How can I run a single method multiple times multi-threaded when called as a method of a class?
At first I tried to use the cluster module, but I realize it just re-runs the whole process from the start, rightfully so.
How can I achieve something like what's outlined below?
I want a class's method to spawn n processes, and when the parallel tasks are completed, I can resolve a promise which the method returns.
The problem with the code below is that calling cluster.fork() will fork index.js process.
index.js
const Person = require('./Person.js');
var Mary = new Person('Mary');
Mary.run(5).then(() => {...});
console.log('I should only run once, but I am called 5 times too many');
Person.js
const cluster = require('cluster');
class Person{
run(distance){
var completed = 0;
return new Promise((resolve, reject) => {
for(var i = 0; i < distance; i++) {
// run a separate process for each
cluster.fork().send(i).on('message', message => {
if (message === 'completed') { ++completed; }
if (completed === distance) { resolve(); }
});
}
});
}
}
I think the short answer is impossible. It's even worse - this has nothing to do with js. To multi (process or thread) in your particular problem you will essentially need a copy of the object in every thread, since it needs (maybe) access to fields - in this case you would need to either initialize it in every thread or share memory. That last one I don't think is provided in cluster, and not trivial in other languages in every use case.
If the calculation is independent of the Person I suggest you extract it, and use the usual (in index.js):
if(cluster.isWorker) {
//Use the i for calculation
} else {
//Create Person, then fork children in for loop
}
You then collect the results and change the Person as needed. You will be copying index.js, but this is standard and you only run what you need.
The problem is if results are dependent on Person. If these are constant for all i you can still send them to your forks independently. Otherwise what you have is the only way to fork. In general forking in cluster is not meant for methods, but for the app itself, which is the standard forking behavior.
Another solution
Following your comment, I suggest you checkout child_process.execFile or child_process.exec on same file.
This way you can spawn a totally independent process on the fly. Now instead of calling cluster.fork you call execFile. You can use either the exit code or stdout as return values (stderr etc.). Promise is now replaced with:
var results = []
for(var i = 0; i < distance; i++) {
// run a separate process for each
results.push(child_process.execFile().child.execFile('node', 'mymethod.js`,i]));
}
//... catch the exit event from all results or return a callback using results.
Inside mymethod.js Have your code that takes i and returns what you want either in the exit code or through stdout, both properties of the returned child_process. This is a bit un-node.js-y since you're waiting on asynchronous calls, but you're requirements are non standard. Since I'm not sure how you use this perhaps returning a callback with the array is a better idea.
Related
Basically, each of the clients ---that have a clientId associated with them--- can push messages and it is important that a second message from the same client isn't processed until the first one is finished processing (Even though the client can send multiple messages in a row, and they are ordered, and multiple clients sending messages should ideally not interfere with each other). And, importantly, a job shouldn't be processed twice.
I thought that using Redis I might be able to fix this issue, I started with some quick prototyping using the bull library, but I am clearly not doing it well, I was hoping someone would know how to proceed.
This is what I tried so far:
Create jobs and add them to the same queue name for one process, using the clientId as the job name.
Consume jobs while waiting large random amounts of random time on 2 separate process.
I tried adding the default locking provided by the library that I am using (bull) but it locks on the jobId, which is unique for each job, not on the clientId .
What I would want to happen:
One of the consumers can't take the job from the same clientId until the previous one is finished processing it.
They should be able to, however, get items from different clientIds in parallel without problem (asynchronously). (I haven't gotten this far, I am right now simply dealing with only one clientId)
What I get:
Both consumers consume as many items as they can from the queue without waiting for the previous item for the clientId to be completed.
Is Redis even the right tool for this job?
