Java Programming - Lecture 40

Java Programming

Lecture 40: Stream API

GTU Diploma in Computer Engineering

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Learning Objectives

After this lecture, you will be able to:

  • Understand the concept and benefits of Java Streams
  • Create streams from various data sources
  • Use intermediate operations for data transformation
  • Apply terminal operations to produce results
  • Work with parallel streams for performance
  • Use collectors for data aggregation
  • Create custom collectors for specific needs
  • Apply stream best practices and performance optimization

::right::

Lecture Overview

  1. Introduction to Stream API
  2. Creating Streams
  3. Intermediate Operations
  4. Terminal Operations
  5. Parallel Streams
  6. Collectors
  7. Custom Collectors
  8. Advanced Stream Operations
  9. Performance and Best Practices
  10. Hands-on Exercises

What is Stream API?

Stream API provides a functional programming approach to processing collections of data.

Key Characteristics

  1. No Storage: Streams don't store data, they operate on data sources
  2. Functional in Nature: Operations don't modify the source
  3. Lazy Evaluation: Intermediate operations are not executed until terminal operation is called
  4. Possibly Unbounded: Streams can be infinite
  5. Consumable: Stream elements are visited only once

Stream vs Collection

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Creating Streams

From Collections

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Stream Factory Methods

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Intermediate Operations

Intermediate operations are lazy and return a stream.

Filter, Map, and Sorted

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More Intermediate Operations

Distinct, Limit, Skip, and FlatMap

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Terminal Operations

Terminal operations consume the stream and produce a result.

Basic Terminal Operations

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Advanced Terminal Operations

Working with Primitive Streams

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Collectors

Collectors provide a way to accumulate stream elements into collections or other results.

Basic Collectors

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Advanced Collectors

Grouping and Partitioning

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Custom Collectors

Creating your own collectors for specific use cases.

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Parallel Streams

Parallel streams can improve performance for CPU-intensive operations on large datasets.

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Stream Performance and Best Practices

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Hands-on Exercise 1: Student Management System

Create a comprehensive student management system using Stream API:

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Hands-on Exercise 2: E-commerce Data Analysis

Create an e-commerce data analysis system:

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Exercise Solutions: Student Management System

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Summary

Key Concepts Covered

  1. Stream Creation: Various ways to create streams from different data sources
  2. Intermediate Operations: filter, map, sorted, distinct, limit, skip, flatMap
  3. Terminal Operations: collect, forEach, reduce, find operations, match operations
  4. Collectors: Built-in collectors for common aggregation operations
  5. Custom Collectors: Creating specialized collectors for specific use cases
  6. Parallel Streams: Leveraging multiple cores for performance
  7. Performance Considerations: When and how to optimize stream operations

Benefits of Stream API

  • Functional Style: More expressive and readable code
  • Lazy Evaluation: Operations are optimized and executed only when needed
  • Composability: Operations can be easily chained and combined
  • Parallelization: Easy to leverage multiple cores
  • Integration: Works seamlessly with collections and other Java APIs

Best Practices

  • Keep lambda expressions simple and readable
  • Avoid side effects in stream operations
  • Use appropriate collectors for better performance
  • Consider parallel streams for CPU-intensive operations on large datasets
  • Prefer primitive streams for numerical operations

Next Lecture Preview

Lecture 41: JavaFX Basics and GUI Programming

  • Introduction to JavaFX
  • Scene Graph and Application Structure
  • Creating User Interfaces with FXML
  • Event Handling and Controls
  • Layouts and Styling with CSS
  • Building Desktop Applications

Preparation

  • Ensure JavaFX is available in your development environment
  • Review event-driven programming concepts
  • Practice with lambda expressions for event handling

Thank You!

Questions and Discussion

  • How do streams improve code readability and maintainability?
  • When would you choose parallel streams over sequential streams?
  • What are the trade-offs between streams and traditional loops?

Resources for Further Learning

  • Oracle Stream API Documentation
  • Java 8 in Action by Raoul-Gabriel Urma
  • Practice with real-world datasets and stream operations

Next: JavaFX and GUI Application Development