Simple and Easy Beginner Friendly Code using RegExp
IntuitionMy first thought is to filter the Users table to select only those rows where the email address matches a specific pattern. This pattern appears to be
# Intuition
My first thought is to filter the `Users` table to select only those rows where the `email` address matches a specific pattern. This pattern appears to be checking for a basic `.com` email format.

# Approach
1. **Select all columns:** The `SELECT *` clause indicates that we want to retrieve all columns from the `Users` table.
2. **Filter rows based on email pattern:** The `WHERE` clause is used to apply a condition to filter the rows.
3. **Use regular expression matching:** The `REGEXP_LIKE` function (which might vary slightly depending on the specific MySQL version or configuration, sometimes it's `RLIKE` or just `email REGEXP`) is used to check if the `email` column matches the provided regular expression.
4. **Define the regular expression:** The regular expression `'^[a-zA-Z0-9_]+@[a-zA-Z]+\.com'` is used to define the desired email format:
   - `^`: Matches the beginning of the string.
   - `[a-zA-Z0-9_]+`: Matches one or more alphanumeric characters (uppercase or lowercase) or underscores. This part likely represents the username.
   - `@`: Matches the "@" symbol.
   - `[a-zA-Z]+`: Matches one or more uppercase or lowercase alphabetic characters. This part likely represents the domain name.
   - `\.`: Matches a literal dot ".". The backslash is used to escape the special meaning of the dot in regular expressions.
   - `com`: Matches the literal string "com".
   - `$`: Matches the end of the string (although it's missing in the provided code snippet, it's generally a good practice to include it for a complete match).

**Note:** The provided code snippet has a syntax error because the closing single quote for the regular expression is missing. The corrected code will include this.

# Complexity
- Time complexity: $$O(n \cdot m)$$
  - Where 'n' is the number of rows in the `Users` table and 'm' is the average length of the `email` string. In the worst case, the regular expression engine might need to examine each character of the email for every row. However, database systems often have optimized implementations for regular expression matching.

- Space complexity: $$O(1)$$
  - The query performs filtering in place and doesn't require significant extra space proportional to the input size. The space used is mainly for storing the result set, which depends on the number of matching rows.

# Code
```sql
SELECT *
FROM Users
WHERE REGEXP_LIKE(email, '^[a-zA-Z0-9_]+@[a-zA-Z]+\.com$');
['MySQL']