Example code
// ./setup.ts
import Queue from 'bull';
import * as uuid from 'uuid';
// Check that when a message is taken from a place, no other message is taken
// TO do that test, have two processes that process messages and one that sets messages, and make the job take a long time
// queue for each room https://stackoverflow.com/questions/54178462/how-does-redis-pubsub-subscribe-mechanism-works/54243792#54243792
// https://groups.google.com/forum/#!topic/redis-db/R09u__3Jzfk
// Make a job not be called stalled, waiting enough time https://github.com/OptimalBits/bull/issues/210#issuecomment-190818353
export async function sleep(ms: number): Promise<void> {
return new Promise((resolve) => {
setTimeout(resolve, ms);
});
}
export interface JobData {
id: string;
v: number;
}
export const queue = new Queue<JobData>('messages', 'redis://127.0.0.1:6379');
queue.on('error', (err) => {
console.error('Uncaught error on queue.', err);
process.exit(1);
});
export function clientId(): string {
return uuid.v4();
}
export function randomWait(minms: number, maxms: number): Promise<void> {
const ms = Math.random() * (maxms - minms) + minms;
return sleep(ms);
}
// Make a job not be called stalled, waiting enough time https://github.com/OptimalBits/bull/issues/210#issuecomment-190818353
// eslint-disable-next-line #typescript-eslint/ban-ts-comment
//#ts-ignore
queue.LOCK_RENEW_TIME = 5 * 60 * 1000;
// ./create.ts
import { queue, randomWait } from './setup';
const MIN_WAIT = 300;
const MAX_WAIT = 1500;
async function createJobs(n = 10): Promise<void> {
await randomWait(MIN_WAIT, MAX_WAIT);
// always same Id
const clientId = Math.random() > 1 ? 'zero' : 'one';
for (let index = 0; index < n; index++) {
await randomWait(MIN_WAIT, MAX_WAIT);
const job = { id: clientId, v: index };
await queue.add(clientId, job).catch(console.error);
console.log('Added job', job);
}
}
export async function create(nIds = 10, nItems = 10): Promise<void> {
const jobs = [];
await randomWait(MIN_WAIT, MAX_WAIT);
for (let index = 0; index < nIds; index++) {
await randomWait(MIN_WAIT, MAX_WAIT);
jobs.push(createJobs(nItems));
await randomWait(MIN_WAIT, MAX_WAIT);
}
await randomWait(MIN_WAIT, MAX_WAIT);
await Promise.all(jobs)
process.exit();
}
(function mainCreate(): void {
create().catch((err) => {
console.error(err);
process.exit(1);
});
})();
// ./consume.ts
import { queue, randomWait, clientId } from './setup';
function startProcessor(minWait = 5000, maxWait = 10000): void {
queue
.process('*', 100, async (job) => {
console.log('LOCKING: ', job.lockKey());
await job.takeLock();
const name = job.name;
const processingId = clientId().split('-', 1)[0];
try {
console.log('START: ', processingId, '\tjobName:', name);
await randomWait(minWait, maxWait);
const data = job.data;
console.log('PROCESSING: ', processingId, '\tjobName:', name, '\tdata:', data);
await randomWait(minWait, maxWait);
console.log('PROCESSED: ', processingId, '\tjobName:', name, '\tdata:', data);
await randomWait(minWait, maxWait);
console.log('FINISHED: ', processingId, '\tjobName:', name, '\tdata:', data);
} catch (err) {
console.error(err);
} finally {
await job.releaseLock();
}
})
.catch(console.error); // Catches initialization
}
startProcessor();
This is run using 3 different processes, which you might call like this (Although I use different tabs for a clearer view of what is happening)
npx ts-node consume.ts &
npx ts-node consume.ts &
npx ts-node create.ts &
I'm not familir with node.js. But for Redis, I would try this,
Let's say you have client_1, client_2, they are all publisher of events.
You have three machines, consumer_1,consumer_2, consumer_3.
Establish a list of tasks in redis, eg, JOB_LIST.
Clients put(LPUSH) jobs into this JOB_LIST, in a specific form, like "CLIENT_1:[jobcontent]", "CLIENT_2:[jobcontent]"
Each consumer takes out jobs blockingly (RPOP command of Redis) and process them.
For example, consumer_1 takes out a job, content is CLIENT_1:[jobcontent]. It parses the content and recognize it's from CLIENT_1. Then it wants to check if some other consumer is processing CLIENT_1 already, if not, it will lock the key to indicate that it's processing CLIENT_1.
It goes on to set a key of "CLIENT_1_PROCESSING" , with content as "consumer_1", using the Redis SETNX command (set if the key not exists), with an appropriate timeout. For example, the task norally takes one minute to finish, you set a timeout of the key of five minutes, just in case consumer_1 crashes and holds on the lock indefinitely.
