Social Media Backend

@RestController
@RequestMapping("/social")
public class SocialController {
}

// 1. User Entity
import jakarta.persistence.*;

@Entity
class SocialUser {

  @Id
  @GeneratedValue(strategy = GenerationType.IDENTITY)
  private Long id;

  private String username;
  private String email;
}


// 2. Post Entity
@Entity
class Post {

  @Id
  @GeneratedValue(strategy = GenerationType.IDENTITY)
  private Long id;

  private Long userId;
  private String content;
  private String imageUrl;
  private Long likesCount;
}


// 3. Comment Entity
@Entity
class Comment {

  @Id
  @GeneratedValue(strategy = GenerationType.IDENTITY)
  private Long id;

  private Long postId;
  private Long userId;
  private String text;
}


// 4. Repository Layer
import org.springframework.data.jpa.repository.JpaRepository;

interface UserRepository extends JpaRepository<SocialUser, Long> {}
interface PostRepository extends JpaRepository<Post, Long> {}
interface CommentRepository extends JpaRepository<Comment, Long> {}


// 5. Service Layer
import org.springframework.stereotype.Service;
import java.util.List;

@Service
class SocialService {

  private final PostRepository postRepo;
  private final CommentRepository commentRepo;

  public SocialService(PostRepository postRepo, CommentRepository commentRepo) {
    this.postRepo = postRepo;
    this.commentRepo = commentRepo;
  }

  public Post createPost(Post post) {
    post.setLikesCount(0L);
    return postRepo.save(post);
  }

  public Comment addComment(Comment comment) {
    return commentRepo.save(comment);
  }

  public List<Post> getFeed() {
    return postRepo.findAll();
  }

  public Post likePost(Long postId) {
    Post post = postRepo.findById(postId).orElseThrow();
    post.setLikesCount(post.getLikesCount() + 1);
    return postRepo.save(post);
  }
}


// 6. Controller Layer
import org.springframework.web.bind.annotation.*;

@RestController
@RequestMapping("/social")
class SocialController {

  private final SocialService service;

  public SocialController(SocialService service) {
    this.service = service;
  }

  @PostMapping("/posts")
  public Post createPost(@RequestBody Post post) {
    return service.createPost(post);
  }

  @PostMapping("/comments")
  public Comment addComment(@RequestBody Comment comment) {
    return service.addComment(comment);
  }

  @GetMapping("/feed")
  public List<Post> getFeed() {
    return service.getFeed();
  }

  @PostMapping("/like/{id}")
  public Post likePost(@PathVariable Long id) {
    return service.likePost(id);
  }
}


// 7. application.properties
spring.datasource.url=jdbc:mysql://localhost:3306/social_media
spring.datasource.username=root
spring.datasource.password=root
spring.jpa.hibernate.ddl-auto=update


// Output:
// /social/posts -> Create post
// /social/comments -> Add comment
// /social/feed -> Get feed
// /social/like/{id} -> Like a post

• 1 System for managing posts and users.
• 2 Handles likes and comments.
• 3 Generates user feeds.
• 4 Built using Spring Boot backend.

• 1 User management
• 2 Post management
• 3 Comment system
• 4 Like system

• 1 User creates post
• 2 Other users interact
• 3 Likes and comments stored
• 4 Feed is generated

• 1 High scalability system
• 2 Real-world architecture learning
• 3 Microservices practice
• 4 Data-heavy application design

• 1 Used in Instagram-like applications.
• 2 Used in Facebook-style social platforms.
• 3 Used in community forums.
• 4 Used in content sharing apps.
• 5 SaaS products use Social Media Backend using Spring Boot in services, dashboards, background jobs, and API workflows.
• 6 ERP and banking systems apply Social Media Backend using Spring Boot with validation, logging, review, and rollback plans.
• 7 E-commerce and healthcare platforms use Social Media Backend using Spring Boot carefully because reliability and data correctness matter.

• 1 A Java program first evaluates the surrounding context, then applies the Social Media Backend using Spring Boot rules to the current data.
• 2 The important mental model is input, transformation, result, and failure path.
• 3 In production, the same flow usually sits inside a larger layer such as a controller, service, repository, job, or UI component.

• 1 Choose the simplest implementation first, then measure real workloads.
• 2 Watch for repeated work inside loops, unnecessary allocations, and slow I/O in hot paths.
• 3 Prefer clear data structures and stable APIs before micro-optimizing syntax.

• 1 Treat external input as untrusted until it is validated.
• 2 Avoid hardcoded secrets and never print sensitive values in examples or logs.
• 3 Use established libraries for authentication, encryption, parsing, and database access.

• 1 No pagination for feed.
• 2 Missing authentication system.
• 3 Poor scalability of like system.
• 4 No caching for feed generation.
• 5 Skipping the small working example before adding framework code.
• 6 Ignoring null, empty, duplicate, and boundary inputs.
• 7 Mixing business logic, input handling, and output formatting in one place.
• 8 Using broad error handling that hides the real failure.
• 9 Forgetting to test the behavior after refactoring.
• 10 Adding clever code that future maintainers will struggle to read.

• 1 Use pagination for feeds.
• 2 Implement JWT authentication.
• 3 Use Redis for caching likes and feeds.
• 4 Use microservices for scalability.
• 5 Start with clear requirements and one minimal working example.
• 6 Use meaningful names that explain business intent.
• 7 Keep examples small enough to debug line by line.
• 8 Validate input at every trust boundary.
• 9 Handle errors explicitly and preserve useful context.
• 10 Prefer simple control flow over deeply nested logic.
• 11 Separate domain logic from I/O and framework code.
• 12 Write tests for normal, boundary, and failure cases.
• 13 Review security assumptions before production use.
• 14 Measure performance before optimizing.
• 15 Document non-obvious decisions close to the code or in project notes.
• 16 Use official documentation when behavior is version-specific.
• 17 Keep dependencies current and remove unused code.
• 18 Avoid hardcoded secrets, credentials, and environment-specific paths.
• 19 Log operational events without exposing sensitive data.
• 20 Design examples so learners can safely modify and rerun them.

• 1 Beginner: rewrite the example with different names and values.
• 2 Intermediate: add validation and handle one expected failure case.
• 3 Advanced: place Social Media Backend using Spring Boot inside a small service-style design with tests.

• 1 Build a small Java console feature that demonstrates Social Media Backend using Spring Boot.
• 2 Accept input, process it with the concept, print a clear result, and handle invalid input.
• 3 Add a README note explaining the design choice and two edge cases you tested.

• 1 If the program does not compile, check spelling, imports, braces, and file/class names first.
• 2 If output is unexpected, print intermediate values and verify each branch of the logic.
• 3 If the design feels complex, reduce it to the smallest working example and add pieces back one at a time.

• 1 Practice Social Media Backend using Spring Boot with a second example from a business domain such as inventory, payroll, banking, or e-commerce.
• 2 Review related Java topics that cover data flow, error handling, testing, and clean design.
• 3 Compare your solution with official documentation and simplify anything you cannot explain clearly.