worker

I/O performance in Node.js worker threads

时光毁灭记忆、已成空白 提交于 2021-02-19 07:17:57
问题 Here's an example with worker thread that takes ~600ms on local machine for synchronous I/O: const fs = require('fs'); const { isMainThread, Worker, parentPort, workerData } = require('worker_threads'); const filename = './foo.txt'; if (isMainThread) { (async () => { console.time('!'); await new Promise((resolve, reject) => { const worker = new Worker(__filename, { workerData: filename }); worker.on('message', resolve); worker.on('error', reject); worker.on('exit', (code) => { if (code !== 0)

Django / Celery / Kombu worker error: Received and deleted unknown message. Wrong destination?

北城余情 提交于 2021-02-08 08:35:17
问题 It seems as though messages are not getting put onto the queue properly. I'm using Django with Celery and Kombu to make use of Django's own database as a Broker Backend. All I need is a very simple Pub/Sub setup. It will eventually deploy to Heroku, so I'm using foreman to run locally. Here is the relevant code and info: pip freeze Django==1.4.2 celery==3.0.15 django-celery==3.0.11 kombu==2.5.6 Procfile web: source bin/activate; python manage.py run_gunicorn -b 0.0.0.0:$PORT -w 4; python

Scavenger: Allocation failed - JavaScript heap out of memory

蓝咒 提交于 2021-01-29 04:31:02
问题 Here's the error message: <--- Last few GCs ---> [2383:0x7efe08001450] 6100 ms: Scavenge 30.3 (39.5) -> 30.5 (42.7) MB, 73.5 / 0.0 ms (average mu = 1.000, curr ent mu = 1.000) allocation failure [2383:0x7efe08001450] 8464 ms: Scavenge 35.1 (44.5) -> 35.3 (44.8) MB, 2336.2 / 0.0 ms (average mu = 1.000, cu rrent mu = 1.000) allocation failure [2383:0x7efe08001450] 32349 ms: Scavenge 36.1 (44.8) -> 36.0 (45.8) MB, 23879.5 / 0.2 ms (average mu = 1.000, c urrent mu = 1.000) allocation failure <---

Node cluster workers memoryUsage

我是研究僧i 提交于 2021-01-27 17:01:56
问题 Does anyone know if there is a platform independent way to get memory usage of a worker? I would expect it would work like this: console.log('App process memoryUsage: ',process.memoryUsage()); cluster.on('online',function(worker){ // doesn't work! console.log('Workers memory usage: ',worker.process.memoryUsage()); }); But the workers process hasn't the method memoryUsage() . Is there a valid reason this isn't implemented ? The only idea to realize this is to work with unix top -pid 1234

Node cluster workers memoryUsage

寵の児 提交于 2021-01-27 17:01:53
问题 Does anyone know if there is a platform independent way to get memory usage of a worker? I would expect it would work like this: console.log('App process memoryUsage: ',process.memoryUsage()); cluster.on('online',function(worker){ // doesn't work! console.log('Workers memory usage: ',worker.process.memoryUsage()); }); But the workers process hasn't the method memoryUsage() . Is there a valid reason this isn't implemented ? The only idea to realize this is to work with unix top -pid 1234

Start multiple rq worker processes easily ― Horizontal scaling [closed]

淺唱寂寞╮ 提交于 2020-12-31 05:09:38
问题 Closed. This question does not meet Stack Overflow guidelines. It is not currently accepting answers. Want to improve this question? Update the question so it's on-topic for Stack Overflow. Closed 2 years ago . Improve this question How can I create a large number of rq worker processes in a VPS easily? Right now I'm manually opening a terminal and running python3 worker.py in it, and then repeating this until I get a satisfying number of worker instances running. I know this is not a

Start multiple rq worker processes easily ― Horizontal scaling [closed]

有些话、适合烂在心里 提交于 2020-12-31 05:04:52
问题 Closed. This question does not meet Stack Overflow guidelines. It is not currently accepting answers. Want to improve this question? Update the question so it's on-topic for Stack Overflow. Closed 2 years ago . Improve this question How can I create a large number of rq worker processes in a VPS easily? Right now I'm manually opening a terminal and running python3 worker.py in it, and then repeating this until I get a satisfying number of worker instances running. I know this is not a