Java Backend Development: Day 19 - Transactions & PreparedStatement

Late last year, I faced a scenario I hadn't encountered before: the need to process a 600,000-row Excel file with 18 columns of data and complex dependencies. My first attempt resulted in an OutOfMemoryError. The sheer volume combined with the business logic just crushed the heap. Instead of simply asking for more server RAM, I decided to dig deeper and look for modern ways to utilize 100% of Java's capabilities. The solution involved moving away from framework defaults and optimizing three critical areas: 1. Reading: I switched from loading the whole DOM to a Streaming approach. Keeping only a sliding window of rows in memory drastically reduced the footprint. 2. Validation: I replaced thousands of database queries (the N+1 problem) with an in-memory entity cache (Maps), validating business rules locally. 3. E: I swapped JPA's saveAll for JDBC Batch. Inserting data in chunks without the overhead of Hibernate's dirty checking made the process fly. It was a great reminder that sometimes the solution isn't about infrastructure, but solid software engineering. #Java #Spring #Backend #Performance #SoftwareEngineering

🚀 Day 21 | Java Backend Development – 100 Days Challenge 📚 Topics Covered Today: JPA EntityManager – in-depth understanding EntityManagerFactory configuration Persistence Context management Spring Boot + Database integration Three-layer architecture: Controller → Service → Repository JPA Repository interface Database configuration using application.properties Built REST APIs with database backend Refactored in-memory application to database-driven architecture Today was a big milestone — transforming simple apps into real, scalable backend systems backed by a database. This is where backend development starts to feel production-ready. From console → REST → Database 🚀 On to Day 22 💪 #SpringBoot #JPA #Hibernate #BackendDevelopment #Java #100DaysOfCode #Day21 #LearningInPublic #SoftwareEngineering

Day-8 💻 Advance Java Practice – #JDBC #Transactions (Commit & Rollback) Today I learned how to handle database transactions in JDBC using Java. Understanding #commit and #rollback helped me see how real-world applications maintain data consistency and avoid partial updates. 🔹 Connected Java application with MySQL database 🔹 Disabled auto-commit using setAutoCommit(false) 🔹 Executed multiple insert queries 🔹 Used commit() to save all changes together 🔹 Used rollback() in catch block for error handling 🔹 Ensured data integrity during transactions 🔹 Closed database connection properly This practice showed me how important transaction management is when performing multiple database operations. Slowly building strong Java backend and database handling skills step by step 🚀 #Java #AdvanceJava #JDBC #Transactions #CommitRollback #MySQL #BackendDevelopment #FullStackDeveloper #LearningJourney 10000 Coders #Trainer:-Gurugubelli Vijaya Kumar

🚀 Published on Maven Central! 🎉 I’m excited to share that my open-source Java library — pg-query-builder — is now officially available on Maven Central! 📦 Maven Artifact: https://lnkd.in/g6SWKHDV pg-query-builder is a lightweight, PostgreSQL-focused dynamic SQL query builder tailored for reactive applications and flexible backend services. ✨ Key Features Build dynamic SQL queries with ease Designed for PostgreSQL database workflows Clean and intuitive API for filtering, sorting & pagination Ready to integrate in Spring WebFlux / R2DBC environments Whether you’re building REST APIs, microservices, or reactive data layers — this utility simplifies custom query construction and enhances code readability. 🔗 Check it out on Maven Central: https://lnkd.in/g6SWKHDV If you try it out, I’d love to hear your feedback! 🙌 #Java #OpenSource #MavenCentral #SpringWebFlux #PostgreSQL #R2DBC #SoftwareDevelopment

📘 Spring Boot Layered Architecture – Simple Explanation I’m sharing a simple diagram that explains the Spring Boot layered architecture, which is widely used in backend Java applications. The application is structured into clear layers: -Controller Layer: receives HTTP requests (GET, POST, PUT, DELETE) and returns JSON responses. -Service Layer: contains the business logic and connects the controller with the data layer. -Repository Layer: handles data access using JPA and communicates with the database. -Entity Layer: represents database tables as Java classes. -Database: stores application data (MySQL / PostgreSQL). This architecture helps create clean, well-organized, and maintainable code, and makes applications easier to scale and test. #SpringBoot #Java #BackendDevelopment #SoftwareArchitecture #RESTAPI #Learning #Students

