we're diving deeper in Node.js architecture, to achieve fully understanding, how to scale our application.
Clear solution is cluster usage https://nodejs.org/api/cluster.html. Everything seems to be fine, apart of workers management description:
Node.js does not automatically manage the number of workers for you, however. It is your responsibility to manage the worker pool for your application's needs.
I was searching, how to really manage the workers, but most solutions, says:
Start so many workers as you've got cores.
But I would like to dynamically scale up or down my workers count, depending on current load on server. So if there is load on server and queue is getting longer, I would like to start next worker. In another way, when there isn't so much load, I would like to shut down workers (and leave f.e. minimum 2 of them).
The ideal place, will be for me Master Process queue, and event when new Request is coming to Master Process. On this place we can decide if we need next worker.
Do you have any solution or experience with managing workers from Master Thread in Cluster? Starting and killing them dynamically?
Regards,
Radek
following code will help you to understand to create cluster on request basis.
this program will genrate new cluster in every 10 request.
Note: you need to open http://localhost:8000/ and refresh the page for increasing request.
var cluster = require('cluster');
var http = require('http');
var numCPUs = require('os').cpus().length;
var numReqs = 0;
var initialRequest = 10;
var maxcluster = 10;
var totalcluster = 2;
if (cluster.isMaster) {
// Fork workers.
for (var i = 0; i < 2; i++) {
var worker = cluster.fork();
console.log('cluster master');
worker.on('message', function(msg) {
if (msg.cmd && msg.cmd == 'notifyRequest') {
numReqs++;
}
});
}
setInterval(function() {
console.log("numReqs =", numReqs);
isNeedWorker(numReqs) && cluster.fork();
}, 1000);
} else {
console.log('cluster one initilize');
// Worker processes have a http server.
http.Server(function(req, res) {
res.writeHead(200);
res.end("hello world\n");
// Send message to master process
process.send({ cmd: 'notifyRequest' });
}).listen(8000);
}
function isNeedWorker(numReqs) {
if( numReqs >= initialRequest && totalcluster < numCPUs ) {
initialRequest = initialRequest + 10;
totalcluster = totalcluster + 1;
return true;
} else {
return false;
}
}
To manually manage your workers, you need a messaging layer to facilitate inter process communication. With IPC master and worker can communicate effectively, by default and architecture stand point this behavior is already implemented in the process module native. However i find the native implementation not flexible or robust enough to handle horizontal scaling due to network requests.
One obvious solution Redis as a message broker to facilitate this method of master and slave communication. However this solution also as its faults , which is context latency, directly linked to command and reply.
Further research led me to RabbitMQ,great fit for distributing time-consuming tasks among multiple workers.The main idea behind Work Queues (aka: Task Queues) is to avoid doing a resource-intensive task immediately and having to wait for it to complete. Instead we schedule the task to be done later. We encapsulate a task as a message and send it to the queue. A worker process running in the background will pop the tasks and eventually execute the job. When you run many workers the tasks will be shared between them.
To implement a robust server , read this link , it may give some insights. Link
Related
I'm using Nodejs cluster module to have multiple workers running.
I created a basic Architecture where there will be a single MASTER process which is basically an express server handling multiple requests and the main task of MASTER would be writing incoming data from requests into a REDIS instance. Other workers(numOfCPUs - 1) will be non-master i.e. they won't be handling any request as they are just the consumers. I have two features namely ABC and DEF. I distributed the non-master workers evenly across features via assigning them type.
For eg: on a 8-core machine:
1 will be MASTER instance handling request via express server
Remaining (8 - 1 = 7) will be distributed evenly. 4 to feature:ABD and 3 to fetaure:DEF.
non-master workers are basically consumers i.e. they read from REDIS in which only MASTER worker can write data.
Here's the code for the same:
if (cluster.isMaster) {
// Fork workers.
for (let i = 0; i < numCPUs - 1; i++) {
ClusteringUtil.forkNewClusterWithAutoTypeBalancing();
}
cluster.on('exit', function(worker) {
console.log(`Worker ${worker.process.pid}::type(${worker.type}) died`);
ClusteringUtil.removeWorkerFromList(worker.type);
ClusteringUtil.forkNewClusterWithAutoTypeBalancing();
});
// Start consuming on server-start
ABCConsumer.start();
DEFConsumer.start();
console.log(`Master running with process-id: ${process.pid}`);
} else {
console.log('CLUSTER type', cluster.worker.process.env.type, 'running on', process.pid);
if (
cluster.worker.process.env &&
cluster.worker.process.env.type &&
cluster.worker.process.env.type === ServerTypeEnum.EXPRESS
) {
// worker for handling requests
app.use(express.json());
...
}
{
Everything works fine except consumers reading from REDIS.
