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‎README.md‎

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@@ -621,6 +621,7 @@ implementation 'com.github.javadev:leetcode-in-kotlin:1.5'
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| <!-- --> | <!-- --> | <!-- --> | <!-- --> | <!-- --> | <!-- -->
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|-|-|-|-|-|-
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| 0183 |[Customers Who Never Order](src/main/kotlin/g0101_0200/s0183_customers_who_never_order/script.sql)| Easy | Database | 376 | 98.73
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#### Day 2 Select and Order
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@@ -910,6 +911,7 @@ implementation 'com.github.javadev:leetcode-in-kotlin:1.5'
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| <!-- --> | <!-- --> | <!-- --> | <!-- --> | <!-- --> | <!-- -->
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|-|-|-|-|-|-
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| 0014 |[Longest Common Prefix](src/main/kotlin/g0001_0100/s0014_longest_common_prefix/Solution.kt)| Easy | Top_Interview_Questions, String | 209 | 88.86
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| 0187 |[Repeated DNA Sequences](src/main/kotlin/g0101_0200/s0187_repeated_dna_sequences/Solution.kt)| Medium | String, Hash_Table, Bit_Manipulation, Sliding_Window, Hash_Function, Rolling_Hash | 319 | 79.03
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| 0003 |[Longest Substring Without Repeating Characters](src/main/kotlin/g0001_0100/s0003_longest_substring_without_repeating_characters/Solution.kt)| Medium | Top_100_Liked_Questions, Top_Interview_Questions, String, Hash_Table, Sliding_Window | 258 | 91.09
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| 0020 |[Valid Parentheses](src/main/kotlin/g0001_0100/s0020_valid_parentheses/Solution.kt)| Easy | Top_100_Liked_Questions, Top_Interview_Questions, String, Stack | 226 | 72.53
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| 0005 |[Longest Palindromic Substring](src/main/kotlin/g0001_0100/s0005_longest_palindromic_substring/Solution.kt)| Medium | Top_100_Liked_Questions, Top_Interview_Questions, String, Dynamic_Programming | 323 | 75.48
@@ -1217,6 +1219,7 @@ implementation 'com.github.javadev:leetcode-in-kotlin:1.5'
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| <!-- --> | <!-- --> | <!-- --> | <!-- --> | <!-- --> | <!-- -->
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|-|-|-|-|-|-
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| 0187 |[Repeated DNA Sequences](src/main/kotlin/g0101_0200/s0187_repeated_dna_sequences/Solution.kt)| Medium | String, Hash_Table, Bit_Manipulation, Sliding_Window, Hash_Function, Rolling_Hash | 319 | 79.03
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| 0005 |[Longest Palindromic Substring](src/main/kotlin/g0001_0100/s0005_longest_palindromic_substring/Solution.kt)| Medium | Top_100_Liked_Questions, Top_Interview_Questions, String, Dynamic_Programming | 323 | 75.48
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#### Day 10 Linked List
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| 0199 |[Binary Tree Right Side View](src/main/kotlin/g0101_0200/s0199_binary_tree_right_side_view/Solution.kt)| Medium | Depth_First_Search, Breadth_First_Search, Tree, Binary_Tree, Data_Structure_II_Day_16_Tree, Level_2_Day_15_Tree | 194 | 92.89
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| 0198 |[House Robber](src/main/kotlin/g0101_0200/s0198_house_robber/Solution.kt)| Medium | Top_100_Liked_Questions, Top_Interview_Questions, Array, Dynamic_Programming, Algorithm_I_Day_12_Dynamic_Programming, Dynamic_Programming_I_Day_3, Level_2_Day_12_Dynamic_Programming, Udemy_Dynamic_Programming | 156 | 92.24
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| 0189 |[Rotate Array](src/main/kotlin/g0101_0200/s0189_rotate_array/Solution.kt)| Medium | Top_100_Liked_Questions, Top_Interview_Questions, Array, Math, Two_Pointers, Algorithm_I_Day_2_Two_Pointers, Udemy_Arrays | 483 | 86.95
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| 0187 |[Repeated DNA Sequences](src/main/kotlin/g0101_0200/s0187_repeated_dna_sequences/Solution.kt)| Medium | String, Hash_Table, Bit_Manipulation, Sliding_Window, Hash_Function, Rolling_Hash, Data_Structure_II_Day_9_String, Udemy_Strings | 319 | 79.03
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| 0185 |[Department Top Three Salaries](src/main/kotlin/g0101_0200/s0185_department_top_three_salaries/script.sql)| Hard | Database | 643 | 95.52
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| 0184 |[Department Highest Salary](src/main/kotlin/g0101_0200/s0184_department_highest_salary/script.sql)| Medium | Database | 590 | 73.49
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| 0183 |[Customers Who Never Order](src/main/kotlin/g0101_0200/s0183_customers_who_never_order/script.sql)| Easy | Database, SQL_I_Day_1_Select | 376 | 98.73
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| 0182 |[Duplicate Emails](src/main/kotlin/g0101_0200/s0182_duplicate_emails/script.sql)| Easy | Database, SQL_I_Day_10_Where | 303 | 92.08
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| 0181 |[Employees Earning More Than Their Managers](src/main/kotlin/g0101_0200/s0181_employees_earning_more_than_their_managers/script.sql)| Easy | Database | 315 | 94.44
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| 0180 |[Consecutive Numbers](src/main/kotlin/g0101_0200/s0180_consecutive_numbers/script.sql)| Medium | Database | 550 | 48.44

