#Mongodb Query Optimization Techniques

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⚡️Famous Interview Problem: How did you reduce a Database Query time from 5 seconds → 50 milliseconds? 💬 Detailed PDF link in Bio OR comment "🔥" to get link ⸻ 1️⃣ Find the Slow Part (Profiling) 🕵️‍♂️ 𝐃𝐞𝐟𝐢𝐧𝐢𝐭𝐢𝐨𝐧 : Identify what’s actually slow — full scan, missing index, or heavy join. 𝐄𝐱𝐚𝐦𝐩𝐥𝐞 : Like checking why Instagram loads slowly: is it feed, stories or comments. ⸻ 2️⃣ Shard & Partition Data (Smart Split) 🗂️ 𝐃𝐞𝐟𝐢𝐧𝐢𝐭𝐢𝐨𝐧 : Split large tables by user or date so each query scans less data. 𝐄𝐱𝐚𝐦𝐩𝐥𝐞 : Instagram splits posts by month- your feed loads recent posts, not years of content. ⸻ 3️⃣ Add Indexes (Fast Search) 🔍 𝐃𝐞𝐟𝐢𝐧𝐢𝐭𝐢𝐨𝐧 : Jump directly to relevant rows instead of scanning everything. 𝐄𝐱𝐚𝐦𝐩𝐥𝐞 : Finding a user by username — the DB uses an index instead of checking every row. ⸻ 4️⃣ Cache Popular Data (Memory Boost) ⚡ 𝐃𝐞𝐟𝐢𝐧𝐢𝐭𝐢𝐨𝐧 : Store frequent results in memory for instant access. 𝐄𝐱𝐚𝐦𝐩𝐥𝐞 : Your Instagram home feed loads fast because it’s cached, not fetched every time. ⸻ 5️⃣ Precompute Heavy Work (Summary Tables) 🧮 𝐃𝐞𝐟𝐢𝐧𝐢𝐭𝐢𝐨𝐧 : Save ready-made results for analytics instead of recalculating each time. 𝐄𝐱𝐚𝐦𝐩𝐥𝐞 : Insta doesn’t count every view when you open Reels- it keeps running total ready. ⸻ 6️⃣ Reduce Payload / Select Only What You Need 📦 𝐃𝐞𝐟𝐢𝐧𝐢𝐭𝐢𝐨𝐧 : Fetch only the necessary columns or rows instead of everything. 𝐄𝐱𝐚𝐦𝐩𝐥𝐞 : Instagram loads images and captions first, then later fetches comments. ⸻ Refer PDF for more points 🔥 #SystemDesign #TechCareers #mission_compile #interview #google #TechReels #SoftwareEngineering #TechCommunity #API #Database #BackendDevelopment #InterviewPrep #InstaTech #EngineeringLife #LearnWithReels #coding #trending #dsa #leetcode #DatabaseOptimization [Database query Optimization, System Design Interview, Scale APIs, Cache, Async Processing, Database Optimization, Reduce Payload, External Service Handling, Fast Database, High Traffic Systems, Backend Engineering, Distributed Systems, Scalable Systems, Tech Reels, Learn System Design, Programming Tips, Software Engineering]

The more we move towards Search Everywhere Optimisation (Modern SEO) the more you need to think inside-out about your audience and design content around it. Here is one such framework I use. [SEO Framework, SEO, AEO, GEO, SEO Secret, SEO Template, Search Queries, LLM SEO, ChatGPT SEO, Perplexity SEO, Claude SEO, Keyword Research]

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Figuring the the reasons for slow queries in database requires a clear understanding of database internals !! Posting this video again so that more can understand this concept !! #tech_fundas #database #mysql #mongodb

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🔍 Curious about the journey behind a PostgreSQL query? Join us in our latest video as we unveil the intricate processes at work! - 📝 Parsing SQL into a structured format - 🧠 Smart planning with a cost-based optimizer - ⚙️ Execution with a powerful row-by-row engine - 🔒 Multi-Version Concurrency Control for seamless access - 🛠️ Decades of innovation shaping PostgreSQL's capabilities 👉 Don’t miss out—click to explore how PostgreSQL transforms your queries into results! #PostgreSQL #Databases #SQL #DataScience #TechExplained

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Optimize your SQL query performance! Did you know that adding ORDER BY can skyrocket your SQL query performance costs? ⚡️ What seems like a minor tweak can increase the cost from 1343 to a staggering 8132—6X higher! Don't let unnecessary sorting drain your resources. Always prioritize SQL query performance by sorting only when essential. Let's make SQL query performance smarter, not harder!