📘 #Day107 of My Java Full Stack Journey Today I learned how to read data from the database using JDBC and how to process it using ResultSet. ✨ 𝐖𝐡𝐚𝐭 𝐢𝐬 𝐚 𝐑𝐞𝐚𝐝 𝐎𝐩𝐞𝐫𝐚𝐭𝐢𝐨𝐧? A read operation is used to fetch data from the database, using a SELECT query. 𝑬𝒙: SELECT * FROM student; In JDBC, read operations are executed using: 👉executeQuery() 🔹𝐔𝐬𝐢𝐧𝐠 𝐏𝐫𝐞𝐩𝐚𝐫𝐞𝐝𝐒𝐭𝐚𝐭𝐞𝐦𝐞𝐧𝐭 𝐟𝐨𝐫 𝐑𝐞𝐚𝐝 𝐎𝐩𝐞𝐫𝐚𝐭𝐢𝐨𝐧: I used PreparedStatement to execute the SELECT query safely and efficiently. 𝑬𝒙: PreparedStatement ps = con.prepareStatement(query); ResultSet rs = ps.executeQuery(); ➜ PreparedStatement executes the query ➜ executeQuery() returns the ResultSet ➜ ResultSet contains the data returned from the database 🔹 𝐏𝐫𝐨𝐜𝐞𝐬𝐬𝐢𝐧𝐠 𝐑𝐞𝐬𝐮𝐥𝐭𝐒𝐞𝐭: ResultSet acts like a cursor that allows us to read data row by row. Using ResultSet: ➜ Move through rows using next() ➜ Retrieve values using getInt(), getString(), etc. ➜ Column indexing starts from 1 📌 𝙆𝙚𝙮 𝙇𝙚𝙖𝙧𝙣𝙞𝙣𝙜𝙨: ▪ executeQuery() is used for read operations ▪ ResultSet stores data returned from the database ▪ ResultSet allows row-by-row processing ▪ Must close ResultSet after usage Gurugubelli Vijaya Kumar | 10000 Coders #Java #JDBC #ResultSet #AdvancedJava #BackendDevelopment #JavaLearning

Your Service layer is too fat. 🍔 I used to treat my Java classes (Entities) as "Data Containers." They were just bags of Getters and Setters. All the logic lived in the Service layer. 1. "Check if order is paid." 2. "Change status to cancelled." 3. "Update the timestamp." This is called an Anemic Domain Model. And it makes your Services massive, messy, and hard to test. ❌ The Bad Way (Left Code): The Service acts like a "Puppet Master," pulling strings on the Entity. The Entity is dumb. It doesn't protect its own data. ✅ The Senior Way (Right Code): Rich Domain Model. Move the logic inside the Entity. order.cancel() Now, the Order class is responsible for its own rules: 1. "I cannot be cancelled if I haven't been paid." 2. "If I am cancelled, I must set a timestamp." Your Service layer becomes just a thin wrapper: order.cancel(); repository.save(order); Clean. Testable. Object-Oriented. Are your entities "Smart Objects" or just "Data Bags"? 👇 #SoftwareArchitecture #JavaDevelopers #Java #SpringBoot #CleanCode #ObjectOrientedProgramming #DomainDrivenDesign #DevTips #ProgrammingThoughts

📊 Leveling Up My Backend Game with SQL! As a Java Full-Stack Developer, mastering SQL is crucial for building powerful applications! Here are the core concepts I'm focusing on: ✨ SQL Syntax - Crafting clean and effective queries ✨ Tables - Designing and managing database schemas ✨ SELECT Statements - Retrieving data efficiently for APIs ✨ JOINs - Working with relational data across multiple tables ✨ Filtering Data - Implementing business logic with WHERE and HAVING ✨ Indexes - Enhancing application performance through query optimization From managing user data to handling complex transactions, SQL is essential for every full-stack developer. Combining this with Java frameworks like Spring and Hibernate opens up endless possibilities for creating scalable, data-driven applications! 🚀💡 #JavaFullStack #SQL #DatabaseManagement #BackendDevelopment #FullStackDeveloper #JavaDeveloper #TechGrowth #Programming #Fortuneit

