Writing Flyway migrations in Java for complex data transformations

#DAY1 #Day1 of SQL #100DaysOFCode | Java Full Stack Development SQL (Structured Query Language) commands are instructions used to interact with a database. They help in creating, modifying, retrieving, and managing data efficiently. 🔹 Types of SQL Commands 1️⃣ DDL (Data Definition Language) Used to define and manage the structure of database objects like tables and schemas. Commands: CREATE – Creates a new table or database. ALTER – Modifies the structure of a table. DROP – Deletes a table or database. TRUNCATE – Removes all data from a table but keeps its structure. RENAME – Changes the name of a table or column. 2️⃣ DML (Data Manipulation Language) Used to manipulate data stored in tables. Commands: INSERT – Adds new records to a table. UPDATE – Modifies existing data. DELETE – Removes data from a table. 3️⃣ DQL (Data Query Language) Used to retrieve data from the database. Command: SELECT – Fetches data from one or more tables. 4️⃣ DCL (Data Control Language) Used to control access and permissions in the database. Commands: GRANT – Gives privileges to users. REVOKE – Removes privileges from users. 5️⃣ TCL (Transaction Control Language) Used to manage transactions and ensure data consistency. Commands: COMMIT – Saves changes permanently. ROLLBACK – Undoes changes. SAVEPOINT – Sets a point in a transaction for partial rollback. In short: DDL → Defines structure DML → Manages data DQL → Queries data DCL → Controls permissions TCL → Manages transactions A big thanks to my mentor Gurugubelli Vijaya Kumar Sir and the 10000 Coders for constantly guiding me and helping me build a strong foundation in programming concepts. Trainer: Ganesh Usha Sri #JavaScript #SQL #Java #Coding #Programming #100DaysOfCode #Java #programming #CodeNewbie #LearnToCode #Developer #Tech #ProgrammingTips #JavaDeveloper #CodeDaily #DataStructures #CodingLife

#DAY1 #Day1 of SQL #100DaysOFCode | Java Full Stack Development SQL (Structured Query Language) commands are instructions used to interact with a database. They help in creating, modifying, retrieving, and managing data efficiently. 🔹 Types of SQL Commands 1️⃣ DDL (Data Definition Language) Used to define and manage the structure of database objects like tables and schemas. Commands: CREATE – Creates a new table or database. ALTER – Modifies the structure of a table. DROP – Deletes a table or database. TRUNCATE – Removes all data from a table but keeps its structure. RENAME – Changes the name of a table or column. 2️⃣ DML (Data Manipulation Language) Used to manipulate data stored in tables. Commands: INSERT – Adds new records to a table. UPDATE – Modifies existing data. DELETE – Removes data from a table. 3️⃣ DQL (Data Query Language) Used to retrieve data from the database. Command: SELECT – Fetches data from one or more tables. 4️⃣ DCL (Data Control Language) Used to control access and permissions in the database. Commands: GRANT – Gives privileges to users. REVOKE – Removes privileges from users. 5️⃣ TCL (Transaction Control Language) Used to manage transactions and ensure data consistency. Commands: COMMIT – Saves changes permanently. ROLLBACK – Undoes changes. SAVEPOINT – Sets a point in a transaction for partial rollback. In short: DDL → Defines structure DML → Manages data DQL → Queries data DCL → Controls permissions TCL → Manages transactions A big thanks to my mentor Gurugubelli Vijaya Kumar Sir and the 10000 Coders for constantly guiding me and helping me build a strong foundation in programming concepts. Trainer: Ganesh Usha Sri #JavaScript #SQL #Java #Coding #Programming #100DaysOfCode #Java #programming #CodeNewbie #LearnToCode #Developer #Tech #ProgrammingTips #JavaDeveloper #CodeDaily #DataStructures #CodingLife

💡 Spring Data JPA — Simplifying Database Operations in Java! 🚀 When I first started working with databases in Java, I found myself writing tons of boilerplate code just to perform simple CRUD operations. Then I discovered Spring Data JPA, and everything changed! ✨ So what is Spring Data JPA? It’s a part of the Spring Framework that lets you interact with databases using simple Java interfaces, no need to write complex SQL queries or manage connections manually. With just a few lines of code, you can: ✅ Save data ✅ Fetch records ✅ Update entities ✅ Delete entries For example 👇 public interface EmployeeRepository extends JpaRepository<Employee, Long> { List<Employee> findByDepartment(String department); } That’s it — Spring will generate all the implementation behind the scenes! 🔥 A few things that make it awesome: 🌱 Less boilerplate code ⚙️ Built-in CRUD operations 🔍 Supports custom queries 📄 Easy pagination & sorting 💾 Works smoothly with Spring Boot If you’re a beginner exploring Spring + Databases, start with Spring Data JPA — it’s a total game-changer! #SpringBoot #SpringDataJPA #Java #LearningJourney #BackendDevelopment #Developers #Coding

