I playing around with watches functionality and struggling to get it work.
The problem is that watch never fires, it simply not react to changes that I make for key in other transactions.
val key = new Tuple().add("watch-test").pack()
val watchExecuted = db.runAsync(tr => {
tr.set(key, new Tuple().add(1).pack())
tr.watch(key)
})
Thread.sleep(5000) // ensure that watch applied
db.run(tr => {
tr.set(key, new Tuple().add(2).pack())
})
watchExecuted.get() // never finish
Is anybody have any idea why watches do not react on changes as it supposed to do?
I think what's going on here is that your first transaction is never completing. It's maybe not obvious from the documentation, but runAsync won't return until the CompletableFuture returned in your function is ready. Because you are returning the watch future and not changing the value until after the transaction, it's never becoming ready and the transaction never ends.
If you replaced runAsync with run, I think it would work:
val watchExecuted = db.run(tr => {
tr.set(key, new Tuple().add(1).pack())
tr.watch(key)
})
If you wanted to use runAsync, then you would need to return your watch future wrapped in another object.
EDIT: or rather, if you want to use runAsync, you could return a CompletableFuture<CompletableFuture<Void>>:
var watchExecuted = db.runAsync(tr => {
tr.set(key, new Tuple().add(1).pack())
CompletableFuture.completedFuture(tr.watch(key))
});
Related
I have an application which checks for new entries in DB2 every 15 seconds on the iSeries using IBM's idb-connector. I have async functions which return the result of the query to socket.io which emits an event with the data included to the front end. I've narrowed down the memory leak to the async functions. I've read multiple articles on common memory leak causes and how to diagnose them.
MDN: memory management
Rising Stack: garbage collection explained
Marmelab: Finding And Fixing Node.js Memory Leaks: A Practical Guide
But I'm still not seeing where the problem is. Also, I'm unable to get permission to install node-gyp on the system which means most memory management tools are off limits as memwatch, heapdump and the like need node-gyp to install. Here's an example of what the functions basic structure is.
const { dbconn, dbstmt } = require('idb-connector');// require idb-connector
async function queryDB() {
const sSql = `SELECT * FROM LIBNAME.TABLE LIMIT 500`;
// create new promise
let promise = new Promise ( function(resolve, reject) {
// create new connection
const connection = new dbconn();
connection.conn("*LOCAL");
const statement = new dbstmt(connection);
statement.exec(sSql, (rows, err) => {
if (err) {
throw err;
}
let ticks = rows;
statement.close();
connection.disconn();
connection.close();
resolve(ticks.length);// resolve promise with varying data
})
});
let result = await promise;// await promise
return result;
};
async function getNewData() {
const data = await queryDB();// get new data
io.emit('newData', data)// push to front end
setTimeout(getNewData, 2000);// check again in 2 seconds
};
Any ideas on where the leak is? Am i using async/await incorrectly? Or else am i creating/destroying DB connections improperly? Any help on figuring out why this code is leaky would be much appreciated!!
Edit: Forgot to mention that i have limited control on the backend processes as they are handled by another team. I'm only retrieving the data they populate the DB with and adding it to a web page.
Edit 2: I think I've narrowed it down to the DB connections not being cleaned up properly. But, as far as i can tell I've followed the instructions suggested on their github repo.
I don't know the answer to your specific question, but instead of issuing a query every 15 seconds, I might go about this in a different way. Reason being that I don't generally like fishing expeditions when the environment can tell me an event occurred.
So in that vein, you might want to try a database trigger that loads the key to the row into a data queue on add, or even change or delete if necessary. Then you can just put in an async call to wait for a record on the data queue. This is more real time, and the event handler is only called when a record shows up. The handler can get the specific record from the database since you know it's key. Data queues are much faster than database IO, and place little overhead on the trigger.
I see a couple of potential advantages with this method:
You aren't issuing dozens of queries that may or may not return data.
The event would fire the instant a record is added to the table, rather than 15 seconds later.
You don't have to code for the possibility of one or more new records, it will always be 1, the one mentioned in the data queue.
yes you have to close connection.
Don't make const data. you don't need promise by default statement.exec is async and handles it via return result;
keep setTimeout(getNewData, 2000);// check again in 2 seconds
line outside getNewData otherwise it becomes recursive infinite loop.
Sample code
const {dbconn, dbstmt} = require('idb-connector');
const sql = 'SELECT * FROM QIWS.QCUSTCDT';
const connection = new dbconn(); // Create a connection object.
connection.conn('*LOCAL'); // Connect to a database.
const statement = new dbstmt(dbconn); // Create a statement object of the connection.
statement.exec(sql, (result, error) => {
if (error) {
throw error;
}
console.log(`Result Set: ${JSON.stringify(result)}`);
statement.close(); // Clean up the statement object.
connection.disconn(); // Disconnect from the database.
connection.close(); // Clean up the connection object.
return result;
});
*async function getNewData() {
const data = await queryDB();// get new data
io.emit('newData', data)// push to front end
setTimeout(getNewData, 2000);// check again in 2 seconds
};*
change to
**async function getNewData() {
const data = await queryDB();// get new data
io.emit('newData', data)// push to front end
};
setTimeout(getNewData, 2000);// check again in 2 seconds**
First thing to notice is possible open database connection in case of an error.
if (err) {
throw err;
}
Also in case of success connection.disconn(); and connection.close(); return boolean values that tell is operation successful (according to documentation)
Always possible scenario is to pile up connection objects in 3rd party library.
