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My understanding is that threads exist as a way of doing several things in parallel that share the same address space but each has its individual stack. Asynchronous programming is basically a way of using fewer threads. I don't understand why it's undesirable to just have blocking calls and a separate thread for each blocked command?
For example, suppose I want to scrape a large part of the web. A presumably uncontroversial implementation might be to have a large number of asynchronous loops. Each loop would ask for a webpage, wait to avoid overloading the remote server, then ask for another webpage from the same website until done. The loops would then be executed on a much smaller number of threads (which is fine because they mostly wait). So to restate the question, I don't see why it's any cheaper to e.g. maintain a threadpool within the language runtime than it would be to just have one (mostly blocked) OS thread per loop and let the operating system deal with the complexity of scheduling the work? After all, if piling two different schedulers on top of each other is so good, it can still be implemented that way in the OS :-)
It seems obvious the answer is something like "threads are expensive". However, a thread just needs to keep track of where it has got to before it was interrupted the last time. This is pretty much exactly what an asynchronous command needs to know before it blocks (perhaps representing what happens next by storing a callback). I suppose one difference is that a blocking asynchronous command does so at a well defined point whereas a thread can be interrupted anywhere. If there really is a substantial difference in terms of the cost of keeping the state, where does it come from? I doubt it's the cost of the stack since that wastes at most a 4KB page, so it's a non-issue even for 1000s of blocked threads.
Many thanks, and sorry if the question is very basic. It might be I just cannot figure out the right incantation to type into Google.
Threads consume memory, as they need to have their state preserved even if they aren't doing anything. If you make an asynchronous call on a single thread, it's literally (aside from registering that the call was made somewhere) not consuming any resources until it needs to be resolved, because if it isn't actively being processed you don't care about it.
If the architecture of your application is written in a way that the resources it needs scale linearly (or worse) with the number of users / traffic you receive, then that is going to be a problem. You can watch this talk about node.js if you want to watch someone talk at length about this.
https://www.youtube.com/watch?v=ztspvPYybIY
I stumbled over node.js sometime ago and like it a lot. But soon I found out that it lacked badly the ability to perform CPU-intensive tasks. So, I started googling and got these answers to solve the problem: Fibers, Webworkers and Threads (thread-a-gogo). Now which one to use is a confusion and one of them definitely needs to be used - afterall what's the purpose of having a server which is just good at IO and nothing else? Suggestions needed!
UPDATE:
I was thinking of a way off-late; just needing suggestions over it. Now, what I thought of was this: Let's have some threads (using thread_a_gogo or maybe webworkers). Now, when we need more of them, we can create more. But there will be some limit over the creation process. (not implied by the system but probably because of overhead). Now, when we exceed the limit, we can fork a new node, and start creating threads over it. This way, it can go on till we reach some limit (after all, processes too have a big overhead). When this limit is reached, we start queuing tasks. Whenever a thread becomes free, it will be assigned a new task. This way, it can go on smoothly.
So, that was what I thought of. Is this idea good? I am a bit new to all this process and threads stuff, so don't have any expertise in it. Please share your opinions.
Thanks. :)
Node has a completely different paradigm and once it is correctly captured, it is easier to see this different way of solving problems. You never need multiple threads in a Node application(1) because you have a different way of doing the same thing. You create multiple processes; but it is very very different than, for example how Apache Web Server's Prefork mpm does.
For now, let's think that we have just one CPU core and we will develop an application (in Node's way) to do some work. Our job is to process a big file running over its contents byte-by-byte. The best way for our software is to start the work from the beginning of the file, follow it byte-by-byte to the end.
-- Hey, Hasan, I suppose you are either a newbie or very old school from my Grandfather's time!!! Why don't you create some threads and make it much faster?
-- Oh, we have only one CPU core.
-- So what? Create some threads man, make it faster!
-- It does not work like that. If I create threads I will be making it slower. Because I will be adding a lot of overhead to the system for switching between threads, trying to give them a just amount of time, and inside my process, trying to communicate between these threads. In addition to all these facts, I will also have to think about how I will divide a single job into multiple pieces that can be done in parallel.
