Added Q608

Author: nishant0708

dsa-solutions/lc-solutions/0600-0699/0608-Tree-Node.md

@@ -0,0 +1,101 @@
+---
+id: tree-node
+title: Tree Node
+sidebar_label: 0608-Tree-Node
+tags:
+- Database
+description: "SQL Schema: Given a table with nodes, write an SQL query to find all nodes which are the only child nodes."
+---
+
+## Problem
+
+Given a table `Tree`, write an SQL query to find all nodes which are the only child nodes.
+
+The `Tree` table contains these columns:
+
+- `id`: integer
+- `p_id`: integer (parent id)
+
+### Examples
+
+**Example:**
+
+**Input:**  
+Tree table:
+```
++----+------+
+| id | p_id |
++----+------+
+| 1 | null  |
+| 2 | 1     |
+| 3 | 1     |
+| 4 | 2     |
+| 5 | 2     |
+| 6 | 3     |
+| 7 | 4     |
+| 8 | 5     |
++----+------+
+```
+**Output:** 
+```
++----+
+| id |
++----+
+| 6  |
+| 7  |
+| 8  |
++----+
+```
+Explanation: Nodes `6`, `7`, and `8` are the only child nodes.
+
+### Constraints
+
+- `id` is the primary key column for this table.
+- Each row of this table contains information about the `id` of a node and the `id` of its parent node.
+
+---
+
+## Approach
+
+To solve this problem, we need to find nodes that have no siblings. In other words, we need to find nodes where there is only one child per parent. 
+
+### Steps:
+
+1. Count the number of children for each parent.
+2. Select the nodes where the parent has exactly one child.
+
+### Solution
+
+#### SQL
+
+```sql
+SELECT 
+    id
+FROM 
+    Tree
+WHERE 
+    p_id IN (
+        SELECT 
+            p_id 
+        FROM 
+            Tree 
+        GROUP BY 
+            p_id 
+        HAVING 
+            COUNT(*) = 1
+    );
+```
+### Explanation
+1) The subquery selects p_id values from the Tree table and groups them by p_id. It then uses the HAVING clause to filter groups with a count of exactly one, meaning those p_id values with only one child.
+
+2) The outer query then selects the id values where the p_id matches the ones returned by the subquery, which ensures that we get nodes that are the only child nodes.
+
+### Complexity Analysis
+**Time Complexity:** O(n log n)
+>Reason: The complexity primarily comes from the grouping and counting operations. Depending on the database system, this can vary, but in general, it is expected to be O(n log n).
+
+**Space Complexity:** O(n)
+>Reason: The space complexity is mainly due to the storage of intermediate results, which can be linear in the size of the input.
+
+###  References
+**LeetCode Problem:** Tree Node