Median of Data Stream Using Two Heaps in DSA Javascript - Build from Scratch

Median of Data Stream Using Two Heaps

📖 Scenario: Imagine you are building a live dashboard that shows the median value of numbers coming in one by one, like temperatures recorded every minute. You want to keep track of the median efficiently as new numbers arrive.

🎯 Goal: Build a program that uses two heaps (a max heap and a min heap) to find the median of a stream of numbers step-by-step.

📋 What You'll Learn

Create two heaps: a max heap for the smaller half of numbers and a min heap for the larger half.

Add numbers one by one to the correct heap.

Balance the heaps so their sizes differ by at most one.

Calculate the median from the heaps after all numbers are added.

💡 Why This Matters

🌍 Real World

Finding median in real-time data streams like sensor readings, stock prices, or live user inputs.

💼 Career

Useful for roles in data engineering, software development, and analytics where streaming data needs quick summary statistics.

1

Create two empty heaps

Create two empty arrays called maxHeap and minHeap to represent the max heap and min heap respectively.

DSA Javascript

# Your code here
const maxHeap = [];
const minHeap = [];

Hint

Use empty arrays to start your heaps.

2

Add a helper function to insert into max heap

Write a function called insertMaxHeap that takes a number and inserts it into maxHeap while keeping it sorted in descending order.

DSA Javascript

const maxHeap = [];
const minHeap = [];

// Write function insertMaxHeap to insert number in descending order
// Your code here

Hint

Push the number then sort descending to simulate max heap.

3

Add a helper function to insert into min heap

Write a function called insertMinHeap that takes a number and inserts it into minHeap while keeping it sorted in ascending order.

DSA Javascript

const maxHeap = [];
const minHeap = [];

function insertMaxHeap(num) {
    maxHeap.push(num);
    maxHeap.sort((a, b) => b - a);
}

// Write function insertMinHeap to insert number in ascending order
// Your code here

Hint

Push the number then sort ascending to simulate min heap.

4

Add numbers and find median

Write code to add these numbers 5, 15, 1, 3 one by one to the heaps using insertMaxHeap and insertMinHeap. Keep the heaps balanced so their sizes differ by at most one. Then calculate and print the median after all insertions.

DSA Javascript

const maxHeap = [];
const minHeap = [];

function insertMaxHeap(num) {
    maxHeap.push(num);
    maxHeap.sort((a, b) => b - a);
}

function insertMinHeap(num) {
    minHeap.push(num);
    minHeap.sort((a, b) => a - b);
}

// Add numbers 5, 15, 1, 3 to heaps and balance them
// Calculate and print the median
// Your code here

Hint

Insert each number, balance heaps, then calculate median as middle value or average of two middles.