🚀 Essential SQL Tips for Beginners! 🚀

Diving into the world of SQL? Here are some vital tips to kickstart your journey and enhance your SQL skills! 👩‍💻👨‍💻

🔹 Primary Key = Unique Key + Not Null constraint 🗝
🔹 Perform case-insensitive search using UPPER() function:
UPPER(customer_name) LIKE 'A%A'
🔹 LIKE operator is for string data types 🧵
🔹 COUNT(*), COUNT(1), COUNT(0) are all equivalent 🧮
🔹 Aggregate functions ignore NULL values 🚫
🔹 MIN, MAX, SUM, AVG, COUNT are for int data types; STRING_AGG is for string data types 📊
🔹 For row-level filtration use WHERE; for aggregate-level filtration use HAVING 🕵️‍♂️
🔹 UNION ALL includes duplicates; UNION excludes duplicates 🔄
🔹 Use UNION ALL if results won't have duplicates 🚫
🔹 Alias the subquery if using columns in the outer select query 📝
🔹 Subqueries can be used with NOT IN condition 🔄
🔹 CTEs are visually better than subqueries; performance-wise they're equivalent 📈
🔹 When joining two tables with one having only one value, use 1=1 for a CROSS JOIN 🤝
🔹 Window functions operate at the ROW level 🪟
🔹 RANK() vs DENSE_RANK(): RANK() skips rank if values are the same 🏅
🔹 EXISTS works on true/false conditions; if the query returns at least one value, the condition is TRUE ✅

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🚀 Few Ways to Optimize SQL Queries 🚀

SQL performance lagging? Here are some proven strategies to supercharge your SQL queries! 👇👇

🔍 Use Indexing:
Proper indexing of your database tables can turbocharge query performance by swiftly locating the necessary rows. 📊

⚙️ Optimize Joins:
Cut down the number of joins and choose the right join types (e.g., INNER JOIN, LEFT JOIN) for efficient data retrieval. 🔄

🚫 **Avoid SELECT ***:
Skip selecting all columns using SELECT *, and only fetch the columns you need to trim down unnecessary data transfer and processing. 📑

🎯 Use WHERE Clause Wisely:
Shrink the dataset size by filtering rows early with the WHERE clause before joining or aggregating data. 🧩

🔄 Avoid Subqueries:
Transform subqueries into JOINs or use Common Table Expressions (CTEs) for a performance boost. 📊

🔖 Limit the Use of DISTINCT:
Reduce the use of DISTINCT to prevent resource-heavy sorting and duplicate removal, especially for large datasets. 🚫

🔢 Optimize GROUP BY and ORDER BY:
Use GROUP BY and ORDER BY clauses thoughtfully, leveraging indexed columns to skip unnecessary sorting. 📑

📦 Consider Partitioning:
Divide large tables across multiple nodes to enhance query performance by minimizing I/O operations. 🚀

🔍 Monitor Query Performance:
Regularly check query performance using tools like query execution plans, database profiler, and performance monitoring tools to pinpoint and tackle bottlenecks. 🛠

Hope it helps! 🙂
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🔍 Is Java a Fully Object-Oriented Programming Language? 🤔
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📚 Arrays: All You Need to Know! 🚀

Dive into the world of arrays with these essential questions and programs! 🧠

1️⃣ Print Array even & odd numbers: Separate the odds from the evens! 🔢
2️⃣ Find Array length: Discover the size of your array! 📏
3️⃣ WAP to print array in reverse order: Flip the array! ↩️
4️⃣ WAP to copy one element to a second array: Duplicate with ease! 🔄
5️⃣ WAP to find an element present or not in an array: Search and discover! 🔍
6️⃣ WAP to find the average of a given array: Calculate the mean! 📈
7️⃣ WAP to print array elements in ASC or DESC order: Organize your array! 📊
8️⃣ WAP to find the biggest & smallest elements in an array: Identify the extremes! 📌
9️⃣ WAP to insert an element in an array: Add to your array! ➕
🔟 WAP to delete an element from an array: Remove unwanted elements! ❌
1️⃣1️⃣ WAP to print a 2D matrix: Visualize the matrix! 🎨
1️⃣2️⃣ WAP to add two 2D matrices: Combine matrices! ➕

📌 Bonus Questions:

WAP to find the sum of all elements in an array.
WAP to sort the array without using any built-in function.
WAP to find duplicate elements in an array.
Mastering arrays is essential for every programmer! 💡

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Difference between int.Parse() and int.TryParse()
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