvation
  • Priority inversion
  • A methodology to design concurrent algorithms
  • The starting point - a sequential version of the algorithm
  • Step 1 - analysis
  • Step 2 - design
  • Step 3 - implementation
  • Step 4 - testing
  • Step 5 - tuning
  • Conclusion
  • Java Concurrency API
  • Basic concurrency classes
  • Synchronization mechanisms
  • Executors
  • The fork/join framework
  • Parallel streams
  • Concurrent data structures
  • Concurrency design patterns
  • Signaling
  • Rendezvous
  • Mutex
  • Multiplex
  • Barrier
  • Double-checked locking
  • Read-write lock
  • Thread pool
  • Thread local storage
  • 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
  • Chapter 2: Working with Basic Elements - Threads and Runnables.
  • Threads in Java
  • Threads in Java - characteristics and states
  • The Thread class and the Runnable interface
  • First example: matrix multiplication
  • Common classes
  • Serial version
  • Parallel versions
  • First concurrent version - a thread per element
  • Second concurrent version - a thread per row
  • Third concurrent version - the number of threads is determined by the processors
  • Comparing the solutions
  • Second example - file search
  • Common classes
  • Serial version
  • Concurrent version
  • Comparing the solutions
  • Summary
  • Chapter 3: Managing Lots of Threads - Executors
  • An introduction to executors
  • Basic characteristics of executors
  • Basic components of the Executor framework
  • First example - the k-nearest neighbors algorithm
  • k-nearest neighbors - serial version
  • K-nearest neighbors - a fine-grained concurrent version
  • k-nearest neighbors - a coarse-grained concurrent version
  • Comparing the solutions
  • Second example - concurrency in a client/server environment
  • Client/server - serial version
  • The DAO part
  • The command part
  • The server part
  • Client/version - parallel version
  • The server part
  • The command part
  • Extra components of the concurrent server
  • The status command
  • The cache system
  • The log system
  • Comparing the two solutions
  • Other methods of interest
  • Summary
  • Chapter 4: Getting the Most from Executors
  • Advanced characteristics of executors
  • Cancellation of tasks
  • Scheduling the execution of tasks
  • Overriding the executor methods
  • Changing some initialization parameters
  • First example - an advanced server application
  • The ServerExecutor class
  • The statistics object
  • The rejected task controller
  • The executor tasks
  • The executor
  • The command classes
  • The ConcurrentCommand class
  • The concrete commands
  • The server part.
  • The ConcurrentServer class
  • The RequestTask class
  • The client part
  • Second example - executing periodic tasks
  • The common parts
  • The basic reader
  • The advanced reader
  • Additional information about executors
  • Summary
  • Chapter 5: Getting Data from Tasks - The Callable and Future Interfaces
  • Introducing the Callable and Future interfaces
  • The Callable interface
  • The Future interface
  • First example - a best-matching algorithm for words
  • The common classes
  • A best-matching algorithm - the serial version
  • The BestMatchingSerialCalculation class
  • The BestMachingSerialMain class
  • A best-matching algorithm - the first concurrent version
  • The BestMatchingBasicTask class
  • The BestMatchingBasicConcurrentCalculation class
  • A best-matching algorithm - the second concurrent version
  • Word exists algorithm - a serial version
  • The ExistSerialCalculation class
  • The ExistSerialMain class
  • Word exists algorithm - the concurrent version
  • The ExistBasicTasks class
  • The ExistBasicConcurrentCalculation class
  • The ExistBasicConcurrentMain class
  • Comparing the solutions
  • Best-matching algorithms
  • Exist algorithms
  • The second example - creating an inverted index for a collection of documents
  • Common classes
  • The Document class
  • The DocumentParser class
  • The serial version
  • The first concurrent version - a task per document
  • The IndexingTask class
  • The InvertedIndexTask class
  • The ConcurrentIndexing class
  • The second concurrent version - multiple documents per task
  • The MultipleIndexingTask class
  • The MultipleInvertedIndexTask class
  • The MultipleConcurrentIndexing class
  • Comparing the solutions
  • Other methods of interest
  • Summary
  • Chapter 6: Running Tasks Divided into Phases - The Phaser Class
  • An introduction to the Phaser class
  • Registration and deregistration of participants.
  • Synchronizing phase change
  • Other functionalities
  • First example - a keyword extraction algorithm
  • Common classes
  • The Word class
  • The Keyword class
  • The Document class
  • The DocumentParser class
  • The serial version
  • The concurrent version
  • The KeywordExtractionTask class
  • The ConcurrentKeywordExtraction class
  • Comparing the two solutions
  • The second example - a genetic algorithm
  • Common classes
  • The Individual class
  • The GeneticOperators class
  • The serial version
  • The SerialGeneticAlgorithm class
  • The SerialMain class
  • The concurrent version
  • The SharedData class
  • The GeneticPhaser class
  • The ConcurrentGeneticTask class
  • The ConcurrentGeneticAlgorithm class
  • The ConcurrentMain class
  • Comparing the two solutions
  • Lau15 dataset
  • Kn57 dataset
  • Conclusions
  • Summary
  • Chapter 7: Optimizing Divide and Conquer Solutions - The Fork/Join Framework
  • An introduction to the fork/join framework
  • Basic characteristics of the fork/join framework
  • Limitations of the fork/join framework
  • Components of the fork/join framework
  • The first example - the k-means clustering algorithm
  • The common classes
  • The VocabularyLoader class
  • The word, document, and DocumentLoader classes
  • The DistanceMeasurer class
  • The DocumentCluster class
  • The serial version
  • The SerialKMeans class
  • The SerialMain class
  • The concurrent version
  • Two tasks for the fork/join framework - AssignmentTask and UpdateTask
  • The ConcurrentKMeans class
  • The ConcurrentMain class
  • Comparing the solutions
  • The second example - a data filtering algorithm
  • Common features
  • The serial version
  • The SerialSearch class
  • The SerialMain class
  • The concurrent version
  • The TaskManager class
  • The IndividualTask class
  • The ListTask class
  • The ConcurrentSearch class
  • The ConcurrentMain class.
  • Comparing the two versions
  • The third example - the merge sort algorithm
  • Shared classes
  • The serial version
  • The SerialMergeSort class
  • The SerialMetaData class
  • The concurrent version
  • The MergeSortTask class
  • The ConcurrentMergeSort class
  • The ConcurrentMetaData class
  • Comparing the two versions
  • Other methods of the fork/join framework
  • Summary
  • Chapter 8: Processing Massive Datasets with Parallel Streams - The Map and Reduce Model
  • An introduction to streams
  • Basic characteristics of streams
  • Sections of a stream
  • Sources of a stream
  • Intermediate operations
  • Terminal operations
  • MapReduce versus MapCollect
  • The first example - a numerical summarization application
  • The concurrent version
  • The ConcurrentDataLoader class
  • The ConcurrentStatistics class
  • Customers from the United Kingdom
  • Quantity from the United Kingdom
  • Countries for product
  • Quantity for product
  • Multiple data filter
  • Highest invoice amounts
  • Products with a unit price between 1 and 10
  • The ConcurrentMain class
  • The serial version
  • Comparing the two versions
  • The second example - an information retrieval search tool
  • An introduction to the reduction operation
  • The first approach - full document query
  • The basicMapper() method
  • The Token class
  • The QueryResult class
  • The second approach - reduced document query
  • The limitedMapper() method
  • The third approach - generating an HTML file with the results
  • The ContentMapper class
  • The fourth approach - preloading the inverted index
  • The ConcurrentFileLoader class
  • 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.

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