Qrly
A highly extensible buffer/queue with properly implemented asynchronicity. Based, in part, upon the inner-workings of queue in the async library.
tl;dr; Usage
Qlry implements a simple asynchronous loop with both buffer and queue semantics.
Setup
var queue = new Queue({
concurrency : 32,
flood : 64,
drain : 32
});
queue.worker = function(task, complete) {
var r = {};
try {
r.foo = task.a + task.b;
complete(null, r);
} catch(e) {
complete(e);
}
};
As a queue
queue.on('end', function(results) { ... });
queue.push([ { a : 1, b : 2 }, { a : 4, b : 0 }, null, { a : "A", b : null } ]);
The arguments passed to complete(...) in the worker will be pushed onto the results array in an object with the original task entity:
results.push({
task : { a : 1, b : 2 },
result : { foo : 3 },
error : null // Hopefully...
});
When the queue's task list (backlog) is emptied, and all tasks completed, an end event will be emitted with the results array as payload.
As a buffer
queue.collect = false;
queue.buffer({ "data" : [1, 2, 34, 4]}, function(err, res) { // Do Things; });
Setting collect to false keeps results from being saved internally. Only one task at a time can be passed to buffer(...). The second argument (a function) will be called by complete(...) in the worker, above, when it finishes processing the the respective task.
When the queue's backlog becomes longer than the flood attribute a flood event will be emitted. When the length drops below the drain attribute, a drain event will be emitted.
Tests
Install Mocha
npm install -g mocha
Run
./bin/test
Theory
For those unfamiliar with event loops. No hisses form the Java programmers please...
Consider traditional synchronous loops (while, for, each, ...): A common code body is executed serially while a condition is true, or for each element in a set. The next iteration cannot begin until the previous has completed (e.g. it blocks). This is generally a good thing if you want to, say, maintain consistent state within your program, know WTF your code is doing at any given time, or, maybe, do processor-intensive work.
But... What if you have I/O-intensive work? File access? REST requests? Database transactions? Synchronous interfaces will leave your processor idling while the program waits for a response. Asynchronous I/O is, fundamentally, intended to allow a program to use that idle time to do useful things... like making more async requests.
Node.JS gives us asynchronous I/O primitives. Good start; how would you go about making concurrent HTTP calls to an array of N URLs?
var HTTP = require('http');
var urls = [ "http://www.yahoo.com",
"http://www.linkedin.com",
"http://www.google.com",
"http://www.facebook.com" ];
urls.forEach(function(u) {
HTTP.get(u, function(res) {
console.log("I got a response for " + u);
});
});
console.log("I'm Out!");
All right, that works. Try running it a couple times. Hint: the order of responses probably changed. That's because the requests execute asynchronously.
"But Array.forEach(...) is synchronous! You said..."
Yes, you're right. forEach(...) did block and execute the requests in the order that they appear in the array, but HTTP.get(...) is asynchronous, and returns before its respective HTTP transaction completes, allowing all of the requests to be "in flight" at the same time. The order in which the callbacks are called depends mainly upon how fast the remote web servers can pony up bytes to complete their responses. In fact, none of the callbacks can be executed until the loop completes and the code after it returns. Functions are still atomic!
"Now... I want to execute something once all of those requests have called back. Oh, and I have 10,000 URLs to query. Only do 10 at a time so I don't exhaust my server's TCP socket resources." Umm, #@&*^�.
And we've found the problem: our good old synchronous control structures have no semantics for handling asynchronous flow. Clearly, we need something to do that... like a queue...
API
Constructor(options)Supportedoptionsinclude the following and map to similarly named attributes, below.pausedWhen truthy, sets the initial state of the queue to paused.collectconcurrencyflooded
Readonly Attributes
runnning: NumberCount of tasks that have been shifted off of the backlog queue, but have not yet called backtasks: Array[Object]Backlog of tasks that have not been startedresults: Array[Result]Aggregation ofResultsreturned by completed tasks. Theresultsarray will be returned as the payload ofendevents.flooded: BooleanState flag to indicate that the queue's backlog length is longer than thefloodattribute. Settrueinternally beforefloodedevents are emitted, andfalsebeforedrainevents.
Mutable Attributes
worker: Function(task, callback, meta)The default work function for the queue.callbackis passed a function that accepts two arguments:errorandresult. It must be called before the work function returns.matais an optional value that was passed into the queue with tasks inpush(...)orbuffer(...). It's primary use-case is to share a resource (e.g. database connection) between a block of tasks passed topush(...).paused: BooleanSame aspause()method, below. Once the queue has been instantiated, use of thepause()andresume()methods is preferred over setting the value ofpaused. (defaultfalse)collect: BooleanSave results and errors in theresultsarray (defaulttrue)concurrency: NumberHow many tasks to keep in-flight (default1)flood: NumberUpper threshold at which the queue enters the flooded state.bufferandpushwill return false when the backlog exceeds this value (default256)drain: NumberLower threshold at which thedrainevent is emitted (default1)
Methods
push(tasks[, meta[, callback(results)]])Add a task (or array of tasks) to the queue. If no callback is passed, the return value will be a boolean: false indicates that the 'flood' threshold has been exceeded. If a callback parameter is passed, the associated Group container will be returned.metais an optional value that will be passed to the worker with the respective task(s) being queued by the callcallback(results)will be called when all tasks in thetasksarray passed topushhave all been completed. The callback will be passed an array of result objects from the associated tasks. These tasks' results will not be added to the global results array, or passed toendevents.buffer(task, callback(err, result)[, meta[, worker]])Accepts a single task with a callback to be bound to that task.callback(err, res)Must accept two arguments:errorandresult. It will be called after the work function calls itscomplete(...)callback.- See
push(...)formetausages. workerwill override the queue's default work function.clear()Empty the results arraypause()Set thepausedattribute totrue. This will cause the internal loop to stop popping tasks off of the backlog and complete all running tasks. Callingpause()is preferred over setting thepausedattribute directly. Safe to call repeatedly.resume()Set thepausedattribute to false and restart the internal loop. Safe to call repeatedly.
Events
end: function([Result])Emitted when the backlog is emptied and all tasks completed. Payload contains an array of result and error entities returned by workers (ifcollectistrue)drain: function()Emitted when the backlog length becomes less than thedrainattribute
Changes
0.1.x -> 0.2.0
- Removed
flushableandcleanupattributes. The queue always acts as if both were true. - Renamed events
drainedtodrainandflushedtoendto better match the standard Node.JS API - Added task grouping.
pushaccepts a callback that will be called when all of the tasks in the previous argument are completed.
0.2.0 -> 0.3.0
- Introduces Task object to manage the life-cycle of a given task. Improves flow for task-specific workers,
- Group objects are returned by
pushif a callback is passed. Groups contain references to their constituent tasks, providing the ability to inspect the state of queued/running/completed tasks.
0.3.1
- Fix task.toJSON: Wasn't returning result object
0.3.2
- Add isCompleted to Group
MIT License
Copyright (c) 2013 John Manero, Dynamic Network Services
Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:
The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.
THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.