Habit #3: Repositories Don’t Leak (Domain Integrity) As engineers, we often trade long-term stability for short-term speed. One of the most common traps? Letting your Database Entities escape the Repository layer. The Problem: Passing Hibernate/JPA entities all the way to the Controller. It’s fast to code, but it couples your API to your DB schema. If the DB changes, the API breaks. Plus, the dreaded LazyInitializationException. The Habit: Keep your schema private. The Repository should map entities to clean Domain Models or DTOs before they reach the Service layer. The Benefits: ✅ Decoupling: Change your DB without affecting your API contract. ✅ Security: No accidental "Mass Assignment" of internal fields. ✅ Clarity: Your Service layer works with business logic, not DB rows. What’s your take: Do you map to DTOs every time, or is it "over-engineering" for you? Let's discuss! 👇 #Java #Backend #CleanCode #SoftwareArchitecture #BestPractices #LetsCodeJava

💡 𝐓𝐡𝐞 "𝐅𝐮𝐥𝐥 𝐒𝐭𝐚𝐜𝐤" 𝐌𝐲𝐭𝐡: 𝐖𝐡𝐲 𝐈𝐧𝐭𝐞𝐫𝐯𝐢𝐞𝐰𝐬 𝐚𝐫𝐞 𝐭𝐡𝐞 𝐁𝐞𝐬𝐭 𝐑𝐞𝐚𝐥𝐢𝐭𝐲 𝐂𝐡𝐞𝐜𝐤 📉 I just wrapped up a technical deep-dive with the team at 𝐎𝐫𝐚𝐜𝐥𝐞, and it was a solid reminder that software engineering is an endless ocean 🌊. We had a brilliant discussion on 𝐌𝐢𝐝𝐝𝐥𝐞𝐰𝐚𝐫𝐞 𝐀𝐫𝐜𝐡𝐢𝐭𝐞𝐜𝐭𝐮𝐫𝐞🏗️ and 𝐉𝐚𝐯𝐚 𝐂𝐨𝐧𝐜𝐮𝐫𝐫𝐞𝐧𝐜𝐲☕, where I felt right at home sharing my experience with high-performance banking frameworks (shoutout to 𝐋𝐢𝐠𝐡𝐭-4𝐉 ⚡). But it also highlighted an area for my weekend reading list: 𝐓𝐡𝐞 𝐃𝐚𝐭𝐚𝐛𝐚𝐬𝐞 𝐋𝐚𝐲𝐞𝐫💾. As modern developers, we often rely so heavily on ORMs (like Hibernate 🛡️) that we sometimes let our raw SQL muscles get a little rusty ⚙️. Today was a good nudge to get back to basics: 𝐀𝐂𝐈𝐃 𝐩𝐫𝐨𝐩𝐞𝐫𝐭𝐢𝐞𝐬, 𝐉𝐨𝐢𝐧 𝐬𝐭𝐫𝐚𝐭𝐞𝐠𝐢𝐞𝐬, 𝐚𝐧𝐝 𝐐𝐮𝐞𝐫𝐲 𝐎𝐩𝐭𝐢𝐦𝐢𝐳𝐚𝐭𝐢𝐨𝐧🔍. 𝐀𝐥𝐰𝐚𝐲𝐬 𝐥𝐞𝐚𝐫𝐧𝐢𝐧𝐠, 𝐚𝐥𝐰𝐚𝐲𝐬 𝐝𝐞𝐛𝐮𝐠𝐠𝐢𝐧𝐠. 𝐎𝐧 𝐭𝐨 𝐭𝐡𝐞 𝐧𝐞𝐱𝐭 𝐜𝐨𝐦𝐩𝐢𝐥𝐞! 💻🚀 #InterviewExperience #JavaDeveloper #SystemDesign #Oracle #SQL #ContinuousLearning #GrowthMindset #BackendEngineering