I would check those.
This was confirmed to be a memory leak in the idb-connector library that i was using. Link to github issue Here. Basically there was a C++ array that never had it's memory deallocated. A new version was added and the commit can viewed Here.
I am in a situation where I have a CRON task on google app engine (using flex environment) that just dies after some time, but I have no trace WHY (checked the GA Logs, nothing, tried try/catch, and explicitly log it - no error).
I have explicitly verified that if I create a cron task that runs for 8 minutes (but doesn't do much - just sleeps and updates database every second), it will run successfully. This is just to prove that CRON jobs can at least run 8 minutes if not more. & I have set up the Express & NodeJS combo up correctly.
This is all fine, but seems that my other cron job dies in 2-3 minutes, so quite fast. It is hitting some kind of limit, but I have no idea how to control for it, or even what limit it is, so all I can do is speculate.
I will tell more about my CRON task. It is basically rapidly querying MongoDB database where every query is quite fast. I've tried the same code locally, and there are no problems.
My speculation is that I am somehow creating too many MongoDB requests at once, and potentially running out of something?
Here's a pseudocode (just to describe what kind of scale data we're talking about - the numbers and flow are exactly the same):
function q1() {
return await mongoExecute(async (db) => {
const [l1, l2] = await Promise.all([
db.collection('Obj1').count({uid1: c1, u2action: 'L'}),
db.collection('Obj1').count({uid2: c2, u1action: 'L'}),
]);
return l1+l2;
});
}
for(let i = 0; i < 8000; i++) {
const allImportantInformation = Promise.all([
q1(),
q2(),
q3(),
.....
q10()
])
await mongoDb.saveToServer(document);
}
It is getting somewhere around i=1600 before the CRON job just dies without any explanation. The GA Cron Job panel clearly says the JOB has failed.
Here is also my mongoExecute (which is just a separate module that caches the db object, which hopefully is the correct practice in order to ensure that mongodb pooling works correctly.)
import { MongoClient, Db } from 'mongodb';
let db = null;
let promiseInProgress = null;
export async function mongoExecute<T> (executor: (instance: Db) => T): Promise<T | null> {
if (!db) {
if (!promiseInProgress) {
promiseInProgress = new Promise(async (resolve, reject) => {
const tempDb = await MongoClient.connect(process.env.MONGODB_URL);
resolve(tempDb);
});
}
db = await promiseInProgress;
}
try {
const value = await executor(db);
return value;
} catch (error) {
console.log(error);
return null;
}
}
What would be the solution? My idea is to basically ensure less requests are made at once (so all the promises would be sequential, and potentially add sleep between each cycle in the FOR.
I don't understand because it works fine up until some specific point (and quite big point, it's definitely different amount, sometimes it is 800, sometimes 1200, etc).
Is there any "running out of TCP connections" scenario happening? Theoretically we shouldn't run out of anything because we don't have much open at any given point.
It seems to be working if I throw 200ms wait between each cycle & I suspect I can figure out solution, all the items don't have to be updated in the same CRON execution, but it is a bit annoying, and I would like to know what's going on.
Is the garbage collector not catching up fast enough, why exactly is GA silently failing my cron task?
I discovered what the bug is, and fixed it accordingly.
Let me rephrase it; I have no idea what the bug was, and having no errors at any point was discouraging, however I managed to fix (lucky guess) whatever was happening by updating my nodejs mongodb driver to the latest version (from 2.xx -> 3.1.10).
No sleeps needed in my code anymore.
If I do this in node:
console.log('1');
console.log('2');
outputs:
1
2
And the process ends.
If I change it to this:
console.log('1');
var Firebase = require('firebase');
var ref = new Firebase('https://<some-base>.firebaseio.com/');
console.log('2');
outputs:
1
2
and the process continues.
I believe that this is because ref is keeping the process alive. I know that I can use process.exit but I would prefer to not do that. I actually don't want the process to exit anyway, I just want to make sure that I don't have a memory leak issue where my firebase ref lasts forever. Is there any way to destroy a firebase reference once I'm done with it?
[Engineer at Firebase] Currently, instantiating the Firebase client with new Firebase(...) will create a long-lived persistent connection that keeps the Node.js process alive.
This is admittedly not ideal for a bunch of use cases, and we have some work to do here to ensure that the process exits cleanly and automatically when there are no outstanding Firebase listeners or pending writes to the server, but it's been medium / low priority. I'd expect a "fix" to be released by Q2 '15, hopefully Q1.
One workaround I found when using tape was to call test.onFinish(() => process.exit()); at the end. It's not ideal but it seems to get the job done running it both directly and with a test runner.
Example:
const test = require('tape');
test('Some test', (t) => {
// test code
});
test('Another test', (t) => {
// test code
});
test.onFinish(() => process.exit());
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 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!