High Performance SQL Query on LeetCode Beats 80% of Submissions

🚀 Day 25/100 – SQL LeetCode Challenge ✅ Problem Solved: Customer Placing the Largest Number of Orders Today, I worked on an SQL problem where I needed to find the customer who placed the maximum number of orders from a given table. 💡 What I learned today: How to use GROUP BY to group data based on a column Using COUNT() to calculate total occurrences Sorting results using ORDER BY Limiting results with LIMIT to get the top record Understanding how to identify maximum values in SQL 🧠 Approach: I grouped the orders by customer_number, counted the number of orders for each customer, sorted them in descending order, and selected the top result. ✨ Key takeaway: Breaking problems into smaller steps makes SQL queries much easier to understand and solve. #Day25 #LeetCode #SQL #100DaysOfCode #LearningJourney

🗓️ SQL Challenge Day #28: Customers Who Bought All Products 🔹 Find customers who purchased every single product! 🛒 🔹 Problem:   Report customers who bought ALL products:   ✅ Handle duplicate purchases gracefully   ✅ Match total distinct products  🔹 Solution:  SELECT customer_id   FROM Customer   GROUP BY customer_id   HAVING COUNT(DISTINCT product_key) = (SELECT COUNT(*) FROM Product);  ✅ Result: Accepted  💡 Key Takeaway:   **COUNT(DISTINCT) + scalar subquery** is the gold standard for "bought all" problems!   ⚠️ Why DISTINCT? Customer might buy same product multiple times – we only care about unique products owned.   ✅ Subquery `(SELECT COUNT(*) FROM Product)` gives total product universe – clean and maintainable.  👇 Your turn:   Have you used this pattern for "completed all courses" or "visited all locations" type problems? Share your use case!  #SQL #LeetCode #DataEngineering #ProblemSolving #Coding #LearningInPublic #Database #DataAnalytics

📊 Recently, I took some time to revisit core SQL concepts while practicing query-based problems on LeetCode. It was a great way to strengthen fundamentals like: • JOINs and subqueries • GROUP BY & aggregation • Window functions • Writing optimized queries for real-world scenarios Along with problem-solving, I also revised important database concepts such as ACID properties and Normalization, which are essential for designing reliable and scalable systems. To keep everything in one place, I’ve created a concise PDF that includes: ✔ Common SQL queries (interview-focused) ✔ Clear explanation of ACID properties ✔ Normalization concepts with examples Sharing it here in case it helps others who are preparing for SQL interviews or brushing up their basics. #SQL #LeetCode #Database #BackendDevelopment #InterviewPreparation #LearningJourney

SQL Progress: Logic & CASE Statements! Today I solved another Medium challenge on LeetCode. This problem was a great lesson in how to calculate percentages and rates directly in SQL. What I learned today: 1. AVG with CASE WHEN: I learned that I can use AVG(CASE WHEN condition THEN 1.0 ELSE 0.0 END) to calculate a rate. It’s a very clear way. 2. Handling NULLs in Rates: By using a LEFT JOIN between the Signups and Confirmations tables, I ensured that users with no actions are still included, and the AVG function automatically treats them as 0 if they don't meet the "confirmed" criteria. 3. Precision with ROUND: Used ROUND(..., 2) to make sure the final confirmation rate is clean and meets the required format(0.00). I would love to learn from your experience: is ther another methods cleaner? قليل مستمر خير من كثير منقطع #SQL #DataEngineering #PostgreSQL #LeetCode #100DaysOfCode #DataAnalytics #ProblemSolving

Stop writing SQL "Inception." Use CTEs instead. 🛑📖 We’ve all been there: opening a query only to find a subquery, inside a subquery, inside another subquery. It’s hard to read, impossible to debug, and a nightmare for your future self. If you want to move from a "Junior" to a "Senior" SQL mindset, you need to master CTEs (Common Table Expressions). Why CTEs are a game-changer: Readability: They allow you to read code from top to bottom, like a story, rather than from the inside out. Reusability: You can reference the same CTE multiple times in one query. No more copy-pasting the same subquery logic! Debugging: You can test each "layer" of your data transformation individually before joining them all together. The Golden Rule: If your logic has more than two levels of nesting, it’s time for a WITH clause. #SQL #DataEngineering #Database #CodingTips #CleanCode #DataAnalytics #CareerGrowth

Solving the SQL 50 challenge on LeetCode has been an exciting and confidence-boosting journey. Each problem pushed me to think deeper, optimize queries, and strengthen my understanding of SQL concepts. From basic queries to advanced topics like joins, aggregations, subqueries, and window functions — this journey was truly enriching 💡 📘 What’s in my notes/document? A structured study guide covering: All 50 problems with solutions Clear explanations for each query Key SQL concepts like SELECT, JOINs, Aggregations, Window Functions, and more Practical patterns and best practices for real-world scenarios Once you get a solid grip on fundamentals, problems labeled medium or even hard start feeling like easy. It’s all about consistency and practice. #SQL #LeetCode #DataEngineering #LearningJourney #sql50