If the SETNX returns 0, it means it fails to acquire the lock of CLIENT_1 (someone is already processing a job of client_1). Then it returns the job (a value of "CLIENT_1:[jobcontent]")to the left side of JOB_LIST, by using Redis LPUSH command.Then it might wait a bit (sleep a few seconds), and RPOP another task from the right side of the LIST. If this time SETNX returns 1, consumer_1 acquires the lock. It goes on to process job, after it finishes, it deletes the key of "CLIENT_1_PROCESSING", releasing the lock. Then it goes on to RPOP another job, and so on.
Some things to consider:
The JOB_LIST is not fair,eg, earlier jobs might be processed later
The locking part is a bit rudimentary, but will suffice.
----------update--------------
I've figured another way to keep tasks in order.
For each client(producer), build a list. Like "client_1_list", push jobs into the left side of the list.
Save all the client names in a list "client_names_list", with values "client_1", "client_2", etc.
For each consumer(processor), iterate the "client_names_list", for example, consumer_1 get a "client_1", check if the key of client_1 is locked(some one is processing a task of client_1 already), if not, right pop a value(job) from client_1_list and lock client_1. If client_1 is locked, (probably sleep one second) and iterate to the next client, "client_2", for example, and check the keys and so on.
This way, each client(task producer)'s task is processed by their order of entering.
EDIT: I found the problem regarding BullJS is starting jobs in parallel on one processor: We are using named jobs and where defining many named process functions on one queue/processor. The default concurrency factor for a queue/processor is 1. So the queue should not process any jobs in parallel.
The problem with our mentioned setup is if you define many (named) process-handlers on one queue the concurrency is added up with each process-handler function: So if you define three named process-handlers you get a concurrency factor of 3 for given queue for all the defined named jobs.
So just define one named job per queue for queues where parallel processing should not happen and all jobs should run sequentially one after the other.
That could be important e.g. when pushing a high number of jobs onto the queue and the processing involves API calls that would give errors if handled in parallel.
The following text is my first approach of answering the op's question and describes just a workaround to the problem. So better just go with my edit :) and configure your queues the right way.
I found an easy solution to operators question.
In fact BullJS is processing many jobs in parallel on one worker instance:
Let's say you have one worker instance up and running and push 10 jobs onto the queue than possibly that worker starts all processes in parallel.
My research on BullJS-queues gave that this is not intended behavior: One worker (also called processor by BullJS) should only start a new job from the queue when its in idle state so not processing a former job.
Nevertheless BullJS keeps starting jobs in parallel on one worker.
In our implementation that lead to big problems during API calls that most likely are caused by t00 many API calls at a time. Tests gave that when only starting one worker the API calls finished just fine and gave status 200.
So how to just process one job after the other once the previous is finished if BullJS does not do that for us (just what the op asked)?
We first experimented with delays and other BullJS options but thats kind of workaround and not the exact solution to the problem we are looking for. At least we did not get it working to stop BullJS from processing more than one job at a time.
So we did it ourself and started one job after the other.
The solution was rather simple for our use case after looking into BullJS API reference (BullJS API Ref).
We just used a for-loop to start the jobs one after another. The trick was to use BullJS's
job.finished
method to get a Promise.resolve once the job is finished. By using await inside the for-loop the next job gets just started immediately after the job.finished Promise is awaited (resolved). Thats the nice thing with for-loops: Await works in it!
Here a small code example on how to achieve the intended behavior:
for (let i = 0; i < theValues.length; i++) {
jobCounter++
const job = await this.processingQueue.add(
'update-values',
{
value: theValues[i],
},
{
// delay: i * 90000,
// lifo: true,
}
)
this.jobs[job.id] = {
jobType: 'socket',
jobSocketId: BackgroundJobTasks.UPDATE_VALUES,
data: {
value: theValues[i],
},
jobCount: theValues.length,
jobNumber: jobCounter,
cumulatedJobId
}
await job.finished()
.then((val) => {
console.log('job finished:: ', val)
})
}
The important part is really
await job.finished()
inside the for loop. leasingValues.length jobs get started all just one after the other as intended.
That way horizontally scaling jobs across more than one worker is not possible anymore. Nevertheless this workaround is okay for us at the moment.
