Node.js: Memory Leak When Using Redis with Bull Queue for Job Management
I'm experiencing a memory leak in my Node.js application that uses Bull for job queuing and Redis for storage. I've set up a simple worker that processes jobs, but after running for a while, the memory usage keeps increasing, ultimately leading to the application crashing. I'm using Node.js version 16.13.0, Bull version 4.0.0, and Redis version 6.2.1. Here's a simplified version of my code: ```javascript const Queue = require('bull'); const redis = require('redis'); const redisClient = redis.createClient(); const jobQueue = new Queue('jobQueue', { redis: { host: '127.0.0.1', port: 6379 } }); jobQueue.process(async (job) => { // Simulate heavy processing await new Promise(resolve => setTimeout(resolve, 1000)); console.log(`Processed job ${job.id}`); }); const addJobs = () => { for (let i = 0; i < 1000; i++) { jobQueue.add({ data: `Job ${i}` }); } }; addJobs(); ``` I suspect that the scenario might be related to how I'm handling completed jobs or perhaps the way Bull retains job data. I’ve tried enabling Redis key space notifications and optimizing the job processing logic, but the memory scenario continues. I even tried the `removeOnComplete` and `removeOnFail` options when adding jobs, but they didn't seem to help. When I monitor my application with `node --inspect`, I see that memory usage grows steadily without releasing memory even after jobs are completed. The heap snapshot indicates that many objects are retained that should be garbage collected. Any advice on how to diagnose this memory leak or optimize the usage of Bull with Redis would be greatly appreciated!