LeetCode 1606 | Find Servers That Handled Most Requests | Java | Hard | TreeSet | CodeByTushu
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In today’s video, we solve LeetCode 1606 — Find Servers That Handled Most Number of Requests using TreeSet, PriorityQueue and Simulation in Java.
We are given k servers numbered 0 to k - 1 and two integer arrays arrival and load representing the arrival times and execution durations of n requests. Each server has infinite computing capacity but can only process at most one request at any given time. Requests are dispatched cyclically starting from index (i modulo k). If that server is busy, the request searches for the next available server wrapping around to 0, and if all k servers are currently busy, the request is permanently dropped. Our goal is to identify and return all busiest server IDs that handled the maximum number of requests.
We implement an optimal event-driven simulation using a dual-structure engine. We maintain available servers inside a self-balancing binary search tree (TreeSet in Java) to execute logarithmic ceiling lookups with wrap-around fallback, while running tasks are tracked in a min-priority queue ordered by completion timestamp.
🔥 Problem Highlights
✅ Event-driven simulation driven by request arrival order and completion timestamps
✅ Dual-structure architecture combining a TreeSet available pool with a Min-Heap busy queue
✅ Logarithmic cyclic lookup using ceiling(i modulo k) with first() wrap-around fallback
✅ Batch server release mechanism freeing all tasks completed on or before current arrival time
✅ High-load capacity management dropping incoming requests when all k servers are occupied
✅ Optimal O((K + N) log K) runtime with strictly O(K) auxiliary space independent of N
⏱️ TIMESTAMPS
00:00 Intro & Day 107 Streak Celebration
00:41 Problem Understanding & Cyclic Dispatch Rules
01:54 Core Insight: Dual-Structure Engine (TreeSet + Min-Heap)
02:53 5-Step Event-Driven Algorithm Walkthrough
04:13 Optimal Java 17 Solution Walkthrough Line by Line
06:32 Test Cases Walkthrough & Day 107 Streak Celebration
07:05 Time Complexity Analysis (O((K + N) log K))
07:56 Space Complexity Analysis (O(K) Auxiliary Space)
08:33 Summary & Outro!
📂 Problem Folder & Detailed Documentation:
https://github.com/CodeByTushu/CodeByTushu-LeetCode-Solutions/tree/main/solutions/November/09-November/1606-Find-Servers-That-Handled-Most-Number-of-Requests
☕ Java Solution:
https://github.com/CodeByTushu/CodeByTushu-LeetCode-Solutions/blob/main/solutions/November/09-November/1606-Find-Servers-That-Handled-Most-Number-of-Requests/Solution.java
🐍 Python Solution:
https://github.com/CodeByTushu/CodeByTushu-LeetCode-Solutions/blob/main/solutions/November/09-November/1606-Find-Servers-That-Handled-Most-Number-of-Requests/solution.py
⚡ C++ Solution:
https://github.com/CodeByTushu/CodeByTushu-LeetCode-Solutions/blob/main/solutions/November/09-November/1606-Find-Servers-That-Handled-Most-Number-of-Requests/solution.cpp
🌐 JavaScript Solution:
https://github.com/CodeByTushu/CodeByTushu-LeetCode-Solutions/blob/main/solutions/November/09-November/1606-Find-Servers-That-Handled-Most-Number-of-Requests/solution.js
🔗 LeetCode Source Code
📌 https://codebytushu.com/leetcode/problem/find-servers-that-handled-most-number-of-requests
🌐 All LeetCode Solutions
📌 https://codebytushu.com/Leetcode/
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🔥 Perfect For
LeetCode Hard Problems
Java DSA Preparation
Balanced Binary Search Trees
PriorityQueue & Min-Heap Simulation
Cyclic Search and Wrap-Around Patterns
Event-Driven System Design
Time Complexity Optimization
Coding Interview Preparation
Problem Solving
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💬 Question of the Day
Why do we use a TreeSet (or dual min-heaps) rather than a simple queue or list for available servers?
1️⃣ To sort requests by arrival time
2️⃣ To find the next available cyclic server ID greater than or equal to (i modulo k) in O(log k) time
3️⃣ To automatically drop requests when load is too high
4️⃣ To calculate total processing duration across all servers
#LeetCode1606 #LeetCode #FindServersThatHandledMostNumberOfRequests #Java #JavaDSA #TreeSet #PriorityQueue #Heap #DSA #CodingInterview #ProblemSolving #LeetCodeHard #DailyLeetCode #JavaProgramming #CodeByTushu
👇 Comment the answer below! 🔥 Close description
In today’s video, we solve LeetCode 1606 — Find Servers That Handled Most Number of Requests using TreeSet, PriorityQueue and Simulation in Java.