I will get in contact with optimalbits - the maker of BullJS to clear things out.
This was running good for single call asynchronously:
"use strict";
function bashRun(commandList,stdoutCallback,completedCallback)
{
const proc=require("child_process");
const p=proc.spawn("bash");
p.stdout.on("data",function(data){
stdoutCallback(output);
});
p.on("exit",function(){
completedCallback();
});
p.stderr.on("data",function(err){
process.stderr.write("Error: "+err.toString("utf8"));
});
commandList.forEach(i=>{
p.stdin.write(i+"\n");
});
p.stdin.end();
}
module.exports.bashRun = bashRun;
But when inside a for loop, it doesn't. It just outputs only latest element(process)'s stdout info:
for(var i=0;i<20;i++)
{
var iLocal =i;
bashRun(myList,function(myStdout){ /* only result for iLocal=19 !*/},function(){});
}
I need this asynchronously (and also concurrently with multiple child processes) give output from each stdoutCallback functions to do some processing in it. While stdout doesn't work, completedCallback is called 20 times at least so there must be still 20 processes throughout some time slice but not sure if they existed on same slice of time.
What am I doing wrong so that spawned child processes can not give their output to nodejs? (why only last of them (i=19) can?)
I tried to exchange spawn with fork but now it gives error
p.stdout.on("data",function(data){
^
TypeError: Cannot read property 'on' of null
How can I use something else to retain same functionality of above module?
Looks like issue with scope value of i, try changing loop to use let.
Eg: for(let i=0;i<20;i++)
TL;DR
What is the best way to forcibly keep a Node.js process running, i.e., keep its event loop from running empty and hence keeping the process from terminating? The best solution I could come up with was this:
const SOME_HUGE_INTERVAL = 1 << 30;
setInterval(() => {}, SOME_HUGE_INTERVAL);
Which will keep an interval running without causing too much disturbance if you keep the interval period long enough.
Is there a better way to do it?
Long version of the question
I have a Node.js script using Edge.js to register a callback function so that it can be called from inside a DLL in .NET. This function will be called 1 time per second, sending a simple sequence number that should be printed to the console.
The Edge.js part is fine, everything is working. My only problem is that my Node.js process executes its script and after that it runs out of events to process. With its event loop empty, it just terminates, ignoring the fact that it should've kept running to be able to receive callbacks from the DLL.
My Node.js script:
var
edge = require('edge');
var foo = edge.func({
assemblyFile: 'cs.dll',
typeName: 'cs.MyClass',
methodName: 'Foo'
});
// The callback function that will be called from C# code:
function callback(sequence) {
console.info('Sequence:', sequence);
}
// Register for a callback:
foo({ callback: callback }, true);
// My hack to keep the process alive:
setInterval(function() {}, 60000);
My C# code (the DLL):
public class MyClass
{
Func<object, Task<object>> Callback;
void Bar()
{
int sequence = 1;
while (true)
{
Callback(sequence++);
Thread.Sleep(1000);
}
}
public async Task<object> Foo(dynamic input)
{
// Receives the callback function that will be used:
Callback = (Func<object, Task<object>>)input.callback;
// Starts a new thread that will call back periodically:
(new Thread(Bar)).Start();
return new object { };
}
}
The only solution I could come up with was to register a timer with a long interval to call an empty function just to keep the scheduler busy and avoid getting the event loop empty so that the process keeps running forever.
Is there any way to do this better than I did? I.e., keep the process running without having to use this kind of "hack"?
The simplest, least intrusive solution
I honestly think my approach is the least intrusive one:
setInterval(() => {}, 1 << 30);
This will set a harmless interval that will fire approximately once every 12 days, effectively doing nothing, but keeping the process running.
Originally, my solution used Number.POSITIVE_INFINITY as the period, so the timer would actually never fire, but this behavior was recently changed by the API and now it doesn't accept anything greater than 2147483647 (i.e., 2 ** 31 - 1). See docs here and here.
Comments on other solutions
For reference, here are the other two answers given so far:
Joe's (deleted since then, but perfectly valid):
require('net').createServer().listen();
Will create a "bogus listener", as he called it. A minor downside is that we'd allocate a port just for that.