‎src/main/kotlin/g0101_0200/s0183_customers_who_never_order/readme.md‎

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183\. Customers Who Never Order
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Easy
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SQL Schema
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Table: `Customers`
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+-------------+---------+
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| Column Name | Type |
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+-------------+---------+
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| id | int |
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| name | varchar |
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+-------------+---------+
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id is the primary key column for this table.
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Each row of this table indicates the ID and name of a customer.
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Table: `Orders`
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+-------------+------+
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| Column Name | Type |
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+-------------+------+
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| id | int |
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| customerId | int |
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+-------------+------+
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id is the primary key column for this table.
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customerId is a foreign key of the ID from the Customers table.
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Each row of this table indicates the ID of an order and the ID of the customer who ordered it.
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Write an SQL query to report all customers who never order anything.
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Return the result table in **any order**.
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The query result format is in the following example.
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**Example 1:**
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**Input:**
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Customers table:
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+----+-------+
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| id | name |
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+----+-------+
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| 1 | Joe |
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| 2 | Henry |
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| 3 | Sam |
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| 4 | Max |
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+----+-------+
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Orders table:
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+----+------------+
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| id | customerId |
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+----+------------+
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| 1 | 3 |
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| 2 | 1 |
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+----+------------+
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**Output:**
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+-----------+
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| Customers |
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+-----------+
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| Henry |
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| Max |
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+-----------+

‎src/main/kotlin/g0101_0200/s0183_customers_who_never_order/script.sql‎

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# Write your MySQL query statement below
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# #Easy #Database #SQL_I_Day_1_Select #2022_06_27_Time_376_ms_(98.73%)_Space_0B_(100.00%)
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SELECT c.Name as Customers
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FROM Customers as c
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LEFT JOIN Orders as o
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ON c.Id = o.CustomerId
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WHERE o.CustomerId is null

