Week #5: 100 Days of SQL Optimisation

Tips for maximising SQL query efficiency

Think of SQL optimisation as planning a holiday. A last-minute booking might secure a flight, but it could leave you with inconvenient layovers and missed experiences. By carefully organising your trip, prioritising key destinations, and booking accommodations wisely, you simplify your journey, predicting potential delays and maximising enjoyment. A well-optimised query is like a perfectly planned trip, smooth, efficient, and rewarding. ✈️🌍

Generated using DALL-E by ChatGPT

This week, we worked on a mix of well-known interview questions and real-world datasets. Each example focuses on different methods to improve performance in various scenarios.

Here’s a quick look at what we covered in this week’s optimisation journey:

• Day 29: Optimising a query using the Electric Vehicle Population Data by DATA.GOV¹.

• Day 30: Solved the Teams Power Users Microsoft SQL interview question from DataLemur², with 1M randomly generated entries.

• Day 31: Solved the Patient Support Analysis (Part 1) UnitedHealth SQL interview question from DataLemur³, with 500k randomly generated entries.

• Day 32: Solved the Supercloud Customer Microsoft SQL interview question from DataLemur⁴, with 100k randomly generated entries.

• Day 33: Optimising a query using the IMDb's Non-Commercial Datasets⁵.

• Day 34: Solved the Product Sales Analysis III SQL problem from LeetCode⁶ using a randomly generated 1M entry.

• Day 35: Solved the Salaries Differences LinkedIn and Dropbox SQL question from stratascratch⁷, with 5M randomly generated entries.

In this post, we dive into week five of our 100-day SQL optimisation journey.

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Day 29: Partial Index for Updates