Jacob's:
process.stdin.resume();
Or the equivalent:
process.stdin.on("data", () => {});
Puts stdin into "old" mode, a deprecated feature that is still present in Node.js for compatibility with scripts written prior to Node.js v0.10 (reference).
I'd advise against it. Not only it's deprecated, it also unnecessarily messes with stdin.
Use "old" Streams mode to listen for a standard input that will never come:
// Start reading from stdin so we don't exit.
process.stdin.resume();
Here is IFFE based on the accepted answer:
(function keepProcessRunning() {
setTimeout(keepProcessRunning, 1 << 30);
})();
and here is conditional exit:
let flag = true;
(function keepProcessRunning() {
setTimeout(() => flag && keepProcessRunning(), 1000);
})();
You could use a setTimeout(function() {""},1000000000000000000); command to keep your script alive without overload.
spin up a nice repl, node would do the same if it didn't receive an exit code anyway:
import("repl").then(repl=>
repl.start({prompt:"\x1b[31m"+process.versions.node+": \x1b[0m"}));
I'll throw another hack into the mix. Here's how to do it with Promise:
new Promise(_ => null);
Throw that at the bottom of your .js file and it should run forever.
I have a code snippet in nodejs like this:
in every 2 sec, foo() will be called.
function foo()
{
while (count < 10)
{
doSometing()
count ++;``
}
}
doSomething()
{
...
}
The limitation is, foo() has no callback.
How to make while loop execute and foo() completes without waiting for dosomething() to complete (call dosomething() and proceed), and dosomething() executes parallely?
I think, what you want is:
function foo()
{
while (count < 10)
{
process.nextTick(doSometing);
count ++;
}
}
process.nextTick will schedule the execution of doSometing on the next tick of the event loop. So, instead of switching immediately to doSometing this code will just schedule the execution and complete foo first.
You may also try setTimeout(doSometing,0) and setImmediate(doSometing). They'll allow I/O calls to occur before doSometing will be executed.
Passing arguments to doSomething
If you want to pass some parameters to doSomething, then it's best to ensure they'll be encapsulated and won't change before doSomething will be executed:
setTimeout(doSometing.bind(null,foo,bar),0);
In this case doSometing will be called with correct arguments even if foo and bar will be changed or deleted. But this won't work in case if foo is an object and you changes one of its properties.
What the alternatives are?
If you want doSomething to be executed in parallel (not just asynchronous, but actually in parallel), then you may be interested in some job-processing solution. I recommend you to look at kickq:
var kickq = require('kickq');
kickq.process('some_job', function (jobItem, data, cb) {
doSomething(data);
cb();
});
// ...
function foo()
{
while (count < 10)
{
kickq.create('some_job', data);
count ++;
}
}
kickq.process will create a separate process for processing your jobs. So, kickq.create will just register the job to be processed.
kickq uses redis to queue jobs and it won't work without it.
Using node.js build-in modules
Another alternative is building your own job-processor using Child Process. The resulting code may look something like this:
var fork = require('child_process').fork,
child = fork(__dirname + '/do-something.js');
// ...
function foo()
{
while (count < 10)
{
child.send(data);
count ++;
}
}
do-something.js here is a separate .js file with doSomething logic:
process.on('message', doSomething);
The actual code may be more complicated.
Things you should be aware of
Node.js is single-threaded, so it executes only one function at a time. It also can't utilize more then one CPU.
Node.js is asynchronous, so it's capable of processing multiple functions at once by switching between them. It's really efficient when dealing with functions with lots of I/O calls, because it's newer blocks. So, when one function waits for the response from DB, another function is executed. But node.js is not a good choice for blocking tasks with heavy CPU utilization.
It's possible to do real parallel calculations in node.js using modules like child_process and cluster. child_process allows you to start a new node.js process. It also creates a communication channel between parent and child processes. Cluster allows you to run a cluster of identical processes. It's really handy when you're dealing with http requests, because cluster can distribute them randomly between workers. So, it's possible to create a cluster of workers processing your data in parallel, though generally node.js is single-threaded.
I first tried a general description of the problem, then some more detail why the usual approaches don't work. If you would like to read these abstracted explanations go on. In the end I explain the greater problem and the specific application, so if you would rather read that, jump to "Actual application".
