Streams, Collectors, and Optionals for Data Processing in Java 8

Introduction to the Course 2m 1s What Are You Going to Learn in This Course? 2m 33s What Should You Know to Follow This Course? Agenda of This Module 2m 25s What Is a Spliterator? 3m 55s The Spliterator Interface, What Do We Need to Implement? 3m 18s The ArrayListSpliterator: the tryAdvance() Method 2m 5s The ArrayListSpliterator: the trySplit() Method 2m 39s Introduction to the Live Coding: How to Write a Spliterator 1m 56s Using Our Own Spliterator: Setting up the Application 2m 13s Using Our Own Spliterator: Writing the Use Case Pattern 2m 11s Implementing Our Own Spliterator: The First Methods 3m 4s Implementing Our Own Spliterator: The tryAdvance() Method 3m 37s Implementing the tryAdvance() Method: Setting the Returned Object 1m 50s Implementing Our Own Spliterator: Running the Example 1m 10s Live Coding Session Wrap-up 1m 12s Module Wrap-up 1m 32s

Introduction and Agenda of the module 1m 53s Concatenating Streams: The Stream.concat Pattern 3m 5s Merging Streams: The Stream.of and flatMap Pattern 2m 50s How Does the flatMap Pattern Work: Examples 1m 43s Splitting a Text into Words Using the flatMap Pattern 3m 25s Splitting a Text into Words: Putting the Result in a Set 1m 33s State of a Stream: The Stream.characteristics() Method 2m 51s What Are the Eight Characteristics of a Stream? 2m 10s How Does the Steam Methods Modify the State of a Stream 2m 30s State of a Stream: A First Example 2m 3s How to Use the Stream.sorted() Method with a Comparator 0m 54s Live Coding Session: Presentation of the Example 1m 48s Live Coding: Merging Streams Using Stream.of and flatMap 3m 20s Live Coding: Splitting a Large Text in Words Using flatMap 3m 38s Live Coding Session Summary 0m 51s Streams of Numbers: Converting from a Stream of Objects 1m 50s Optimizing the Conversion from a Stream of Objects 1m 27s Patterns to Build Streams of Numbers 1m 41s Specialized Methods: min(), max() and summaryStatistics() 2m 49s Live Coding Session: Introduction of the Scrabble Example 2m 1s Live Coding: Computing the Score of a Word in Scrabble 3m 25s Live Coding: Getting the Word with the Best Score 3m 18s Live Coding: Computing Statistics on the Words of Shakespeare 1m 56s Live Coding Session and Module Wrap-up 2m 41s

Introduction and Agenda of the Module 1m 49s Building Parallel Processing on Multithread 3m 24s Tools for Parallel Processing in the JDK 2m 51s Parallel Streams: First Patterns 2m 8s Caveats in Parallel Processing: Synchronization and Visibility 1m 53s Stateful and Stateless Operations: The Limit Method Example 3m 6s How to Tell a Stateless Operation from a Stateful One 0m 58s Parallel Performance Analysis: Description of the Use Case 3m 21s Parallel Performance Analysis: Understanding the Computing Times 2m 16s A Sneaky Stateful Operation: The unordered() Method 2m 12s Parallel Reduction: What Not to Do! 3m 47s Tuning Parallelism: Setting the Size of the Common Fork Join Pool 2m 11s Tuning Parallelism: Setting the Executor of a Computation 2m 13s Live Coding: Understanding the Multithreaded Computation 3m 57s Live Coding: Parallel Reduction, How Can It Go Wrong? 3m 3s Live Coding: Parallel Reduction, Hint at the Collector Pattern 0m 57s Live Coding Session Summary 1m 20s Module Wrap-up 2m 36s

Introduction and Agenda of the Module 1m 35s Optional: A First Explanation of the Concept 3m 28s Patterns to Use an Optional as a Wrapper Type That Can Be Empty 2m 7s Patterns to Build an Optional from Scratch 2m 35s More Optional Patterns: The Map, Filter and ifPresent Patterns 2m 30s How We Can See an Optional as a Special Kind of Stream 0m 43s Introduction to Advanced Optional Patterns: The NewMath Example 1m 45s Building a First Data Processing Pipeline with the NewMath Class 1m 55s How Does the Optional.flatMap Pattern Work? 2m 23s Leveraging the flatMap Pattern to Convert an Optional to a Stream 4m 20s Building a Parallel Data Processing Pipeline with NewMath 1m 23s Introduction to the Live Coding Session 0m 22s Live Coding: How Not to Process Doubles with NewMath 2m 46s Live Coding: Failing to Go Parallel with the Wrong Pattern 2m 33s Live Coding: Building an Optional flatMapper for NewMath 2m 56s Live Coding: Analyzing the Optional flatMapper 1m 25s Live Coding: Parallel Stream with the Optional flatMapper 3m 14s Live Coding Session Summary 1m 30s Module Wrap-up 2m 6s

Introduction and Agenda of the Module 1m 54s What Is a Collector? A Look Back at the Reduction Step 1m 1s A First Anti-pattern to Reduce a Stream in a List 1m 56s Reduction in a List: The Right Pattern with a Collector 1m 17s The Collectors Class: We Have a Collector for That 2m 33s Computing a Max and an Average with a Collector 1m 36s Building Strings with a Collector 0m 46s Collecting Data in a Set 1m 10s Collecting in a Map: The partiionningBy and groupingBy Patterns 2m 26s Adding a Downstream Collector to Process Map Values 1m 41s Specifying Built Containers, the collectingAndThen Pattern 2m 30s Live Coding: Introducing the Shakespeare Plays Scrabble Use Case 2m 49s Live Coding: Building Histograms to Extract the Best Words 4m 38s Live Coding: Writing Whizzing with a Blank Letter 1m 55s Live Coding: Computing the Histogram of the Letters of a Word 2m 43s Live Coding: Computing the Number of Blanks Need for Whizzing 4m 25s Live Coding: Computing the Score of Words with Blank Letters 3m 19s Live Coding: Computing the Best Words with Blanks 1m 45s Live Coding Session Summary 1m 43s Module Wrap-up 3m 1s

Introduction and Agenda of the Module 1m 44s What if We Need Collectors that Are Not in the Collectors Class? 1m 16s Collectors Made of a Supplier, an Accumulator, and a Combiner 1m 47s Example of a Supplier and Accumulator for an ArrayList 1m 32s Example of a Combiner for an ArrayList 1m 40s Putting it All Together: The Collector.of Pattern 1m 47s Live Coding: Presenting the Actors and Movies Use Case 2m 35s Live Coding: Counting the Number of Actors 2m 40s Live Coding: Finding the Actor That Played in the Most Movies 4m 26s Live Coding: Adding the Year Constraint, Introduction 2m 6s Live Coding: Setting the Custom Downstream Collector 1m 0s Live Coding: Writing the Supplier for the Custom Collector 1m 30s Live Coding: Writing the Accumulator 2m 35s Live Coding: Writing the Combiner by Merging Maps 2m 50s Live Coding: Taking a Global Look at the Custom Collector 2m 29s Live Coding: Extracting the Max of the Submap 4m 6s Live Coding: Extracting the Max of the Main Map 2m 6s Live Coding Session Summary 2m 0s Other Custom Collectors: The summaryStatistics Pattern 2m 5s Module Wrap-up 2m 17s