Java 8 Lambdas

lambdas Preface. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . vii 1. Introduction. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 Why Did They Need to Change Java Again? 1 What Is Functional Programming? 2 Example Domain 3 2. Lambda Expressions. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 Your First Lambda Expression 5 How to Spot a Lambda in a Haystack 6 Using Values 8 Functional Interfaces 9 Type Inference 11 Key Points 13 Exercises 14 3. Streams. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17 From External Iteration to Internal Iteration 17 What’s Actually Going On 20 Common Stream Operations 21 collect(toList()) 22 map 22 filter 24 flatMap 25 max and min 26 A Common Pattern Appears 27 reduce 28 Putting Operations Together 30 Refactoring Legacy Code 31 iii Multiple Stream Calls 34 Higher-Order Functions 36 Good Use of Lambda Expressions 36 Key Points 37 Exercises 37 Advanced Exercises 39 4. Libraries. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 41 Using Lambda Expressions in Code 41 Primitives 42 Overload Resolution 45 @FunctionalInterface 47 Binary Interface Compatibility 47 Default Methods 48 Default Methods and Subclassing 49 Multiple Inheritance 52 The Three Rules 53 Tradeoffs 54 Static Methods on Interfaces 54 Optional 55 Key Points 56 Exercises 57 Open Exercises 58 5. Advanced Collections and Collectors. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 59 Method References 59 Element Ordering 60 Enter the Collector 62 Into Other Collections 62 To Values 63 Partitioning the Data 64 Grouping the Data 65 Strings 66 Composing Collectors 67 Refactoring and Custom Collectors 69 Reduction as a Collector 76 Collection Niceties 77 Key Points 78 Exercises 78 6. Data Parallelism. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 81 Parallelism Versus Concurrency 81 iv | Table of Contents Why Is Parallelism Important? 83 Parallel Stream Operations 83 Simulations 85 Caveats 88 Performance 89 Parallel Array Operations 92 Key Points 94 Exercises 94 7. Testing, Debugging, and Refactoring. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 97 Lambda Refactoring Candidates 97 In, Out, In, Out, Shake It All About 98 The Lonely Override 98 Behavioral Write Everything Twice 99 Unit Testing Lambda Expressions 102 Using Lambda Expressions in Test Doubles 105 Lazy Evaluation Versus Debugging 106 Logging and Printing 106 The Solution: peek 107 Midstream Breakpoints 107 Key Points 108 8. Design and Architectural Principles. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 109 Lambda-Enabled Design Patterns 110 Command Pattern 110 Strategy Pattern 114 Observer Pattern 117 Template Method Pattern 119 Lambda-Enabled Domain-Specific Languages 123 A DSL in Java 124 How We Got There 125 Evaluation 127 Lambda-Enabled SOLID Principles 127 The Single Responsibility Principle 128 The Open/Closed Principle 130 The Dependency Inversion Principle 134 Further Reading 137 Key Points 137 9. Lambda-Enabled Concurrency. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 139 Why Use Nonblocking I/O? 139 Callbacks 140 Table of Contents | v Message Passing Architectures 144 The Pyramid of Doom 145 Futures 147 Completable Futures 149 Reactive Programming 152 When and Where 155 Key Points 155 Exercises 156 10. Moving Forward 159