Handling Large Data Streams with Sliding Window Algorithm in Node.js - Memory Leak Issues?
I've searched everywhere and can't find a clear answer. I'm currently implementing a sliding window algorithm in Node.js to process large data streams, but I’m working with memory leak issues which I need to seem to resolve. My implementation is designed to keep track of the sum of a fixed number of recent elements from the stream, but after processing a substantial amount of data, the application crashes due to high memory usage. Here's a simplified version of my code: ```javascript class SlidingWindow { constructor(size) { this.size = size; this.window = []; this.sum = 0; } add(value) { if (this.window.length === this.size) { this.sum -= this.window.shift(); } this.window.push(value); this.sum += value; } getSum() { return this.sum; } } const slidingWindow = new SlidingWindow(5); // Simulating data stream setInterval(() => { const randomValue = Math.floor(Math.random() * 100); slidingWindow.add(randomValue); console.log(`Current Sum: ${slidingWindow.getSum()}`); }, 100); ``` I’ve tried using `process.memoryUsage()` to monitor memory allocation, and it does increase steadily over time, even after stopping the data stream. I've also considered using `WeakMap` or `WeakSet` for the window but that doesn't seem applicable here because I need to keep the actual values. Additionally, I've looked into using streams or buffers, but I'm not sure how it would integrate with this sliding window logic. Is there a known pattern or best practice for managing memory in such scenarios, or am I missing something fundamental in my implementation? Any suggestions for preventing memory leaks in a high-frequency data processing loop like this would be greatly appreciated. For context: I'm using Javascript on macOS. Am I missing something obvious? For context: I'm using Javascript on Ubuntu 22.04. What's the correct way to implement this?