I am using a node.js child-process to do some computationally intensive work. The parent process does it's work but at some point in the execution it reaches a point where it must have the information from the child process before continuing. Therefore, I am looking for a way to wait for the child-process to finish.
My current setup looks somewhat like this:
importantDataCalculator = fork("./runtime");
importantDataCalculator.on("message", function (msg) {
if (msg.type === "result") {
importantData = msg.data;
} else if (msg.type === "error") {
importantData = null;
} else {
throw new Error("Unknown message from dataGenerator!");
}
});
and somewhere else
function getImportantData() {
while (importantData === undefined) {
// wait for the importantDataGenerator to finish
}
if (importantData === null) {
throw new Error("Data could not be generated.");
} else {
// we should have a proper data now
return importantData;
}
}
So when the parent process starts, it executes the first bit of code, spawning a child process to calculate the data and goes on doing it's own bit of work. When the time comes that it needs the result from the child process to continue it calls getImportantData(). So the idea is that getImportantData() blocks until the data is calculated.
However, the way I used doesn't work. I think this is due to me preventing the event loop from executing by using the while-loop. And since the Event-Loop does not execute no message from the child-process can be received and thus the condition of the while-loop can not change, making it an infinite loop.
Of course, I don't really want to use this kind of while-loop. What I would rather do is tell node.js "execute one iteration of the event loop, then get back to me". I would do this repeatedly, until the data I need was received and then continue the execution where I left of by returning from the getter.
I realize that his poses the danger of reentering the same function several times, but the module I want to use this in does almost nothing on the event loop except for waiting for this message from the child process and sending out other messages reporting it's progress, so that shouldn't be a problem.
Is there way to execute just one iteration of the event loop in Node.js? Or is there another way to achieve something similar? Or is there a completely different approach to achieve what I'm trying to do here?
The only solution I could think of so far is to change the calculation in such a way that I introduce yet another process. In this scenario, there would be the process calculating the important data, a process calculating the bits of data for which the important data is not needed and a parent process for these two, which just waits for data from the two child-processes and combines the pieces when they arrive. Since it does not have to do any computationally intensive work itself, it can just wait for events from the event loop (=messages) and react to them, forwarding the combined data as necessary and storing pieces of data that cannot be combined yet.
However this introduces yet another process and even more inter-process communication, which introduces more overhead, which I would like to avoid.
Edit
I see that more detail is needed.
The parent process (let's call it process 1) is itself a process spawned by another process (process 0) to do some computationally intensive work. Actually, it just executes some code over which I don't have control, so I cannot make it work asynchronously. What I can do (and have done) is make the code that is executed regularly call a function to report it's progress and provided partial results. This progress report is then send back to the original process via IPC.
But in rare cases the partial results are not correct, so they have to be modified. To do so I need some data I can calculate independently from the normal calculation. However, this calculation could take several seconds; thus, I start another process (process 2) to do this calculation and provide the result to process 1, via an IPC message. Now process 1 and 2 are happily calculating there stuff, and hopefully the corrective data calculated by process 2 is finished before process 1 needs it. But sometimes one of the early results of process 1 needs to be corrected and in that case I have to wait for process 2 to finish its calculation. Blocking the event loop of process 1 is theoretically not a problem, since the main process (process 0) would not be be affected by it. The only problem is, that by preventing the further execution of code in process 1 I am also blocking the event loop, which prevents it from ever receiving the result from process 2.
So I need to somehow pause the further execution of code in process 1 without blocking the event loop. I was hoping that there was a call like process.runEventLoopIteration that executes an iteration of the event loop and then returns.
I would then change the code like this:
function getImportantData() {
while (importantData === undefined) {
process.runEventLoopIteration();
}
if (importantData === null) {
throw new Error("Data could not be generated.");
} else {
// we should have a proper data now
return importantData;
}
}
thus executing the event loop until I have received the necessary data but NOT continuing the execution of the code that called getImportantData().