Since there are multiple consumers of a particular feature, each one reads the same message and start processing individually, which is what I don't want. If there are 4 consumers, 1 is marked as busy and can not consumer until free, 3 are available. Once the message for that particular feature is written in REDIS by MASTER, the problem is all 3 available consumers of that feature start consuming. This means that the for a single message, the job is done based on number of available consumers.
const stringifedData = JSON.stringify(req.body);
const key = uuidv1();
const asyncHsetRes = await asyncHset(type, key, stringifedData);
if (asyncHsetRes) {
await asyncRpush(FeatureKeyEnum.REDIS.ABC_MESSAGE_QUEUE, key);
res.send({ status: 'success', message: 'Added to processing queue' });
} else {
res.send({ error: 'failure', message: 'Something went wrong in adding to queue' });
}
Consumer simply accepts messages and stop when it is busy
module.exports.startHeartbeat = startHeartbeat = async function(config = {}) {
if (!config || !config.type || !config.listKey) {
return;
}
heartbeatIntervalObj[config.type] = setInterval(async () => {
await asyncLindex(config.listKey, -1).then(async res => {
if (res) {
await getFreeWorkerAndDoJob(res, config);
stopHeartbeat(config);
}
});
}, HEARTBEAT_INTERVAL);
};
Ideally, a message should be read by only one consumer of that particular feature. After consuming, it is marked as busy so it won't consume further until free(I have handled this). Next message could only be processed by only one consumer out of other available consumers.
Please help me in tacking this problem. Again, I want one message to be read by only one free consumer and rest free consumers should wait for new message.
Thanks
I'm not sure I fully get your Redis consumers architecture, but I feel like it contradicts with the use case of Redis itself. What you're trying to achieve is essentially a queue based messaging with an ability to commit a message once its done.
Redis has its own pub/sub feature, but it is built on fire and forget principle. It doesn't distinguish between consumers - it just sends the data to all of them, assuming that its their logic to handle the incoming data.
I recommend to you use Queue Servers like RabbitMQ. You can achieve your goal with some features that AMQP 0-9-1 supports: message acknowledgment, consumer's prefetch count and so on. You can set up your cluster with very agile configs like ok, I want to have X consumers, and each can handle 1 unique (!) message at a time and they will receive new ones only after they let the server (rabbitmq) know that they successfully finished message processing. This is highly configurable and robust.
However, if you want to go serverless with some fully managed service so that you don't provision like virtual machines or anything else to run a message queue server of your choice, you can use AWS SQS. It has pretty much similar API and features list.
Hope it helps!
I'd like to fork a long running express request in node and send an express response with the child, allowing the parent to serve other requests. I'm already using cluster but I'd like to fork another process in addition to the cluster for specific long running requests. What I'd like to prevent is all the processes in the cluster being consumed by a specific long running processes, while most of the other requests are fast.
Thanks
var express = require('express');
var webserver = express();
webserver.get("/test", function(request, response) {
// long running HTTP request
response.send(...);
});
What I'm thinking of is something like following, although I'm not sure this works:
var cp = require('child_process');
var express = require('express');
var webserver = express();
webserver.get("/test", function(request, response) {
var child = cp.fork('do_nothing.js');
child.on("message", function(message) {
if(message == "start") {
response.send(...);
process.exit();
}
});
child.send("start");
});
Let me know if anyone knows how to do this.
Edit: So, the idea is that the child could take a long time. There are a limited number of processes in the cluster serving express responses and I don't want to consume them all on a specific long-running request type. In the code below, the entire cluster would be consumed by the long running express requests.
while(1) {
if(rand() % 100 == 0) {
if(fork() == 0) {
sleep(hour(1));
exit(0);
}
} else {
sleep(second(1));
}
waitpid(WAIT_ANY, &status, WNOHANG);
}
Edit: I am going to mark the self-answer as solved. I'm sure there's a way to pass a socket to a child but it's not really necessary because the cluster master can manage all child processes. Thanks for your help.
Your second code block is confusing because it appears that you're killing the parent process with process.exit() rather than the child.
In any case, if we assume the problem is this:
You have a cluster of "regular processes".
Occasionally, you want to take an incoming request that was assigned to one of the cluster processes and pass it off to a long running child that will eventually send the response.
After sending the response, the long running child process should exit.
You have a couple options.
You can have the clustered process that was assigned the request, start up a child, send it some initial data and listen for a message back from the child. When it gets the message back from the child, it can send the response and kill the child. This appears to be what you're attempting to do in your second code block.
You can have the clustered process that was assigned the request, start up a child and reassign the request socket to the child process and the child can then own that socket from then on. When it finally sends the response, it can then exit itself.
The first is simpler because no socket assignment from one process to another is required. To implement the second, you'd have to write or find the code to do socket reassignment and then reconstituted as an express request within the child. The cluster module does something like this so the code is there to be found and learned from, but I'm not aware of a trivial way to do it.
Personally, I don't see any particular downside to the first. I suppose if the clustered process were to die for some , you'd lose the long running request socket, but hopefully you can just code your clustered processes not to die unnecessarily.
