How Indexing Improves Query Performance

Don’t index just filters. Index what you need. If you index only your WHERE columns, you leave performance on the table. One of the most effective yet overlooked techniques is Covering Indexes.  Unlike standard indexes that only help filter rows, covering indexes include all columns required for a query. It will reduce query execution time by eliminating the need to access the main table. 𝗪𝗵𝘆 𝗖𝗼𝘃𝗲𝗿𝗶𝗻𝗴 𝗜𝗻𝗱𝗲𝘅𝗲𝘀? • By including all required columns, the query can be resolved entirely from the index, avoiding table lookups. • Can speed up join queries by reducing access to the base table. 𝗖𝗼𝗹𝘂𝗺𝗻𝘀 𝘁𝗼 𝗜𝗻𝗰𝗹𝘂𝗱𝗲: • WHERE: Filters rows. • SELECT: Data to retrieve. • ORDER BY: Sorting columns. 𝗦𝘁𝗲𝗽𝘀 𝘁𝗼 𝗖𝗿𝗲𝗮𝘁𝗲 𝗖𝗼𝘃𝗲𝗿𝗶𝗻𝗴 𝗜𝗻𝗱𝗲𝘅𝗲𝘀 1- Use execution plans to identify queries that perform frequent table lookups. 2- Focus on columns in WHERE, SELECT, and ORDER BY. 3- Don’t create multiple indexes with overlapping columns unnecessarily. 𝗖𝗼𝘃𝗲𝗿𝗶𝗻𝗴 𝗜𝗻𝗱𝗲𝘅𝗲𝘀 𝗮𝗿𝗲 𝗻𝗼𝘁 𝗳𝗼𝗿 𝗳𝗿𝗲𝗲. • Each insert, update, or delete operation must update the index, which can slow down write-heavy workloads. • Covering indexes consumes more disk space. Covering indexes are a powerful tool for database performance, especially for read-heavy applications.  While they can increase write costs, the trade-off is often worth it for the dramatic speedups in query performance.  Every table lookup wastes precious time. Fix it!

𝐏𝐨𝐰𝐞𝐫 𝐨𝐟 𝐒𝐐𝐋 𝐈𝐧𝐝𝐞𝐱𝐢𝐧𝐠: 𝐓𝐡𝐞 𝐊𝐞𝐲 𝐭𝐨 𝐅𝐚𝐬𝐭𝐞𝐫 𝐐𝐮𝐞𝐫𝐢𝐞𝐬! Imagine you’re reading a book with 120 chapters. Now, if someone asks you to jump to Chapter 17 without an index, you’d have to flip through each page until you find it. 𝐁𝐮𝐭 𝐰𝐢𝐭𝐡 𝐚𝐧 𝐢𝐧𝐝𝐞𝐱, 𝐲𝐨𝐮 𝐜𝐚𝐧 𝐢𝐧𝐬𝐭𝐚𝐧𝐭𝐥𝐲 𝐣𝐮𝐦𝐩 𝐭𝐨 𝐭𝐡𝐞 𝐫𝐢𝐠𝐡𝐭 𝐩𝐚𝐠𝐞. 📖✨ This is exactly how indexing in SQL works. Without an index, finding specific data in a large table can be like searching for a needle in a haystack. But with an index, the database knows exactly where to look, making data retrieval much faster. ⚡ Take this simple example: 𝐒𝐄𝐋𝐄𝐂𝐓 * 𝐅𝐑𝐎𝐌 𝐎𝐑𝐃𝐄𝐑_𝐓𝐁 𝐖𝐇𝐄𝐑𝐄 𝐎𝐃𝐄𝐑_𝐈𝐃=7077; Without an index, the database 𝐩𝐞𝐫𝐟𝐨𝐫𝐦𝐬 𝐚 𝐟𝐮𝐥𝐥 𝐭𝐚𝐛𝐥𝐞 𝐬𝐜𝐚𝐧, checking each row until it finds the match. If your table has millions of records, this can be painfully slow! 🐢 But by adding an index, your query can go from seconds to milliseconds! ⚡💨 𝐀𝐋𝐓𝐄𝐑 𝐓𝐀𝐁𝐋𝐄 𝐎𝐑𝐃𝐄𝐑_𝐓𝐁 𝐀𝐃𝐃 𝐈𝐍𝐃𝐄𝐗 𝐎𝐑𝐃𝐄𝐑𝐈𝐃𝐈𝐍𝐃𝐄𝐗(𝐎𝐑𝐃𝐄𝐑𝐈𝐃); 𝐒𝐄𝐋𝐄𝐂𝐓 * 𝐅𝐑𝐎𝐌 𝐎𝐑𝐃𝐄𝐑_𝐓𝐁 𝐖𝐇𝐄𝐑𝐄 𝐎𝐑𝐃𝐄𝐑𝐈𝐃 = 7077; Think of it like sorting a mixed basket of red and white balls. If you separate them first, finding the red ball becomes much quicker! 🎯 𝐀𝐝𝐝𝐢𝐧𝐠 𝐚𝐧 𝐢𝐧𝐝𝐞𝐱 𝐜𝐚𝐧 𝐝𝐫𝐚𝐬𝐭𝐢𝐜𝐚𝐥𝐥𝐲 𝐢𝐦𝐩𝐫𝐨𝐯𝐞 𝐲𝐨𝐮𝐫 𝐪𝐮𝐞𝐫𝐲 𝐩𝐞𝐫𝐟𝐨𝐫𝐦𝐚𝐧𝐜𝐞, 𝐦𝐚𝐤𝐢𝐧𝐠 𝐲𝐨𝐮𝐫 𝐒𝐐𝐋 𝐜𝐨𝐝𝐞 𝐦𝐨𝐫𝐞 𝐞𝐟𝐟𝐢𝐜𝐢𝐞𝐧𝐭 𝐚𝐧𝐝 𝐟𝐚𝐬𝐭𝐞𝐫. 𝐓𝐲𝐩𝐞 𝐨𝐟 𝐈𝐧𝐝𝐞𝐱𝐢𝐧𝐠:- 𝐂𝐥𝐮𝐬𝐭𝐞𝐫𝐞𝐝 𝐈𝐧𝐝𝐞𝐱: It determines the physical order of data in a table, typically created on the primary key, like ORDER ID. 𝐍𝐨𝐧-𝐂𝐥𝐮𝐬𝐭𝐞𝐫𝐞𝐝 𝐈𝐧𝐝𝐞𝐱: It creates a separate structure that improves query performance by storing values of the indexed columns along with pointers to the actual data rows. 𝐁𝐨𝐭𝐭𝐨𝐦 𝐥𝐢𝐧𝐞: Indexing is a must for anyone looking to optimize their SQL queries and make their data work for them. 🛠️ #SQL #Indexing #DatabaseOptimization #TechTips