While the term "lambda expression" may sound abstract and academic, Java 8 Lambdas can have a big impact on how you program every day. In simplest terms, a lambda expression is a function—a bit of code—that you can pass to another method as an argument. Thus, you can cope with changing requirements by using a behavior, represented by a lambda, as a parameter. Java 8's functional programming features, like lambdas and the new Stream API that enables a cleaner way to iterate through collections, can help you write concise, maintainable code that scales easily and performs well on multicore architectures.
Java 8 in Action is a clearly-written guide to Java 8 lambdas and functional programming in Java. It begins with a practical introduction to the structure and benefits of lambda expressions in real-world Java code. The book then introduces the Stream API and shows how it can make collections-related code radically easier to understand and maintain. Along the way, you'll discover new FP-oriented design patterns with Java 8 for code reuse, code readability, exception handling, data manipulation, and concurrency. For developers also exploring other functional languages on the JVM, the book concludes with a quick survey of useful functional features in Scala.
Raoul-Gabriel Urma has worked as a software engineer for Oracle's Java Platform Group, Google's Python team, Ebay, and Goldman Sachs as well as for several startup projects. He's currently completing a PhD in Computer Science at the University of Cambridge and is a regular speaker and instructor. Mario Fusco is a senior software engineer at Red Hat working on Drools, the JBoss ...
- 深入讲解Lambda表达式与Stream API
- 涵盖Optional、CompletableFuture等新特性
- 提供Java 8代码重构与并行处理实战
- 希望掌握Java 8新特性的Java开发者
- 需要重构旧代码以提升简洁性的程序员
- 对函数式编程思想感兴趣的初学者
- 建议结合书中代码示例动手实践
- 第四部分函数式思想较深，可酌情略读
- 重点理解Stream API与并行流的使用
- 讲解通俗易懂，是Java 8入门首选
- 内容全面，覆盖JDK 8所有核心新特性
- 侧重实战应用，原理性知识讲解较少
本导读基于书籍简介、目录、原文摘录、短评和书评生成，不等同于全文精读。
- "In fact, using synchronized across multiple processing cores is far more expensive than we often expect, because synchronization forces code to execute sequentially, which works against the goal of parallelism."
- "同步API与异步API 同步API其实只是对传统方法调用的另一种称呼：你调用了某个方法，调用方在被调用方 运行的过程中会等待，被调用方运行结束返回，调用方取得被调用方的返回值并继续运行。即 使调用方和被调用方在不同的线程中运行，调用方还是需要等待被调用方结束运行，这就是阻 塞式调用这个名词的由来。 与此相反， 异步API会直接返回，或者至少在被调用方计算完成之前，将它剩余的计算任 务交给另一个线程去做，该线程和调用方是异步的——这就是非阻塞式调用的由来。执行剩余 计算任务的线程会将它的计算结果返回给调用方。返回的方式要么是通过回调函数，要么是由 调用方再次执行一个“等待，直到计算完成”的方法调"
- "并行——使用流还是CompletableFutures？ 目前为止，你已经知道对集合进行并行计算有两种方式：要么将其转化为并行流，利用map 这样的操作开展工作，要么枚举出集合中的每一个元素，创建新的线程，在CompletableFuture内对其进行操作。后者提供了更多的灵活性，你可以调整线程池的大小，而这能帮助 你确保整体的计算不会因为线程都在等待I/O而发生阻塞。 我们对使用这些API的建议如下。 ❑如果你进行的是计算密集型的操作，并且没有I/O，那么推荐使用Stream接口，因为实 现简单，同时效率也可能是最高的（如果所有的线程都是计算密集型的，那就没有必要 创建比处理器核数更多的线程"
- "第二，要求它是 Predicate<Apple>（目标类型）对象的第二个正式参数"
- "名叫开放服务网关协议（open service gateway initiative, OGSi）"
显示全部
Deep Learning with Python (2/e)
Functional Design and Architecture
Grokking Machine Learning
Unit Testing
Deep Learning with JavaScript
Istio in Action