Upload 7-Advanced-String-Functions-RegEx-Clause

Author: ziaroque

7-Advanced-String-Functions-RegEx-Clause/1517_Find_Users_With_Valid_Emails.sql

@@ -0,0 +1,73 @@
+-- Source: https://leetcode.com/problems/find-users-with-valid-e-mails/description/?envType=study-plan-v2&envId=top-sql-50
+
+-- Table: Users
+
+-- +---------------+---------+
+-- | Column Name   | Type    |
+-- +---------------+---------+
+-- | user_id       | int     |
+-- | name          | varchar |
+-- | mail          | varchar |
+-- +---------------+---------+
+-- user_id is the primary key (column with unique values) for this table.
+-- This table contains information of the users signed up in a website. Some e-mails are invalid.
+
+-- Write a solution to find the users who have valid emails.
+
+-- A valid e-mail has a prefix name and a domain where:
+
+-- The prefix name is a string that may contain letters (upper or lower case), digits, underscore '_', period '.', and/or dash '-'. The prefix name must start with a letter.
+-- The domain is '@leetcode.com'.
+-- Return the result table in any order.
+
+-- The result format is in the following example.
+
+-- Example 1:
+
+-- Input: 
+-- Users table:
+-- +---------+-----------+-------------------------+
+-- | user_id | name      | mail                    |
+-- +---------+-----------+-------------------------+
+-- | 1       | Winston   | winston@leetcode.com    |
+-- | 2       | Jonathan  | jonathanisgreat         |
+-- | 3       | Annabelle | bella-@leetcode.com     |
+-- | 4       | Sally     | sally.come@leetcode.com |
+-- | 5       | Marwan    | quarz#2020@leetcode.com |
+-- | 6       | David     | david69@gmail.com       |
+-- | 7       | Shapiro   | .shapo@leetcode.com     |
+-- +---------+-----------+-------------------------+
+-- Output: 
+-- +---------+-----------+-------------------------+
+-- | user_id | name      | mail                    |
+-- +---------+-----------+-------------------------+
+-- | 1       | Winston   | winston@leetcode.com    |
+-- | 3       | Annabelle | bella-@leetcode.com     |
+-- | 4       | Sally     | sally.come@leetcode.com |
+-- +---------+-----------+-------------------------+
+-- Explanation: 
+-- The mail of user 2 does not have a domain.
+-- The mail of user 5 has the # sign which is not allowed.
+-- The mail of user 6 does not have the leetcode domain.
+-- The mail of user 7 starts with a period.
+
+------------------------------------------------------------------------------
+
+-- SQL Schema
+
+Create table If Not Exists Users (user_id int, name varchar(30), mail varchar(50))
+Truncate table Users
+insert into Users (user_id, name, mail) values ('1', 'Winston', 'winston@leetcode.com')
+insert into Users (user_id, name, mail) values ('2', 'Jonathan', 'jonathanisgreat')
+insert into Users (user_id, name, mail) values ('3', 'Annabelle', 'bella-@leetcode.com')
+insert into Users (user_id, name, mail) values ('4', 'Sally', 'sally.come@leetcode.com')
+insert into Users (user_id, name, mail) values ('5', 'Marwan', 'quarz#2020@leetcode.com')
+insert into Users (user_id, name, mail) values ('6', 'David', 'david69@gmail.com')
+insert into Users (user_id, name, mail) values ('7', 'Shapiro', '.shapo@leetcode.com')
+
+-- MS SQL Server Code
+
+SELECT user_id, name, mail
+FROM Users
+WHERE mail LIKE '[A-Za-z]%@leetcode.com'
+AND mail NOT LIKE '%[^A-Za-z0-9.\_-]%@leetcode.com'

7-Advanced-String-Functions-RegEx-Clause/176_Second_Highest_Salary.sql

@@ -0,0 +1,69 @@
+-- Source: https://leetcode.com/problems/second-highest-salary/description/?envType=study-plan-v2&envId=top-sql-50
+
+-- Table: Employee
+
+-- +-------------+------+
+-- | Column Name | Type |
+-- +-------------+------+
+-- | id          | int  |
+-- | salary      | int  |
+-- +-------------+------+
+-- id is the primary key (column with unique values) for this table.
+-- Each row of this table contains information about the salary of an employee.
+
+-- Write a solution to find the second highest salary from the Employee table. If there is no second highest salary, return null (return None in Pandas).
+
+-- The result format is in the following example.
+
+-- Example 1:
+
+-- Input: 
+-- Employee table:
+-- +----+--------+
+-- | id | salary |
+-- +----+--------+
+-- | 1  | 100    |
+-- | 2  | 200    |
+-- | 3  | 300    |
+-- +----+--------+
+-- Output: 
+-- +---------------------+
+-- | SecondHighestSalary |
+-- +---------------------+
+-- | 200                 |
+-- +---------------------+
+-- Example 2:
+
+-- Input: 
+-- Employee table:
+-- +----+--------+
+-- | id | salary |
+-- +----+--------+
+-- | 1  | 100    |
+-- +----+--------+
+-- Output: 
+-- +---------------------+
+-- | SecondHighestSalary |
+-- +---------------------+
+-- | null                |
+-- +---------------------+
+
+------------------------------------------------------------------------------
+
+-- SQL Schema
+
+Create table If Not Exists Employee (id int, salary int)
+Truncate table Employee
+insert into Employee (id, salary) values ('1', '100')
+insert into Employee (id, salary) values ('2', '200')
+insert into Employee (id, salary) values ('3', '300')
+
+-- MS SQL Server Code
+
+SELECT (
+    SELECT DISTINCT salary
+     FROM Employee
+     ORDER BY salary DESC
+     OFFSET 1 ROW
+     FETCH NEXT 1 ROW ONLY
+) AS SecondHighestSalary;

