Sai Gnanadeep’s Post

Solving the N+1 Problem in Nest.js + TypeORM + GraphQL Ever noticed your GraphQL queries getting slower as your data grows? You might be running into the N+1 problem. 😬 💡 What’s the N+1 problem? You fetch a list of records (say, posts), and for each post, you make another query to retrieve related data (such as comments). So instead of running 1 query, you end up running 1 + N queries 😬, and that’s where performance drops fast. ⚙️ How to fix it: ✅ Use leftJoinAndSelect or relations in TypeORM to fetch everything in a single query. ✅ Implement DataLoader in GraphQL to batch and cache requests. ✅ Avoid running queries inside loops in your resolvers or services. 🚀 The result: → Fewer queries → Faster APIs → Smoother GraphQL performance Mostly, I applied this optimization in my Nest.js + TypeORM projects, and the speed boost is incredible 🔥 Have you ever faced the N+1 issue in your backend? How did you handle it? #NestJS #TypeORM #GraphQL #BackendDevelopment #WebPerformance #WebDev #NodeJS

I reduced my endpoint duration from 6s to 1s using this simple change. I had a REST API in my NestJS backend that was doing multiple TypeORM queries inside a transaction. Each call looked harmless. Together, they cost 5 to 6 seconds per request. Instead of adding caching or scaling the server, I combined all those separate DB calls into one well-structured SQL query. The result? 6 seconds reduced to 1 second. It’s a reminder that: - ORMs like TypeORM are great for maintainability, but they abstract away performance details. - Complex business logic often deserves raw SQL for precision and speed. - Every extra DB round-trip is a hidden tax. If you’re leading a backend or reviewing PRs, keep an eye out for: - Repeated repository calls inside loops. - Multiple queries within a single request. - Missing query profiling during code reviews. Sometimes, the fastest optimization is not a new tool or some hidden recipe, it’s writing better SQL. Curious if others still prefer ORMs for heavy logic or switch to SQL when speed matters? #NestJS #TypeORM #BackendEngineering #FullStackDevelopment #SoftwareArchitecture #DatabaseOptimization #SQLPerformance #WebPerformance #CTO #TechLeadership #SeniorDevelopers

🚀 Introducing CodeCache — A Smarter Way to Save and Reuse Your Code Snippets! 💻 As developers, we often find ourselves digging through old projects, notes, or chats just to find that one useful code snippet — utility functions, API setups, UI snippets, or that perfect regex we don’t want to reinvent every time. CodeCache solves that problem — a modern, organized, and developer-friendly platform to save, search, and reuse code snippets effortlessly. 🧠 What is CodeCache? CodeCache is a Code Snippet Organizer built to help developers store, manage, and reuse snippets efficiently. No more digging through old projects or StackOverflow history — just open CodeCache, search, and copy. Because productivity isn’t just about writing new code — it’s about reusing your best work efficiently. ✨ Why You’ll Love It: 🔍 Instant Search & Filter: Quickly find snippets by title or tags. 💾 One-Click Save & Copy: Save your code securely and reuse it anywhere. 🏷 Organized Categorization: Tag your snippets for easier discovery. 💻 Edit or create snippets with the power of Monaco Editor — the same editor that powers VS Code! ☁️ Reliable cloud infrastructure powered by Aiven Cloud for database hosting and seamless scalability 🔒 Secure your workspace with JWT-based authentication and protected routes 📱 Smooth, responsive UI — optimized for both desktop and mobile devices for coding convenience on the go 🛠 Tech Stack: Frontend: React.js ⚛ + Vite ⚡ + TailwindCSS 🎨 Backend: Node.js + Express.js Database: MySQL + Sequelize ORM Authentication: JWT + Cookie-based sessions Code Editor: Monaco Editor ✍ Deployment: Frontend on Vercel | Backend on Render This project aims to simplify a developer’s workflow — because great ideas shouldn’t get lost in your editor’s history or local notes. 🌐 Live Demo: https://lnkd.in/d4xgsyBN 💻 GitHub Repository: https://lnkd.in/dz8PfA3N #WebDevelopment #FullStack #ReactJS #NodeJS #MySQL #DeveloperTools #CodingProductivity #CodeSnippet #Vite #TailwindCSS #CodeCache