Basically what I'm doing in process 1 is this:
function callback(partialDataMessage) {
if (partialDataMessage.needsCorrection) {
getImportantData();
// use data to correct message
process.send(correctedMessage); // send corrected result to main process
} else {
process.send(partialDataMessage); // send unmodified result to main process
}
}
function executeCode(code) {
run(code, callback); // the callback will be called from time to time when the code produces new data
// this call is synchronous, run is blocking until the calculation is finished
// so if we reach this point we are done
// the only way to pause the execution of the code is to NOT return from the callback
}
Actual application/implementation/problem
I need this behaviour for the following application. If you have a better approach to achieve this feel free to propose it.
I want to execute arbitrary code and be notified about what variables it changes, what functions are called, what exceptions occur etc. I also need the location of these events in the code to be able to display the gathered information in the UI next to the original code.
To achieve this, I instrument the code and insert callbacks into it. I then execute the code, wrapping the execution in a try-catch block. Whenever the callback is called with some data about the execution (e.g. a variable change) I send a message to the main process telling it about the change. This way, the user is notified about the execution of the code, while it is running. The location information for the events generated by these callbacks is added to the callback call during the instrumentation, so that is not a problem.
The problem appears, when an exception occurs. I also want to notify the user about exceptions in the tested code. Therefore, I wrapped the execution of the code in a try-catch and any exceptions that get out of the execution are caught and send to the user interface. But the location of the errors is not correct. An Error object created by node.js has a complete call stack so it knows where it occurred. But this location if relative to the instrumented code, so I cannot use this location information as is, to display the error next to the original code. I need to transform this location in the instrumented code into a location in the original code. To do so, after instrumenting the code, I calculate a source map to map locations in the instrumented code to locations in the original code. However, this calculation might take several seconds. So, I figured, I would start a child process to calculate the source map, while the execution of the instrumented code is already started. Then, when an exception occurs, I check whether the source map has already been calculated, and if it hasn't I wait for the calculation to finish to be able to correct the location.
Since the code to be executed and watched can be completely arbitrary I cannot trivially rewrite it to be asynchronous. I only know that it calls the provided callback, because I instrumented the code to do so. I also cannot just store the message and return to continue the execution of the code, checking back during the next call whether the source map has been finished, because continuing the execution of the code would also block the event-loop, preventing the calculated source map from ever being received in the execution process. Or if it is received, then only after the code to execute has completely finished, which could be quite late or never (if the code to execute contains an infinite loop). But before I receive the sourceMap I cannot send further updates about the execution state. Combined, this means I would only be able to send the corrected progress messages after the code to execute has finished (which might be never) which completely defeats the purpose of the program (to enable the programmer to watch what the code does, while it executes).
Temporarily surrendering control to the event loop would solve this problem. However, that does not seem to be possible. The other idea I have is to introduce a third process which controls both the execution process and the sourceMapGeneration process. It receives progress messages from the execution process and if any of the messages needs correction it waits for the sourceMapGeneration process. Since the processes are independent, the controlling process can store the received messages and wait for the sourceMapGeneration process while the execution process continues executing, and as soon as it receives the source map, it corrects the messages and sends all of them off.
However, this would not only require yet another process (overhead) it also means I have to transfer the code once more between processes and since the code can have thousands of line that in itself can take some time, so I would like to move it around as little as possible.
I hope this explains, why I cannot and didn't use the usual "asynchronous callback" approach.
Adding a third ( :) ) solution to your problem after you clarified what behavior you seek I suggest using Fibers.
Fibers let you do co-routines in nodejs. Coroutines are functions that allow multiple entry/exit points. This means you will be able to yield control and resume it as you please.
Here is a sleep function from the official documentation that does exactly that, sleep for a given amount of time and perform actions.
function sleep(ms) {
var fiber = Fiber.current;
setTimeout(function() {
fiber.run();
}, ms);
Fiber.yield();
}
Fiber(function() {
console.log('wait... ' + new Date);
sleep(1000);
console.log('ok... ' + new Date);
}).run();
console.log('back in main');
You can place the code that does the waiting for the resource in a function, causing it to yield and then run again when the task is done.