7-Advanced-String-Functions-RegEx-Clause/196_Delete_Duplicate_Emails.sql

@@ -0,0 +1,65 @@
+-- Source: https://leetcode.com/problems/delete-duplicate-emails/description/?envType=study-plan-v2&envId=top-sql-50
+
+-- Table: Person
+
+-- +-------------+---------+
+-- | Column Name | Type    |
+-- +-------------+---------+
+-- | id          | int     |
+-- | email       | varchar |
+-- +-------------+---------+
+-- id is the primary key (column with unique values) for this table.
+-- Each row of this table contains an email. The emails will not contain uppercase letters.
+
+-- Write a solution to delete all duplicate emails, keeping only one unique email with the smallest id.
+
+-- For SQL users, please note that you are supposed to write a DELETE statement and not a SELECT one.
+
+-- For Pandas users, please note that you are supposed to modify Person in place.
+
+-- After running your script, the answer shown is the Person table. The driver will first compile and run your piece of code and then show the Person table. The final order of the Person table does not matter.
+
+-- The result format is in the following example.
+
+-- Example 1:
+
+-- Input: 
+-- Person table:
+-- +----+------------------+
+-- | id | email            |
+-- +----+------------------+
+-- | 1  | john@example.com |
+-- | 2  | bob@example.com  |
+-- | 3  | john@example.com |
+-- +----+------------------+
+-- Output: 
+-- +----+------------------+
+-- | id | email            |
+-- +----+------------------+
+-- | 1  | john@example.com |
+-- | 2  | bob@example.com  |
+-- +----+------------------+
+-- Explanation: john@example.com is repeated two times. We keep the row with the smallest Id = 1.
+
+------------------------------------------------------------------------------
+
+-- SQL Schema
+
+Create table If Not Exists Person (Id int, Email varchar(255))
+Truncate table Person
+insert into Person (id, email) values ('1', 'john@example.com')
+insert into Person (id, email) values ('2', 'bob@example.com')
+insert into Person (id, email) values ('3', 'john@example.com')
+
+-- MS SQL Server Code
+
+WITH DuplicateEmails AS (
+    SELECT
+        id
+        , email
+        , ROW_NUMBER() OVER(PARTITION BY email ORDER BY id) AS rank_id
+    FROM Person
+)
+
+DELETE FROM DuplicateEmails
+WHERE rank_id > 1;

README.md

@@ -94,12 +94,12 @@ This github repository contains my solutions for the Top SQL 50 problems using M
 
 ### Advanced String Functions / Regex Clause
 
-| #    | Problem                               | Level  | Status |
-| ---- | ------------------------------------- | ------ | ------ |
-| 1667 | Fix Names in a Table                  | Easy   | -      |
-| 1527 | Patients with a Condition             | Easy   | -      |
-| 196  | [Delete Duplicate Emails]()           | Easy   | Solved |
-| 176  | [Second Highest Salary]()             | Medium | Solved |
-| 1484 | Group Sold Products By The Date       | Easy   | -      |
-| 1327 | List the Products Ordered in a Period | Easy   | -      |
-| 1517 | [Find Users With Valid E-mails]()     | Easy   | Solved |
+| #    | Problem                                                                                                          | Level  | Status |
+| ---- | ---------------------------------------------------------------------------------------------------------------- | ------ | ------ |
+| 1667 | Fix Names in a Table                                                                                             | Easy   | -      |
+| 1527 | Patients with a Condition                                                                                        | Easy   | -      |
+| 196  | [Delete Duplicate Emails](/7-Advanced-String-Functions-RegEx-Clause/196_Delete_Duplicate_Emails.sql)             | Easy   | Solved |
+| 176  | [Second Highest Salary](/7-Advanced-String-Functions-RegEx-Clause/176_Second_Highest_Salary.sql)                 | Medium | Solved |
+| 1484 | Group Sold Products By The Date                                                                                  | Easy   | -      |
+| 1327 | List the Products Ordered in a Period                                                                            | Easy   | -      |
+| 1517 | [Find Users With Valid E-mails](/7-Advanced-String-Functions-RegEx-Clause/1517_Find_Users_With_Valid_Emails.sql) | Easy   | Solved |