java core

The Fork/Join Framework in Java, introduced in Java 7, is a powerful tool for parallel processing, designed to efficiently handle divide-and-conquer algorithms. It’s built on the ForkJoinPool, a specialized thread pool that optimizes task distribution across multiple CPU cores. The framework is particularly useful for recursive, computationally intensive tasks that can be split into smaller […]

Parallel processing with streams in Java leverages the parallelStream() method from the Stream API, introduced in Java 8, to distribute stream operations across multiple CPU cores. This can significantly improve performance for computationally intensive tasks, especially when processing large datasets. Below is a concise explanation and example of how to use parallel streams effectively. Key

The Optional class in Java, introduced in Java 8, is designed to address the problem of null references. It represents an object that may or may not contain a non-null value. This class encourages explicit handling of null values, reducing the likelihood of NullPointerExceptions and making code more robust and readable. The Optional class has

Numerical streams in Java, part of the Stream API introduced in Java 8, are specialized streams for handling primitive numeric types (int, long, double) to avoid the overhead of boxing/unboxing in regular object streams. They include IntStream, LongStream, and DoubleStream, found in the java.util.stream package. These streams are optimized for numerical computations and provide specific

In Java 8 Streams, a stream pipeline is a sequence of operations that process a stream of elements in a functional and declarative manner. It consists of a source, zero or more intermediate operations, and a terminal operation. Chaining operations refers to the process of combining multiple intermediate operations in a fluent API style to

In Java 8 Streams, lazy evaluation and short-circuiting operations are key features that optimize performance by processing only the necessary data. Below, I explain both concepts, their mechanisms, and examples. Lazy Evaluation Lazy evaluation means that intermediate operations in a stream pipeline are not executed until a terminal operation is invoked. Each intermediate operation (e.g.,

In Java 8 Streams, partitioning is a way to split a stream’s elements into two groups based on a predicate (a condition that returns true or false). This is achieved using the Collectors.partitioningBy collector, which groups elements into a Map<Boolean, List<T>>, where the keys are true (elements matching the predicate) and false (elements not matching

In Java, grouping operations with the Stream API are powerful for organizing data into categories, typically using the Collectors.groupingBy collector. These operations allow you to group stream elements based on a classification function, similar to SQL’s GROUP BY. The result is often a Map where keys are categories and values are collections of elements (or

The Collector interface in Java, part of the java.util.stream package, defines how elements of a Stream are collected into a final result, such as a List, Set, Map, or other data structure. It’s used with the Stream.collect() method and is highly flexible, allowing both predefined collectors (via Collectors class) and custom implementations. Below, I’ll explain