🧐 𝗝𝗣𝗔𝗥𝗲𝗽𝗼𝘀𝗶𝘁𝗼𝗿𝘆 𝘃𝘀 𝗖𝗥𝗨𝗗𝗥𝗲𝗽𝗼𝘀𝗶𝘁𝗼𝗿𝘆: 𝗪𝗵𝗮𝘁’𝘀 𝘁𝗵𝗲 𝗱𝗶𝗳𝗳𝗲𝗿𝗲𝗻𝗰𝗲? If you’ve been working with Spring Data JPA for a while, you’ve probably noticed that sometimes we extend CrudRepository, and other times, JpaRepository. But, what’s really the difference between them? 𝗟𝗲𝘁’𝘀 𝗴𝗼 𝘀𝘁𝗿𝗮𝗶𝗴𝗵𝘁 𝘁𝗼 𝘁𝗵𝗲 𝗽𝗼𝗶𝗻𝘁: Both are interfaces provided by Spring Data, and both help us perform basic operations like save(), findById(), delete(), etc. So, if CrudRepository already gives us all these basic CRUD operations, why would we need JpaRepository? The answer is: JpaRepository extends CrudRepository and adds more JPA-specific functionalities. Here’s what you get extra with JpaRepository: Methods like findAll(Sort sort) and findAll(Pageable pageable), super useful when dealing with pagination and sorting. Batch operations such as saveAll() or deleteAllInBatch(). Integration with JPA features, like flushing the persistence context (flush()) or deleting entities in batches, which can significantly improve performance. 💡 𝗧𝗵𝗲 𝗺𝗮𝗶𝗻 𝗶𝗱𝗲𝗮: CrudRepository → Basic CRUD operations. JpaRepository → Everything from CrudRepository + JPA extra features (pagination, sorting, batch operations, flush, etc). If you’re using Spring Data JPA, the default and most common choice is JpaRepository, because it’s a superset of the other two main repositories (CrudRepository and PagingAndSortingRepository). When we use JpaRepository, it’s not just about saving or finding data, it gives us extra control and performance with JPA. Let me know how you’ve used these extra features in your projects! #LearningJourney #CuriosityDriven #Java #developers #JavaDevelopers #Programming #SoftwareEngineering #CleanCode #TechTips #CodingJourney

Hibernate’s N+1 Problem — The Silent Performance Killer 😱 If your app feels slow even with small data — you might be a victim of the N+1 SELECT Problem in Hibernate 🐢 --- 🧩 What is the N+1 Problem? Imagine this 👇 You fetch all Departments (1 query), and for each department, Hibernate fires another query to get its Employees (N queries). ➡️ Total = N + 1 queries! 😬 List<Department> departments = session.createQuery("from Department", Department.class).list(); for (Department dept : departments) { System.out.println(dept.getEmployees().size()); } 💥 Result: 1 query for Departments + N queries for Employees = Performance Disaster! --- ⚡ The Fix — Use JOIN FETCH Tell Hibernate to fetch related data in a single query 🧠 List<Department> departments = session .createQuery("SELECT d FROM Department d JOIN FETCH d.employees", Department.class) .list(); ✅ Result: Only 1 query to fetch everything 🚀 --- 🧠 Pro Tips to Avoid N+1 Traps: 💡 Use @EntityGraph for flexible fetch strategies 💡 Avoid global EAGER fetching — it often backfires 💡 Enable show_sql or use p6spy to monitor queries --- 🔥 Remember: Small query issues today become big performance nightmares tomorrow. 💬 Have you ever battled the N+1 monster in production? How did you fix it? #Hibernate #SpringBoot #Java #JPA #BackendDevelopment #Performance #CodeOptimization #Microservices #Developers

Java Performance Tip 🚀 Dealing with large datasets in Spring Data JPA? Stop loading everything into memory! Use Stream-based queries with proper fetch size configuration for better memory management and performance. ✅ Old way: Loads entire result set into memory - potential OutOfMemoryError ✅ New way: Streams data in batches - efficient memory usage and better performance Key Benefits: 🎯 Prevents OutOfMemoryError with large datasets ⚡ Processes data in chunks (batch of 1000 records) 💾 Lower memory footprint 🔄 Works seamlessly with Java Streams API 📊 Perfect for data processing and reporting Pro Tips: Always close streams properly (use try-with-resources) Use @Transactional(readOnly = true) on service methods #Java #SpringBoot #SpringData #JPA #Hibernate #Performance #BestPractices #CleanCode #SoftwareDevelopment #BackendDevelopment #TechTips

