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public List<List<Integer>> levelOrder(TreeNode root) {
     List<List<Integer>> list  = new ArrayList<>();
     Queue<TreeNode> q = new java.util.LinkedList<TreeNode>();
     ArrayList<Integer> level;
     if(root!=null){
         level = new ArrayList<Integer>();
         level.add(root.val);
         list.add(level);
         q.add(root);
         level = new ArrayList<Integer>();

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public class ExampleTwo {
  
  public static void myExample(){
  		System.out.println("Hello there, you have reached personal website of Sreeprasad");
  }
	
	public static void main(String[] args) {
		Thread t = new Thread(ExampleTwo::myExample);
		t.start();
	}

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Runnable aRunnableObject = () -> System.out.println("Hello CrowdTwist !");

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public class ExampleThree{
	
	private static int bal=0;	

	 public static void updateBal(){
	 	bal+=10;
	 	bal-=10;
	 }

	 public static void monitorBal(){

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public class ThreadJoin{


	public static void main(String[] args) {
		Thread t = new Thread(ThreadJoin::print);
		t.start();
		try{
			t.join();	
		}catch(InterruptedException e){
			System.out.println(e);

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Programming Achievements: How to Level Up as a Developer

This gist is part of a blog post. Check it out at:

http://jasonrudolph.com/blog/2011/08/09/programming-achievements-how-to-level-up-as-a-developer

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Latency numbers every programmer should know

L1 cache reference ......................... 0.5 ns
Branch mispredict ............................ 5 ns
L2 cache reference ........................... 7 ns
Mutex lock/unlock ........................... 25 ns
Main memory reference ...................... 100 ns             
Compress 1K bytes with Zippy ............. 3,000 ns  =   3 µs
Send 2K bytes over 1 Gbps network ....... 20,000 ns  =  20 µs
SSD random read ........................ 150,000 ns  = 150 µs

Read 1 MB sequentially from memory ..... 250,000 ns = 250 µs

sreeprasad

#System Design Cheatsheet

Picking the right architecture = Picking the right battles + Managing trade-offs

##Basic Steps

1. Clarify and agree on the scope of the system

• User cases (description of sequences of events that, taken together, lead to a system doing something useful)
  • Who is going to use it?
  • How are they going to use it?

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Introduction

This gist started with a collection of resources I was maintaining on stream data processing — also known as distributed logs, data pipelines, event sourcing, CQRS, and other names.

Over time the set of resources grew quite large and I received some interest in a more guided, opinionated path for learning about stream data processing. So I added the reading list.

Please send me feedback!

sreeprasad

import java.util.Collection;
import java.util.Map;
import java.util.Map.Entry;
import java.util.Set;
import java.util.WeakHashMap;
import java.util.concurrent.ConcurrentHashMap;
import java.util.concurrent.DelayQueue;
import java.util.concurrent.Delayed;
import java.util.concurrent.TimeUnit;