📚 Day 09 of my #100DaysLogicChallenge Topic: Stack Data Structure in JavaScript 🧩 💡 Continuing my Data Structures journey (after Singly & Doubly Linked Lists), today I implemented one of the most fundamental and powerful structures — the Stack! A Stack follows the LIFO (Last In, First Out) principle — just like a pile of books 📚, where the last one placed is the first to be removed. 🧠 What I learned & implemented: Created a Stack class in JavaScript from scratch Implemented core methods: push(item) → Add element to the top pop() → Remove top element peek() → View top element without removing isEmpty() → Check if stack is empty size() → Return stack length Understood stack operations both conceptually and practically ⚙️ Use Cases of Stack: Undo/Redo functionality Browser back/forward navigation Expression evaluation (like postfix or parentheses validation) Function call management in recursion 📘 Connected DSA Topics So Far: 🧩 Day 02: Singly Linked List 🔁 Day 05: Doubly Linked List 🧱 Day 09: Stack in JavaScript 👉 Slowly building up a strong foundation in Data Structures with pure logic and no external libraries. 🎯 Key Takeaways: Stack is simple yet powerful for solving many real-world problems Reinforces logic behind memory management and recursive calls Helps in strengthening algorithmic thinking 🚀 Every new DSA concept adds another brick to the foundation of logic. Building strong fundamentals — one day, one structure at a time 💪 #100DaysLogicChallenge #JavaScript #LogicBuilding #DataStructures #Day09 #Stack #ProblemSolving #LearnByBuilding #CodingChallenge #WebDevelopment #DSA #ProgrammingFundamentals

What a ride! Just deployed my latest full-stack app, and honestly, the real win wasn't just the code, but the journey to get it live. 😅 This project was a deep dive into building a robust School Management Portal using Next.js and MySQL. It tested everything from frontend design to tricky server configurations. 🏆 My Top 3 Learning Takeaways: Backend is King (and Tricky!): Building Next.js API Routes and connecting them directly to MySQL (CRUD) was the core challenge. I learned firsthand the mechanics of server-side file upload logic and managing persistent data—no magic, just pure backend engineering. The DevOps Struggle is Real: Getting the code from local machine to Vercel was the biggest fight. I had to troubleshoot persistent Git/GitHub authentication issues and solve critical Vercel build failures caused by incorrect file types and dependencies. Lesson learned: Deployment is half the battle! Frontend Polish Matters: Used Tailwind CSS and React Hook Form to build a responsive, professional-looking dashboard (loved playing with that dark theme inspired by OpticOdds!). Form validation was key to making the UX smooth. The app is fully functional on localhost. The connection errors on the live demo are a good reminder of the difference between local MySQL and cloud-hosted data. Thanks for all the resources and guidance that helped me cross the finish line! 🔗 Check out the code (GitHub): https://lnkd.in/gyTpFX29 🔗 See the live UI (Vercel): https://lnkd.in/gqhSzAZ3 #FullStackDeveloper #NextJS #Backend #MySQL #Deployment #ProblemSolving #WebDevelopment

🚀 Mastering res.on() Events in Node.js – The Hidden Power Behind Streams! Ever wondered how you can listen to the lifecycle of an HTTP response in Node.js? That’s where res.on() comes in — it lets you react to key response events such as when data is being sent, finished, or when something goes wrong. Let’s break it down 👇 🧠 What is res.on()? In Node.js, every HTTP response object (res) is an EventEmitter, which means we can subscribe to events like: 'data' → when data chunks are being written 'end' → when all data is sent 'error' → when something goes wrong during transmission 'close' → when the connection closes (even abruptly) This gives developers fine-grained control over network responses — a must for performance monitoring, debugging, and logging. 💡 Why Use res.on()? ✅ Monitor outgoing responses — useful for logging and analytics. ✅ Handle premature disconnects — detect if clients drop off. ✅ Improve debugging — get detailed insights into request/response flow. ✅ Enhance performance tracking — measure when responses actually complete. 🎯 Key Takeaway res.on() turns your Node.js responses into observable events — empowering you to build robust, reliable, and production-grade servers with deeper control over network behavior. #NodeJS #BackendDevelopment #WebPerformance #FullStackDevelopment #JavaScript #LearningInPublic