You can read this article on sending a socket to a new node.js process:
Sending a socket to a forked process
And, this node.js doc on sending a socket:
Example: sending a socket object
So, I've verified that this is not necessary for my use case, but I was able to get it working using the code below. It's not exactly what the OP asks for, but it works.
What it's doing is sending an instruction to the cluster master, which forks the additional process upon receipt of the slow express request.
Since the express request doesn't need to know the status of the newly forked cluster worker, it just handles the slow request as normal and then exits.
The instruction to the cluster master informs the master not to replace the dying slow express request process, so the number of workers reverts to the original number after the slow request finishes.
The pool will increase in size when there are slow requests, but revert to normal. This will prevent like 20 simultaneous slow requests from bringing down the cluster.
var numberOfWorkers = 10;
var workerCount = 0;
var slowRequestPids = { };
if (cluster.isMaster) {
for(var i = 0; i < numberOfWorkers; i++) {
workerCount++;
cluster.fork();
}
cluster.on('exit', function(worker) {
workerCount--;
var pidString = String(worker.process.pid);
if(pidString in slowRequestPids) {
delete slowRequestPids[pidString];
if(workerCount >= numberOfWorkers) {
logger.info('not forking replacement for slow process');
return;
}
}
logger.info('forking replacement for a process that died unexpectedly');
workerCount++;
cluster.fork();
}
cluster.on("message", function(msg) {
if(typeof msg.fork != "undefined" && workerCount < 100) {
logger.info("forking additional process upon slow request");
slowRequestPids[msg.fork] = 1;
workerCount++;
cluster.fork();
}
});
return;
}
webserver.use("/slow", function(req, res) {
process.send({fork: String(process.pid) });
sleep.sleep(300);
res.send({ response_from: "virtual child" });
res.on("finish", function() {
logger.info('process exits, restoring cluster to original size');
process.exit();
});
});
I'm running a clustered node app, with 8 worker processes. I'm giving output when serving requests, and the output includes the ID of the process which handled the request:
app.get('/some-url', function(req, res) {
console.log('Request being handled by process #' + process.pid);
res.status(200).text('yayyy');
});
When I furiously refresh /some-url, I see in the output that the same process is handling the request every time.
I used node load-test to query my app. Again, even with 8 workers available, only one of them handles every single request. This is obviously undesirable as I wish to load-test the clustered app to see the overall performance of all processes working together.
Here's how I'm initializing the app:
var cluster = require('cluster');
if (cluster.isMaster) {
for (var i = 0; i < 8; i++) cluster.fork();
} else {
var app = require('express')();
// ... do all setup on `app`...
var server = require('http').createServer(app);
server.listen(8000);
}
How do I get all my workers working?
Your request does not use any ressources. I suspect that the same worker is always called, because it just finishes to handle the request before the next one comes in.
What happens if you do some calculation inside that takes more time than the time needed to handle a request ? As it stands, the worker is never busy between accepting a request and answering it.
I know that Node.js uses a single-thread and an event loop to process requests only processing one at a time (which is non-blocking). But i am unable to determine Event loop capacity to run 100k request per second.
Here i want to capacity planning for nodejs server to handle the 100k request per second.
Please let me know how can i determine the capacity of event loop to increase capacity.
A single instance of Node.js runs in a single thread. To take advantage of multi-core systems the user will sometimes want to launch a cluster of Node.js processes to handle the load.
More info here and here
For the reference check following code for simple implementation of cluster in node.js
var cluster = require('cluster');
var express = require('express');
var numCPUs = require('os').cpus().length;
if (cluster.isMaster) {
for (var i = 0; i < numCPUs; i++) {
// Create a worker
cluster.fork();
}
} else {
// Workers share the TCP connection in this server
var app = express();
app.get('/', function (req, res) {
res.send('Hello World!');
});
// All workers use this port
app.listen(8080);
}
Cluster is an extensible multi-core server manager for node.js for more source check here.
Code sample :
var cpuCoreLength = require("os").cpus().length;
var cluster = require("cluster");
if(cluster.isMaster){
cluster.setupMaster({
exec : "child.js"
});
var JOB_QUEUE=["data1","data2","data3"]; //for this post, value inserted manually.
for(var i=0;i<cpuCoreLength;i++){
var worker = cluster.fork();
worker.on("message",function(data){
if(data.type == "SEND_DATA"){
worker.send({"data":JOB_QUEUE[0]});
}
});
}
}
else
{
process.send("type":"SEND_DATA"});
process.on("message",function(data){
//Do the Process
});
}
Hi this is sample code for my process.In the above code JOB_QUEUE is data that to be processed by worker. when new worker created one data will be pushed to worker. Worker will use common file specified in the Master Setting. This is one copy of Master. I am going to create like 5 Master Code with different JOB_QUEUE but same child file. bcoz every master node going to handle different set of data and each master to be processing with 1000000 of data. To monitor data processed by worker purpose i created separate Master. My question, will it lead any performance Issue in Terms of CPU or due to CPU core if i run Multiple Master Node?