-- Okay okay, I see you are poor. Let's use my computer, it has 32 cores!
-- Wow, you are awesome my dear friend, thank you very much. I appreciate it!
Then we turn back to work. Now we have 32 cpu cores thanks to our rich friend. Rules we have to abide have just changed. Now we want to utilize all this wealth we are given.
To use multiple cores, we need to find a way to divide our work into pieces that we can handle in parallel. If it was not Node, we would use threads for this; 32 threads, one for each cpu core. However, since we have Node, we will create 32 Node processes.
Threads can be a good alternative to Node processes, maybe even a better way; but only in a specific kind of job where the work is already defined and we have complete control over how to handle it. Other than this, for every other kind of problem where the job comes from outside in a way we do not have control over and we want to answer as quickly as possible, Node's way is unarguably superior.
-- Hey, Hasan, are you still working single-threaded? What is wrong with you, man? I have just provided you what you wanted. You have no excuses anymore. Create threads, make it run faster.
-- I have divided the work into pieces and every process will work on one of these pieces in parallel.
-- Why don't you create threads?
-- Sorry, I don't think it is usable. You can take your computer if you want?
-- No okay, I am cool, I just don't understand why you don't use threads?
-- Thank you for the computer. :) I already divided the work into pieces and I create processes to work on these pieces in parallel. All the CPU cores will be fully utilized. I could do this with threads instead of processes; but Node has this way and my boss Parth Thakkar wants me to use Node.
-- Okay, let me know if you need another computer. :p
If I create 33 processes, instead of 32, the operating system's scheduler will be pausing a thread, start the other one, pause it after some cycles, start the other one again... This is unnecessary overhead. I do not want it. In fact, on a system with 32 cores, I wouldn't even want to create exactly 32 processes, 31 can be nicer. Because it is not just my application that will work on this system. Leaving a little room for other things can be good, especially if we have 32 rooms.
I believe we are on the same page now about fully utilizing processors for CPU-intensive tasks.
-- Hmm, Hasan, I am sorry for mocking you a little. I believe I understand you better now. But there is still something I need an explanation for: What is all the buzz about running hundreds of threads? I read everywhere that threads are much faster to create and dumb than forking processes? You fork processes instead of threads and you think it is the highest you would get with Node. Then is Node not appropriate for this kind of work?
-- No worries, I am cool, too. Everybody says these things so I think I am used to hearing them.
-- So? Node is not good for this?
-- Node is perfectly good for this even though threads can be good too. As for thread/process creation overhead; on things that you repeat a lot, every millisecond counts. However, I create only 32 processes and it will take a tiny amount of time. It will happen only once. It will not make any difference.
-- When do I want to create thousands of threads, then?
-- You never want to create thousands of threads. However, on a system that is doing work that comes from outside, like a web server processing HTTP requests; if you are using a thread for each request, you will be creating a lot of threads, many of them.
-- Node is different, though? Right?
-- Yes, exactly. This is where Node really shines. Like a thread is much lighter than a process, a function call is much lighter than a thread. Node calls functions, instead of creating threads. In the example of a web server, every incoming request causes a function call.
-- Hmm, interesting; but you can only run one function at the same time if you are not using multiple threads. How can this work when a lot of requests arrive at the web server at the same time?
-- You are perfectly right about how functions run, one at a time, never two in parallel. I mean in a single process, only one scope of code is running at a time. The OS Scheduler does not come and pause this function and switch to another one, unless it pauses the process to give time to another process, not another thread in our process. (2)
-- Then how can a process handle 2 requests at a time?
-- A process can handle tens of thousands of requests at a time as long as our system has enough resources (RAM, Network, etc.). How those functions run is THE KEY DIFFERENCE.
-- Hmm, should I be excited now?
-- Maybe :) Node runs a loop over a queue. In this queue are our jobs, i.e, the calls we started to process incoming requests. The most important point here is the way we design our functions to run. Instead of starting to process a request and making the caller wait until we finish the job, we quickly end our function after doing an acceptable amount of work. When we come to a point where we need to wait for another component to do some work and return us a value, instead of waiting for that, we simply finish our function adding the rest of work to the queue.
