Exploring the Power of Java 8's Stream API and Frequently used cases, Sample programming

Introduction:

Java 8 brought a significant evolution to the language with the introduction of functional programming features. One of the standout features is the Stream API, a powerful tool for processing collections of data in a concise and expressive manner. In this blog post, we'll delve into the Stream API and discover how it has simplified and enhanced data manipulation in Java.

What is the Stream API?

The Stream API is a new abstraction introduced in Java 8 to process sequences of elements, such as collections, arrays, or I/O channels. It allows developers to perform functional-style operations on the elements, leveraging the power of lambda expressions to write more readable and concise code.

Key Features:

Functional Paradigm:

The Stream API promotes a functional programming paradigm by allowing developers to perform operations like filtering, mapping, and reducing on a collection in a declarative manner. This helps in writing more expressive and maintainable code.

Lazy Evaluation:

One of the key advantages of the Stream API is its support for lazy evaluation. This means that operations on a stream are only executed when needed. This can lead to improved performance, especially when working with large datasets.

Parallel Execution:

The Stream API seamlessly supports parallel processing, enabling developers to take advantage of multi-core processors. By invoking the parallel() method on a stream, operations can be automatically parallelized, potentially speeding up data processing tasks.

Stream Operations:

The Stream API provides a rich set of operations to manipulate data, such as filter(), map(), reduce(), collect(), and more. These operations can be combined to create complex data processing pipelines, making it easy to express business logic in a concise manner.

Follow the below GitLab repository for sample use cases and examples on Steam API.

https://gitlab.com/nc-public/java8-streamapi/-/blob/main/com/nc/service/EmployeeService.java?ref_type=heads

Use Cases:

1. Get all the employee names from the employee list - use of map

2. Sort the employee list based on age - use of sorted

3. Get all the phone no from the employee list (where phone is another list) - how to extract a list from list of list - flatmap

4. Group all the employee based on their department

5. Group all the employee based on their department and give count as result

6. Get maximum employee department

7. Find average salary for each department

8. Find max salary for each department

9. Get the second highest salaried employee details in each dept.

10. Filter the employee for each department has salary>3000000

Conclusion:

Java 8's Stream API has undoubtedly changed the way developers handle collections in Java. Its functional programming capabilities, lazy evaluation, and support for parallel processing make it a versatile tool for data manipulation tasks. As developers continue to embrace modern programming paradigms, the Stream API remains a valuable asset for writing clean, efficient, and expressive code in Java.