We are given k servers numbered 0 to k - 1 and two integer arrays arrival and load representing the arrival times and execution durations of n requests. Each server has infinite computing capacity but can only process at most one request at any given time. Requests are dispatched cyclically starting from index (i modulo k). If that server is busy, the request searches for the next available server wrapping around to 0, and if all k servers are currently busy, the request is permanently dropped. Our goal is to identify and return all busiest server IDs that handled the maximum number of requests.
We implement an optimal event-driven simulation using a dual-structure engine. We maintain available servers inside a self-balancing binary search tree (TreeSet in Java) to execute logarithmic ceiling lookups with wrap-around fallback, while running tasks are tracked in a min-priority queue ordered by completion timestamp.
🔥 Problem Highlights
✅ Event-driven simulation driven by request arrival order and completion timestamps
✅ Dual-structure architecture combining a TreeSet available pool with a Min-Heap busy queue
✅ Logarithmic cyclic lookup using ceiling(i modulo k) with first() wrap-around fallback
✅ Batch server release mechanism freeing all tasks completed on or before current arrival time
✅ High-load capacity management dropping incoming requests when all k servers are occupied
✅ Optimal O((K + N) log K) runtime with strictly O(K) auxiliary space independent of N
⏱️ TIMESTAMPS
00:00 Intro & Day 107 Streak Celebration
00:41 Problem Understanding & Cyclic Dispatch Rules
01:54 Core Insight: Dual-Structure Engine (TreeSet + Min-Heap)
02:53 5-Step Event-Driven Algorithm Walkthrough
04:13 Optimal Java 17 Solution Walkthrough Line by Line
06:32 Test Cases Walkthrough & Day 107 Streak Celebration
07:05 Time Complexity Analysis (O((K + N) log K))
07:56 Space Complexity Analysis (O(K) Auxiliary Space)
08:33 Summary & Outro!
📂 Problem Folder & Detailed Documentation:
https://github.com/CodeByTushu/CodeByTushu-LeetCode-Solutions/tree/main/solutions/November/09-November/1606-Find-Servers-That-Handled-Most-Number-of-Requests
☕ Java Solution:
https://github.com/CodeByTushu/CodeByTushu-LeetCode-Solutions/blob/main/solutions/November/09-November/1606-Find-Servers-That-Handled-Most-Number-of-Requests/Solution.java
🐍 Python Solution:
https://github.com/CodeByTushu/CodeByTushu-LeetCode-Solutions/blob/main/solutions/November/09-November/1606-Find-Servers-That-Handled-Most-Number-of-Requests/solution.py
⚡ C++ Solution:
https://github.com/CodeByTushu/CodeByTushu-LeetCode-Solutions/blob/main/solutions/November/09-November/1606-Find-Servers-That-Handled-Most-Number-of-Requests/solution.cpp
🌐 JavaScript Solution:
https://github.com/CodeByTushu/CodeByTushu-LeetCode-Solutions/blob/main/solutions/November/09-November/1606-Find-Servers-That-Handled-Most-Number-of-Requests/solution.js
🔗 LeetCode Source Code
📌 https://codebytushu.com/leetcode/problem/find-servers-that-handled-most-number-of-requests
🌐 All LeetCode Solutions
📌 https://codebytushu.com/Leetcode/
📱 Join CodeByTushu on WhatsApp
Get coding updates, LeetCode solutions, daily questions and more.
https://whatsapp.com/channel/0029Vb8k5mCDeON2Xwlkxe40
❤️ Donate
📌 https://codebytushu.com/Leetcode/donate.php
🔥 Perfect For
LeetCode Hard Problems
Java DSA Preparation
Balanced Binary Search Trees
PriorityQueue & Min-Heap Simulation
Cyclic Search and Wrap-Around Patterns
Event-Driven System Design
Time Complexity Optimization
Coding Interview Preparation
Problem Solving
🌐 Follow CodeByTushu
▶️ YouTube: https://www.youtube.com/@codebytushu
📸 Instagram: https://instagram.com/codebytushu/
💼 LinkedIn: https://www.linkedin.com/company/codebytushu/
🌍 Website: https://codebytushu.com
🐙 GitHub: https://github.com/CodeByTushu
❤️ Don’t Forget To
👍 Like | 💬 Comment | 🔔 Subscribe
💬 Question of the Day
Why do we use a TreeSet (or dual min-heaps) rather than a simple queue or list for available servers?
1️⃣ To sort requests by arrival time
2️⃣ To find the next available cyclic server ID greater than or equal to (i modulo k) in O(log k) time
3️⃣ To automatically drop requests when load is too high
4️⃣ To calculate total processing duration across all servers
#LeetCode1606 #LeetCode #FindServersThatHandledMostNumberOfRequests #Java #JavaDSA #TreeSet #PriorityQueue #Heap #DSA #CodingInterview #ProblemSolving #LeetCodeHard #DailyLeetCode #JavaProgramming #CodeByTushu
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