‎src/main/kotlin/g0101_0200/s0184_department_highest_salary/readme.md‎

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184\. Department Highest Salary
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Medium
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SQL Schema
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Table: `Employee`
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+--------------+---------+
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| Column Name | Type |
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+--------------+---------+
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| id | int |
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| name | varchar |
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| salary | int |
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| departmentId | int |
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+--------------+---------+
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id is the primary key column for this table.
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departmentId is a foreign key of the ID from the `Department` table.
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Each row of this table indicates the ID, name, and salary of an employee. It also contains the ID of their department.
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Table: `Department`
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+-------------+---------+
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| Column Name | Type |
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+-------------+---------+
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| id | int |
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| name | varchar |
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+-------------+---------+
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id is the primary key column for this table.
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Each row of this table indicates the ID of a department and its name.
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Write an SQL query to find employees who have the highest salary in each of the departments.
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Return the result table in **any order**.
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The query result format is in the following example.
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**Example 1:**
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**Input:**
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Employee table:
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+----+-------+--------+--------------+
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| id | name | salary | departmentId |
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+----+-------+--------+--------------+
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| 1 | Joe | 70000 | 1 |
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| 2 | Jim | 90000 | 1 |
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| 3 | Henry | 80000 | 2 |
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| 4 | Sam | 60000 | 2 |
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| 5 | Max | 90000 | 1 |
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+----+-------+--------+--------------+
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Department table:
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+----+-------+
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| id | name |
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+----+-------+
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| 1 | IT |
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| 2 | Sales |
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+----+-------+
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**Output:**
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+------------+----------+--------+
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| Department | Employee | Salary |
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+------------+----------+--------+
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| IT | Jim | 90000 |
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| Sales | Henry | 80000 |
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| IT | Max | 90000 |
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+------------+----------+--------+
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**Explanation:** Max and Jim both have the highest salary in the IT department and Henry has the highest salary in the Sales department.

‎src/main/kotlin/g0101_0200/s0184_department_highest_salary/script.sql‎

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# Write your MySQL query statement below
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# #Medium #Database #2022_06_27_Time_590_ms_(73.49%)_Space_0B_(100.00%)
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SELECT
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d.Name AS Department,
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Sel.Name AS Employee,
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Sel.Salary AS Salary
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FROM
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(
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SELECT
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Name,
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Salary,
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DepartmentId,
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DENSE_RANK() OVER (PARTITION BY DepartmentId ORDER BY Salary DESC) AS dr
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FROM Employee
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) AS Sel
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INNER JOIN Department d ON d.Id = Sel.DepartmentId
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WHERE Sel.dr = 1

‎src/main/kotlin/g0101_0200/s0185_department_top_three_salaries/readme.md‎

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185\. Department Top Three Salaries
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Hard
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SQL Schema
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Table: `Employee`
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+--------------+---------+
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| Column Name | Type |
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+--------------+---------+
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| id | int |
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| name | varchar |
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| salary | int |
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| departmentId | int |
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+--------------+---------+
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id is the primary key column for this table.
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departmentId is a foreign key of the ID from the `Department` table. Each row of this table indicates the ID, name, and salary of an employee. It also contains the ID of their department.
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Table: `Department`
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+-------------+---------+
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| Column Name | Type |
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+-------------+---------+
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| id | int |
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| name | varchar |
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+-------------+---------+
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id is the primary key column for this table.
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Each row of this table indicates the ID of a department and its name.
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A company's executives are interested in seeing who earns the most money in each of the company's departments. A **high earner** in a department is an employee who has a salary in the **top three unique** salaries for that department.
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Write an SQL query to find the employees who are **high earners** in each of the departments.
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Return the result table **in any order**.
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The query result format is in the following example.
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**Example 1:**
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**Input:**
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Employee table:
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+----+-------+--------+--------------+
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| id | name | salary | departmentId |
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+----+-------+--------+--------------+
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| 1 | Joe | 85000 | 1 |
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| 2 | Henry | 80000 | 2 |
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| 3 | Sam | 60000 | 2 |
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| 4 | Max | 90000 | 1 |
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| 5 | Janet | 69000 | 1 |
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| 6 | Randy | 85000 | 1 |
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| 7 | Will | 70000 | 1 |
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+----+-------+--------+--------------+
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Department table:
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+----+-------+
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| id | name |
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+----+-------+
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| 1 | IT |
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| 2 | Sales |
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+----+-------+
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**Output:**
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+------------+----------+--------+
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| Department | Employee | Salary |
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+------------+----------+--------+
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| IT | Max | 90000 |
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| IT | Joe | 85000 |
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| IT | Randy | 85000 |
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| IT | Will | 70000 |
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| Sales | Henry | 80000 |
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| Sales | Sam | 60000 |
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+------------+----------+--------+
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**Explanation:**
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In the IT department:
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- Max earns the highest unique salary
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- Both Randy and Joe earn the second-highest unique salary
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- Will earns the third-highest unique salary
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In the Sales department:
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- Henry earns the highest salary
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- Sam earns the second-highest salary
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- There is no third-highest salary as there are only two employees