Day 18/100 of #100DaysOfCode 💻 Short query. Clear logic. Clean result. 🎯 Customer Placing the Largest Number of Orders:- Find the customer who placed the most orders from the Orders table. GROUP BY to count orders per customer → ORDER BY COUNT DESC to rank them → LIMIT 1 to grab the top one. Done. ✅ 💡 The real insight here - LIMIT 1 is one of those small but powerful tools. Instead of writing a subquery or CTE to find the max, just sort and slice. Cleaner and faster. Sometimes the best query is the shortest one. 🧩 Not every day is a Hard problem grind, some days you just stay consistent, show up, and keep the streak alive. That matters too. 😄 #SQL #100DaysOfCode #LearningInPublic #DataAnalytics #Consistency #DevJourney #LeetCode

💥Hello mates!! (New challenges) 📌Kicking off my SQL 50 journey on LeetCode to sharpen my SQL skills Day 01 starts today! SQL 50 LeetCode (01/50): Today's problem is #1757:"Recyclable and low Fat products"👨💻 This is an Easy-level problem that focuses on filtering data using SQL condition. I used the WHERE clause to solve this problem,and it successfully passed all the test case✅️ How my solution Works: ->I used the WHERE clause to filter the records based on the given condition. ->The AND Operator ensure that only products that are both low- fat and recyclable are selected. ->Since the problem doesn't require any joins or aggregations, the query stays simple,clean and easy to understand. -> This approach reflect real-world SQL queries practices used in Data Analytics and Data Engineering task. Database Used:MySQL See you all tomorrow with another exciting LeetCode problem! #LeetCode #SQL50 #SQLQuery #DataAnalytics #Database #Coding #SQLPractice #Coding

Most SQL developers use CTEs and Views interchangeably.They're not the same. Here's when to use each. 👇 I see this mistake constantly in code reviews. Someone wraps everything in a View when a CTE would do. Or uses a CTE when the logic is needed in 10 different queries. The difference is simpler than you think. ───────────────────────────── The one-line explanation: A View = a saved query that lives in your database permanently. A CTE = a temporary query that exists only inside one query. ───────────────────────────── Same logic. Different lifespan. VIEW: CREATE VIEW high_value_orders AS  SELECT customer_id, SUM(amount) AS total  FROM orders  GROUP BY customer_id  HAVING total > 1000; -- Anyone, anytime, any query: SELECT * FROM high_value_orders; CTE: WITH high_value_orders AS (  SELECT customer_id, SUM(amount) AS total  FROM orders  GROUP BY customer_id  HAVING total > 1000 ) SELECT * FROM high_value_orders; -- Gone after this query ends. ───────────────────────────── Use a VIEW when: → Multiple queries need the same logic → You want to share it across teams or apps → You need a security layer (hide raw columns) Use a CTE when: → You're breaking a complex query into readable steps → It's a one-off analysis — no need to clutter the DB → You need recursion (org charts, hierarchies, trees) ───────────────────────────── The real skill isn't knowing the syntax. It's knowing which tool fits the job and why. What's the most complex CTE or View you've ever written? Drop it below 👇 #SQL #DataEngineering #Analytics #DataScience #Programming #TechTips

🚀 Day 29 – 30 Days SQL LeetCode Challenge Almost at the finish line! 🏁 Today’s problem wraps up key concepts with a powerful real-world analytics scenario 📌 Today's Problem: Immediate Food Delivery II (LeetCode #1174) 🧠 Problem Statement: Find the percentage of customers whose first order was delivered immediately 👉 (order_date = customer_pref_delivery_date) 💡 Key SQL Concepts Used: • Subquery (first order per customer) • GROUP BY • Conditional aggregation • Percentage calculation • ROUND() 📚 What I Practiced Today: ✔ Finding first records per group ✔ Calculating percentages ✔ Combining subqueries + aggregation 🔥 This pattern is used in: • Customer behavior analysis • Conversion metrics • Business KPIs 🎯 Almost there! 1 Day to go… What I’ve mastered so far: ✅ Joins ✅ Subqueries ✅ Window Functions ✅ Aggregations ✅ Real-world SQL problems 📌 Final push tomorrow 🚀 🔗 GitHub Repository: https://lnkd.in/e8aV37dA #SQL #LeetCode #DataAnalytics #30DaysOfSQL #Consistency #LearningInPublic