For example, adapting your example from the question:
var pausedExecution, importantData;
function getImportantData() {
while (importantData === undefined) {
pausedExecution = Fiber.current;
Fiber.yield();
pausedExecution = undefined;
}
if (importantData === null) {
throw new Error("Data could not be generated.");
} else {
// we should have proper data now
return importantData;
}
}
function callback(partialDataMessage) {
if (partialDataMessage.needsCorrection) {
var theData = getImportantData();
// use data to correct message
process.send(correctedMessage); // send corrected result to main process
} else {
process.send(partialDataMessage); // send unmodified result to main process
}
}
function executeCode(code) {
// setup child process to calculate the data
importantDataCalculator = fork("./runtime");
importantDataCalculator.on("message", function (msg) {
if (msg.type === "result") {
importantData = msg.data;
} else if (msg.type === "error") {
importantData = null;
} else {
throw new Error("Unknown message from dataGenerator!");
}
if (pausedExecution) {
// execution is waiting for the data
pausedExecution.run();
}
});
// wrap the execution of the code in a Fiber, so it can be paused
Fiber(function () {
runCodeWithCallback(code, callback); // the callback will be called from time to time when the code produces new data
// this callback is synchronous and blocking,
// but it will yield control to the event loop if it has to wait for the child-process to finish
}).run();
}
Good luck! I always say it is better to solve one problem in 3 ways than solving 3 problems the same way. I'm glad we were able to work out something that worked for you. Admittingly, this was a pretty interesting question.
The rule of asynchronous programming is, once you've entered asynchronous code, you must continue to use asynchronous code. While you can continue to call the function over and over via setImmediate or something of the sort, you still have the issue that you're trying to return from an asynchronous process.
Without knowing more about your program, I can't tell you exactly how you should structure it, but by and large the way to "return" data from a process that involves asynchronous code is to pass in a callback; perhaps this will put you on the right track:
function getImportantData(callback) {
importantDataCalculator = fork("./runtime");
importantDataCalculator.on("message", function (msg) {
if (msg.type === "result") {
callback(null, msg.data);
} else if (msg.type === "error") {
callback(new Error("Data could not be generated."));
} else {
callback(new Error("Unknown message from sourceMapGenerator!"));
}
});
}
You would then use this function like this:
getImportantData(function(error, data) {
if (error) {
// handle the error somehow
} else {
// `data` is the data from the forked process
}
});
I talk about this in a bit more detail in one of my screencasts, Thinking Asynchronously.
What you are running into is a very common scenario that skilled programmers who are starting with nodejs often struggle with.
You're correct. You can't do this the way you are attempting (loop).
The main process in node.js is single threaded and you are blocking the event loop.
The simplest way to resolve this is something like:
function getImportantData() {
if(importantData === undefined){ // not set yet
setImmediate(getImportantData); // try again on the next event loop cycle
return; //stop this attempt
}
if (importantData === null) {
throw new Error("Data could not be generated.");
} else {
// we should have a proper data now
return importantData;
}
}
What we are doing, is that the function is re-attempting to process the data on the next iteration of the event loop using setImmediate.
This introduces a new problem though, your function returns a value. Since it will not be ready, the value you are returning is undefined. So you have to code reactively. You need to tell your code what to do when the data arrives.
This is typically done in node with a callback
function getImportantData(err,whenDone) {
if(importantData === undefined){ // not set yet
setImmediate(getImportantData.bind(null,whenDone)); // try again on the next event loop cycle
return; //stop this attempt
}
if (importantData === null) {
err("Data could not be generated.");
} else {
// we should have a proper data now
whenDone(importantData);
}
}
This can be used in the following way
getImportantData(function(err){
throw new Error(err); // error handling function callback
}, function(data){ //this is whenDone in our case
//perform actions on the important data
})
Your question (updated) is very interesting, it appears to be closely related to a problem I had with asynchronously catching exceptions. (Also Brandon and Ihad an interesting discussion with me about it! It's a small world)
See this question on how to catch exceptions asynchronously. The key concept is that you can use (assuming nodejs 0.8+) nodejs domains to constrain the scope of an exception.
This will allow you to easily get the location of the exception since you can surround asynchronous blocks with atry/catch. I think this should solve the bigger issue here.
You can find the relevant code in the linked question. The usage is something like:
atry(function() {
setTimeout(function(){
throw "something";
},1000);
}).catch(function(err){
console.log("caught "+err);
});
Since you have access to the scope of atry you can get the stack trace there which would let you skip the more complicated source-map usage.
Good luck!