‎src/main/kotlin/g0101_0200/s0185_department_top_three_salaries/script.sql‎

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# Write your MySQL query statement below
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# #Hard #Database #2022_06_27_Time_643_ms_(95.52%)_Space_0B_(100.00%)
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SELECT D.name AS Department,
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A.name AS Employee,
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A.salary AS Salary
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FROM
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(SELECT *,
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dense_rank() over(PARTITION BY departmentID
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ORDER BY salary DESC) AS rn
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FROM Employee) A
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INNER JOIN Department D ON A.departmentid = D.id
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WHERE A.rn < 4
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ORDER BY Department, Salary DESC

‎src/main/kotlin/g0101_0200/s0187_repeated_dna_sequences/Solution.kt‎

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package g0101_0200.s0187_repeated_dna_sequences
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// #Medium #String #Hash_Table #Bit_Manipulation #Sliding_Window #Hash_Function #Rolling_Hash
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// #Data_Structure_II_Day_9_String #Udemy_Strings
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// #2022_10_17_Time_319_ms_(79.03%)_Space_66.7_MB_(16.13%)
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class Solution {
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fun findRepeatedDnaSequences(s: String): List<String> {
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if (s.length < 10) {
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return emptyList()
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}
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val seen = BooleanArray(1024 * 1024)
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val added = BooleanArray(1024 * 1024)
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val chars = s.toCharArray()
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var buf = 0
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val map = IntArray(128)
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map['A'.code] = 0
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map['C'.code] = 1
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map['G'.code] = 2
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map['T'.code] = 3
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val ans: MutableList<String> = ArrayList(s.length / 2)
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for (i in 0..9) {
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buf = (buf shl 2) + map[chars[i].code]
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}
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seen[buf] = true
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for (i in 10 until chars.size) {
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buf = (buf shl 2 and 0xFFFFF) + map[chars[i].code]
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if (seen[buf]) {
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if (!added[buf]) {
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ans.add(String(chars, i - 9, 10))
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added[buf] = true
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}
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} else {
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seen[buf] = true
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}
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}
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return ans
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}
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}

‎src/main/kotlin/g0101_0200/s0187_repeated_dna_sequences/readme.md‎

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187\. Repeated DNA Sequences
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Medium
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The **DNA sequence** is composed of a series of nucleotides abbreviated as `'A'`, `'C'`, `'G'`, and `'T'`.
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* For example, `"ACGAATTCCG"` is a **DNA sequence**.
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When studying **DNA**, it is useful to identify repeated sequences within the DNA.
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Given a string `s` that represents a **DNA sequence**, return all the **`10`\-letter-long** sequences (substrings) that occur more than once in a DNA molecule. You may return the answer in **any order**.
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**Example 1:**
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**Input:** s = "AAAAACCCCCAAAAACCCCCCAAAAAGGGTTT"
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**Output:** ["AAAAACCCCC","CCCCCAAAAA"]
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**Example 2:**
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**Input:** s = "AAAAAAAAAAAAA"
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**Output:** ["AAAAAAAAAA"]
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**Constraints:**
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* <code>1 <= s.length <= 10<sup>5</sup></code>
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* `s[i]` is either `'A'`, `'C'`, `'G'`, or `'T'`.

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