Engineering With Java: Digest #37
Curated and Hand Picked Best Java and Spring Blogs.
In this Engineering With Java newsletter edition, we have hand-picked 10 interesting Java and Spring articles worth reading. Topics include JSON data with JPA, New Java 23 Features, Java Streams, Annotation, Cloud Native Java, etc.
I hope enjoy the reading!
Modify JSON Data in Postgres and Hibernate 6
This article explores modifying JSON data in PostgreSQL using Hibernate, highlighting the advantages of the JSONB data type for efficient storage and querying.
It outlines essential Hibernate configurations needed to support JSONB and provides examples of updating and deleting JSON fields through Hibernate’s Criteria API and JPQL.
Additionally, it discusses practical use cases for manipulating JSON data in applications, offering a comprehensive guide for developers integrating JSON handling into their PostgreSQL and Hibernate projects.
The Future of Java: Exploring the New Features of Java 23
This article discusses the new features introduced in Java 23, emphasizing enhancements that improve developer productivity and application performance.
Key features include the introduction of pattern matching for switch statements, which simplifies code and reduces boilerplate, as well as record patterns that enhance data handling.
It highlights the new virtual threads that improve concurrency, making it easier to write scalable applications.
Additionally, it covers enhancements in project Loom for lightweight threading and project Panama for improved native interoperation. Overall, the article showcases how these advancements position Java for future development, aiming to streamline workflows and optimize performance.
Lombok vs. Plain Java: How Annotations Reduce Boilerplate Code
This article provides a comprehensive guide to Lombok annotations in Java, detailing how they simplify coding by reducing boilerplate code in Java classes.
It explains various commonly used annotations, such as
@Getter,@Setter,@ToString, and@EqualsAndHashCode, which automate the generation of getters, setters, and other utility methods.The article also discusses advanced features like
@Builder, which facilitates the builder pattern for object creation, and@Valuefor immutable classes.Additionally, it covers configuration options and best practices for using Lombok effectively, highlighting its benefits in improving code readability and maintainability while minimizing manual coding effort.
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Easily containerize Java applications with cloud native buildpacks
This article discusses how to simplify the containerization of Java applications using Cloud Native Buildpacks. It explains that Buildpacks automate the process of converting source code into runnable container images, eliminating the need for manual Dockerfile creation.
The article highlights the advantages of using Buildpacks, such as improved build speed, security, and compatibility with various cloud platforms.
It also outlines the process of using Buildpacks with popular Java frameworks, detailing steps for setting up the environment and deploying applications seamlessly.
Overall, the article emphasizes how Buildpacks enhance developer productivity and streamline the deployment of Java applications in cloud-native environments.
Mock @Value in Spring Boot Test
This article explores the benefits of using Cloud Native Buildpacks for containerizing Java applications, emphasizing their ability to automate the creation of runnable container images without the need for manual Dockerfiles.
It highlights key advantages such as increased build speed, enhanced security, and broad compatibility with various cloud platforms.
The piece details the process of integrating Buildpacks with popular Java frameworks, providing a clear guide for setting up the environment and deploying applications efficiently.
Ultimately, it underscores how Buildpacks can significantly improve developer productivity and facilitate seamless deployment in cloud-native contexts.
Effective Techniques for Optimizing Java Streams in Your Code
This article presents effective techniques for optimizing Java streams to enhance performance and efficiency in code. It highlights several strategies, such as minimizing the creation of intermediate objects, using parallel streams judiciously for performance gains, and leveraging lazy evaluation to improve resource management.
The author emphasizes the importance of choosing the right data structures and avoiding unnecessary computations by filtering and mapping streams efficiently.
Additionally, it discusses the impact of stream operations on performance and offers practical examples to illustrate these optimization techniques. Overall, the article serves as a valuable resource for developers looking to write more efficient and performant Java stream code.
10 Billion Integers Walk Into an Array
This article examines the challenges and solutions associated with handling large arrays of integers, specifically when dealing with a dataset containing 10 billion integers.
It discusses the limitations of traditional data structures and algorithms in terms of memory usage and performance.
The author explores techniques such as memory mapping and leveraging external storage to efficiently process large datasets without exhausting system resources.
Additionally, the article highlights the importance of algorithm optimization and provides practical insights into how to manage and manipulate such vast quantities of data effectively.
Overall, it serves as a guide for developers facing the complexities of big data in programming.
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Query JPA Repository With Single Table Inheritance Subtypes
This article explains the single table inheritance strategy in Java Persistence API (JPA), where multiple entity classes are mapped to a single database table.
It details how this approach simplifies the database schema by using a discriminator column to differentiate between the different entity types.
The author outlines the advantages of this method, such as improved query performance and ease of maintenance, while also discussing potential drawbacks, including issues with null values for unused fields.
It provides practical examples of implementing single table inheritance in JPA, including annotations and configurations needed to define the inheritance hierarchy effectively.
Overall, it serves as a useful resource for developers looking to implement inheritance in their JPA applications.
Straightforward Data Access with Jakarta Data and the Oracle Database
This article discusses the integration of Jakarta Data with Oracle Database to facilitate straightforward data access in Java applications. It highlights how Jakarta Data simplifies CRUD operations through a set of annotations and interfaces that streamline database interactions.
The author explains the advantages of using this approach, such as reducing boilerplate code and enhancing productivity for developers.
Additionally, the article covers practical examples of setting up and using Jakarta Data with Oracle Database, illustrating key features like automatic query generation and support for various data types.
Overall, it serves as a practical guide for developers looking to leverage Jakarta Data for efficient database management in their applications.
Optimizing Longest Palindrome Problem: Fixed-Size Array vs. HashMap
This article compares two approaches for optimizing the longest palindrome problem: using a fixed-size array versus a HashMap.
It discusses the efficiency of each method in terms of time and space complexity, highlighting that the fixed-size array offers constant space usage and faster access times, while the HashMap provides flexibility for handling a broader range of characters.
The author presents algorithmic implementations for both strategies, analyzing their performance in various scenarios.
Ultimately, the article concludes that while both methods are effective, the choice between them depends on specific use cases and constraints, such as the character set size and memory considerations.