LeetCode-SQL-PySpark-Solutions

This repository contains my solutions to the top 50 LeetCode SQL challenges implemented using Apache Spark DataFrame (PySpark) and Spark SQL.

I have used the provided pandas schema from the website and converted it into a Spark DataFrame before solving them. I employed Jupyter Notebooks for easy readability.

Each Jupyter Notebook contains both the problem statement and my solution. To practice, clone the repo and clear out the shells containing the solutions and write your own PySpark or Spark SQL code to solve the challenge.

Table of Contents

Select

1. Recyclable and Low Fat Products
2. Find Customer Referee
3. Big Countries
4. Article Views I
5. Invalid Tweets

Basic Joins

6. Replace Employee ID With The Unique Identifier
7. Product Sales Analysis I
8. Customer Who Visited but Did Not Make Any Transactions
9. Rising Temperature
10. Average Time of Process per Machine
11. Employee Bonus
12. Students and Examinations
13. Managers with at Least 5 Direct Reports
14. Confirmation Rate

Basic Aggregate Functions

15. Not Boring Movies
16. Average Selling Price
17. Project Employees I
18. Percentage of Users Attended a Contest
19. Queries Quality and Percentage
20. Monthly Transactions I
21. Immediate Food Delivery II
22. Game Play Analysis IV

Sorting and Grouping

23. Number of Unique Subjects Taught by Each Teacher
24. User Activity for the Past 30 Days I
25. Product Sales Analysis III
26. Classes More Than 5 Students
27. Find Followers Count
28. Biggest Single Number
29. Customers Who Bought All Products

Advanced Select and Joins

30. The Number of Employees Which Report to Each Employee
31. Primary Department for Each Employee
32. Triangle Judgement
33. Consecutive Numbers
34. Product Price at a Given Date
35. Last Person to Fit in the Bus
36. Count Salary Categories

Subqueries

37. Employees Whose Manager Left the Company
38. Exchange Seats
39. Movie Rating
40. Restaurant Growth
41. Friend Requests II: Who Has the Most Friends
42. Investments in 2016
43. Department Top Three Salaries

Advanced String Functions / Regex / Clause

44. Fix Names in a Table
45. Patients With a Condition
46. Delete Duplicate Emails
47. Second Highest Salary
48. Group Sold Products By The Date
49. List the Products Ordered in a Period
50. Find Users With Valid E-Mails