📘 Day 03 — NestJS Learning Journey: Understanding GET, POST & @Body()! Today, I learned how GET and POST methods work in NestJS, and how to use the @Body() decorator to handle incoming data — along with testing it directly in Postman using JSON format. 🚀 💡 Here’s what I explored: 🔹 GET Method: Used to fetch or read data from the server. @Get() getUser() { return 'Fetching all users...'; } When I sent a GET request from Postman, the response was displayed directly — perfect for retrieving data. 🔹 POST Method: Used to send or create new data on the server. @Post() createUser(@Body() userData: any) { return `Received user: ${JSON.stringify(userData)}`; } In Postman, I selected POST, switched to the Body tab, chose raw → JSON, and sent data like this: { "name": "Zobaer", "email": "zobaer@example.com" } NestJS automatically read this JSON data using the @Body() decorator — which is how servers accept and process incoming data from clients. 🧠 This gave me a clear idea of how data travels between client and server, and how NestJS makes this process structured, simple, and clean. Next, I’ll explore PUT, DELETE, and route parameters in more depth to complete my CRUD understanding! 💻🔥 #NestJS #BackendDevelopment #NodeJS #WebDevelopment #TypeScript #LearningJourney #CodeCraftZobaer

🚀 REST vs GraphQL — A Small Change, Big Impact While working with a REST-based system in NestJS, I noticed something interesting: The UI felt slow — not because of the database, but because of overfetching. REST endpoints were sending everything — even when the client needed just a few fields. The result? Heavy payloads, slower renders, and wasted bandwidth. Then I added GraphQL. No database changes. No ORM overhaul. Just a smarter way for the frontend to say, “Give me only what I need.” ✅ Lighter responses ✅ Fewer network calls ✅ Faster perception of speed GraphQL doesn’t make your queries faster — it makes data delivery more efficient. Sometimes, optimization isn’t about rewriting logic — it’s about asking smarter questions to your data. #GraphQL #NestJS #WebDevelopment #Performance #Engineering #APIDesign

When you read a file, stream a video, or send data over the network in Node.js — have you ever wondered how raw binary data gets handled so smoothly? 🧐 Let’s talk about the unsung hero behind it all — Buffer in Node.js! ⚙️ Imagine this 👇 When your computer processes files (text, images, videos), it works with 0s and 1s — pure binary. Now, JavaScript was originally built to handle text data, not raw binaries. So… how does Node.js deal with binary data? That’s where Buffer comes in — a temporary storage area for binary data. 💡 Think of it as a “holding zone” for raw bytes when Node.js talks to the file system or network. Why is Buffer so important? JavaScript strings are UTF-16 encoded — not ideal for binary data. Node.js frequently handles files, images, or network packets — all of which are binary. Buffer bridges that gap efficiently! Key Features: Fixed size (once created, size can’t change) Stores raw binary data (not UTF-8 text) Memory is allocated outside the V8 heap Global class — no need to import Super useful in: File System (fs) Networking (TCP, UDP, WebSockets) Streams (working with data chunks) Buffer vs V8 Memory 🧠 Normally, JavaScript stores data like objects and strings in V8-managed memory, which has limits (~1.4GB) and relies on garbage collection. Buffers, on the other hand, use memory directly from the OS, outside the V8 engine. This means: No garbage collection overhead Can handle larger files (3GB+) Much faster binary performance In short — Buffers = raw power for raw data. ⚡ Next time you read a file or send a network request in Node.js, remember — Buffer is silently doing the heavy lifting behind the scenes 💪 Follow me for more such content https://lnkd.in/dFzTW9wt #backend #webdevelopment #node.js #Javascript #fullstack #Mern

🔥 Day 44 / #100Daysfrontendchallenge — JSON Tree Visualization Today’s challenge was all about turning raw JSON data into a beautiful, structured visual tree — just like you see in advanced developer tools! 💡 Goal: Build an interactive JSON Tree Visualizer where you can paste any JSON data, and it automatically displays a connected hierarchy of nodes — parents, children, arrays, and values — all structured visually. What I Built: A recursive React component system (Root → Parent → Node) Automatic detection for Objects and Arrays Hierarchical rendering with clear parent-child depth Dynamic color coding for nodes and values Smooth visualization layout using flex and spacing logic ⚙️ Tech Used: React + TailwindCSS (no external libraries — built fully from scratch 🚀) 🧩 Next Steps: Add search functionality that finds and auto-scrolls to any key/value in the tree Draw connector lines between nodes for even better visualization Add zoom-in/out transitions for large JSON structures 🎯 Key Learning: Recursion is the heart of tree visualizations — once you understand how to render components recursively, you can create anything from file explorers to org charts to visual data mappers. 💬 “Visualization isn’t about colors — it’s about clarity.” Super fun challenge, and probably one of the most visually satisfying builds so far in this 100-day journey! Source code : https://lnkd.in/gKQnyF5T #100DaysOfCode #FrontendDevelopment #ReactJS #WebDevelopment #LearningInPublic #JSON #Visualization #JavaScript