I just published a concise breakdown of how Hibernate’s @DynamicUpdate behaves during update operations — what it actually optimizes, where it helps, and where it doesn’t. If you’re evaluating @DynamicUpdate for more efficient UPDATE statements, this overview will be useful. 👇 Medium link below. https://lnkd.in/dR_cw99T #springboot #hibernate #java #springdatajpa

Creating a full CRUD (Create, Read, Update, Delete) application in Java using Spring Boot involves several steps. Here’s a detailed guide to help you set up a simple CRUD application using Spring Boot, Spring Data JPA, and an in-memory H2 database. ### Step 1: Set Up Your Project 1. **Initialize a Spring Boot Project**:   * Use [Spring Initializr](https://start.spring.io/) to generate a new project.   * Select the following dependencies: Spring Web, Spring Data JPA, H2 Database. 2. **Download and Import the Project**:   * Once generated, download the project and import it into your IDE (IntelliJ IDEA, Eclipse, etc.). ### Step 2: Define the Model Create an entity class to represent the data model. ```java package com.example.demo.model; import javax.persistence.Entity; import javax.persistence.GeneratedValue; import javax.persistence.GenerationType; import javax.persistence.Id; @Entity public class Employee {       @Id   @GeneratedValue(strategy = GenerationType.IDENTITY)   private Long id;       private String name;   private String role;   // Constructors   public Employee() {}       public Employee(String name, String role) {     this.name = name;     this.role = role;   }   // Getters and Setters   public Long getId() {     return id;   }   public void setId(Long id) {     this.id = id;   }   public String getName() {     return name;   }   public void setName(String name) {     this.name = name;   }   public String getRole() {     return role;   }   public void setRole(String role) {     this.role = role;   } } ```

☕ Java Variables, Data Types & Type Conversion — Where Data Finds Its Identity In today’s Java session, I explored how data gets its personality — how it’s stored, labeled, and transformed behind the scenes. Every variable in Java is like giving a name to a piece of memory. The data type decides the size of that space and the kind of value it can hold — a number, a character, or a simple true/false. It’s structure meeting logic. 💡 Primitive Data Types — the core building blocks of Java: Integers: byte, short, int, long → for whole numbers in different ranges. Floating-Point: float, double → for decimal or fractional values. Character: char → holds a single symbol or letter. Boolean: boolean → represents truth values — true or false. 💡 Non-Primitive (Reference) Types — created by developers to manage more complex data. They include classes, arrays, and interfaces — storing references (memory addresses) instead of direct values. Their default value is null. Then comes the magic of Type Conversion — Java’s way of transforming one type into another: ➡️ Widening (Automatic) — Java promotes smaller types to larger ones, like int → double, safely and smoothly. ➡️ Narrowing (Explicit) — When we take control and manually shrink a type: double score = 89.7;   int finalScore = (int) score; // returns 89  What stood out to me is how beautifully Java blends safety, precision, and control — ensuring every value knows exactly what it is and where it belongs. 🚀 #Java #LearningJourney #Programming #DataTypes #TypeConversion #Coding #SoftwareDevelopment #DataScience

💡 Day 3 of my 𝗝𝗮𝘃𝗮 𝗕𝗮𝗰𝗸𝗲𝗻𝗱 𝗤𝘂𝗲𝘀𝘁𝗶𝗼𝗻 𝗼𝗳 𝘁𝗵𝗲 𝗗𝗮𝘆 𝘀𝗲𝗿𝗶𝗲𝘀: 🧠 Question: You’re working on a Spring Boot application that interacts with a relational database. You notice that for every request, multiple queries are executed for fetching related entities - causing performance issues. 👉 What is the N+1 query problem in JPA/Hibernate, and how can you avoid it? ✅ Answer: The N+1 query problem happens when Hibernate fires: 1 query to fetch parent records N queries to fetch child records for each parent This results in N+1 queries, hurting performance. To avoid it: > Use fetch join 𝘚𝘌𝘓𝘌𝘊𝘛 𝘶 𝘍𝘙𝘖𝘔 𝘜𝘴𝘦𝘳 𝘶 𝘑𝘖𝘐𝘕 𝘍𝘌𝘛𝘊𝘏 𝘶.𝘰𝘳𝘥𝘦𝘳𝘴 > Use @EntityGraph to pre-fetch relationships > Enable batch fetching 𝘩𝘪𝘣𝘦𝘳𝘯𝘢𝘵𝘦.𝘥𝘦𝘧𝘢𝘶𝘭𝘵_𝘣𝘢𝘵𝘤𝘩_𝘧𝘦𝘵𝘤𝘩_𝘴𝘪𝘻𝘦=20 > Always monitor SQL logs to detect hidden N+1 issues. ✅ Fetch joins, entity graphs, and batch fetching = faster DB access & fewer queries ⚡ See you tomorrow for Day 4 👋 #Java #SpringBoot #Hibernate #JPA #Performance #BackendDeveloper #ContinuousLearning #QuestionOfTheDay