Scaling Java Applications Through Concurrency

By Josh Cummings
Distributed systems and multi-core platforms are far too prevalent now to dismiss everyday concurrency. This course outlines several concurrency patterns that the Java Concurrency API simplifies, making it much easier to scale your Java application.
Course info
Rating
(46)
Level
Intermediate
Updated
Aug 4, 2016
Duration
2h 20m
Table of contents
The End of Moore’s Law
Patterns Over Primitives 5m
Running Processes in the Background
The Fire-and-Forget Pattern 3m Introducing ThreadPoolExecutor 4m Implementing Fire-and-Forget Using ThreadPoolExecutor 7m Introducing ForkJoinPool 2m Implementing Fire-and-Forget Using ForkJoinPool 1m Introducing Threaded Recursion with ForkJoinPool and BlockingQueue 2m Implementing Fire-and-Forget Using Threaded Recursion 4m Conclusion 1m
Sharing Resources Among Parallel Workers
Introduction 0m The Scatter-Gather Pattern 2m Scatter-Gather Using Futures 3m Scatter-Gather Using ExecutorService 4m ExecutorService vs. ExecutorCompletionService Performance 2m The Importance of Making Aggregations Thread-safe 3m Gathering Using Concurrency Primitives 4m Gathering Using AtomicInteger, ConcurrentHashMap, and LongAdder 4m Gathering Using ReentrantLock 4m Max Search Using TryLock 3m Conclusion 1m
Coordinating Efforts Among Dependent Processes
Introduction 1m Dependency Choreography Using CountDownLatch 3m Implementing Dependency Choreography Using CountDownLatch 3m Dependency Choreography Using Continuation-passing 5m Implementing Dependency Choreography Using Continuation-Passing 17m Dependency Choreography Using CompletableFuture 3m Implementing Dependency Choreography Using CompletableFuture 6m Addressing Thread Contention Using Thread Pools 3m Conclusion 1m
Throttling Incoming Work
Introduction 3m Throttling Using ThreadPoolExecutor 3m Implementing Throttling Using ThreadPoolExecutor 7m Throttling Using Semaphore 2m Implementing Throttling Using Semaphore 4m Throttling Using CyclicBarrier 3m Implementing Throttling Using CyclicBarrier 6m Throttling Using Phaser 3m Implementing Throttling Using Phaser 5m Performance Metrics Breakdown 2m Conclusion 1m
Description
Course info
Rating
(46)
Level
Intermediate
Updated
Aug 4, 2016
Duration
2h 20m
Description

There are several gems inside the existing concurrency API that have been hiding in the background for years, waiting to be discovered by curious software engineers. The existing Java Concurrency API makes it much easier to build a Java application that is scalable and performant without having to settle for lots of low-level wait-notify usage or lots of locking using the synchronized keyword. In this course, Scaling Java Applications Through Concurrency, you'll cover several concurrency patterns simplified by the Java Concurrency API; these patterns will make scaling new and existing Java applications simpler than ever. First, you'll learn about how the Java Concurrency API has changed scalability and how to run processes in the background. Next, you'll cover classes that will help you avoid mistakes like lost updates when sharing resources. Finally, you'll discover how to coordinate dependent processes and implementing throttling. By the end of this course, you will be able to easily scale your Java applications through concurrency so that they work better and faster.

About the author
Josh Cummings
About the author

Like many software craftsmen, Josh eats, sleeps, and dreams in code. He codes for fun, and his kids code for fun! Right now, Josh works as a full-time committer on Spring Security and loves every minute.

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