-- It sounds too complex?
-- No no, I might sound complex; but the system itself is very simple and it makes perfect sense.
Now I want to stop citing the dialogue between these two developers and finish my answer after a last quick example of how these functions work.
In this way, we are doing what OS Scheduler would normally do. We pause our work at some point and let other function calls (like other threads in a multi-threaded environment) run until we get our turn again. This is much better than leaving the work to OS Scheduler which tries to give just time to every thread on system. We know what we are doing much better than OS Scheduler does and we are expected to stop when we should stop.
Below is a simple example where we open a file and read it to do some work on the data.
Synchronous Way:
Open File
Repeat This:
Read Some
Do the work
Asynchronous Way:
Open File and Do this when it is ready: // Our function returns
Repeat this:
Read Some and when it is ready: // Returns again
Do some work
As you see, our function asks the system to open a file and does not wait for it to be opened. It finishes itself by providing next steps after file is ready. When we return, Node runs other function calls on the queue. After running over all the functions, the event loop moves to next turn...
In summary, Node has a completely different paradigm than multi-threaded development; but this does not mean that it lacks things. For a synchronous job (where we can decide the order and way of processing), it works as well as multi-threaded parallelism. For a job that comes from outside like requests to a server, it simply is superior.
(1) Unless you are building libraries in other languages like C/C++ in which case you still do not create threads for dividing jobs. For this kind of work you have two threads one of which will continue communication with Node while the other does the real work.
(2) In fact, every Node process has multiple threads for the same reasons I mentioned in the first footnote. However this is no way like 1000 threads doing similar works. Those extra threads are for things like to accept IO events and to handle inter-process messaging.
UPDATE (As reply to a good question in comments)
#Mark, thank you for the constructive criticism. In Node's paradigm, you should never have functions that takes too long to process unless all other calls in the queue are designed to be run one after another. In case of computationally expensive tasks, if we look at the picture in complete, we see that this is not a question of "Should we use threads or processes?" but a question of "How can we divide these tasks in a well balanced manner into sub-tasks that we can run them in parallel employing multiple CPU cores on the system?" Let's say we will process 400 video files on a system with 8 cores. If we want to process one file at a time, then we need a system that will process different parts of the same file in which case, maybe, a multi-threaded single-process system will be easier to build and even more efficient. We can still use Node for this by running multiple processes and passing messages between them when state-sharing/communication is necessary. As I said before, a multi-process approach with Node is as well as a multi-threaded approach in this kind of tasks; but not more than that. Again, as I told before, the situation that Node shines is when we have these tasks coming as input to system from multiple sources since keeping many connections concurrently is much lighter in Node compared to a thread-per-connection or process-per-connection system.
As for setTimeout(...,0) calls; sometimes giving a break during a time consuming task to allow calls in the queue have their share of processing can be required. Dividing tasks in different ways can save you from these; but still, this is not really a hack, it is just the way event queues work. Also, using process.nextTick for this aim is much better since when you use setTimeout, calculation and checks of the time passed will be necessary while process.nextTick is simply what we really want: "Hey task, go back to end of the queue, you have used your share!"
(Update 2016: Web workers are going into io.js - a Node.js fork Node.js v7 - see below.)
(Update 2017: Web workers are not going into Node.js v7 or v8 - see below.)
(Update 2018: Web workers are going into Node.js Node v10.5.0 - see below.)
Some clarification
Having read the answers above I would like to point out that there is nothing in web workers that is against the philosophy of JavaScript in general and Node in particular regarding concurrency. (If there was, it wouldn't be even discussed by the WHATWG, much less implemented in the browsers).
You can think of a web worker as a lightweight microservice that is accessed asynchronously. No state is shared. No locking problems exist. There is no blocking. There is no synchronization needed. Just like when you use a RESTful service from your Node program you don't worry that it is now "multithreaded" because the RESTful service is not in the same thread as your own event loop. It's just a separate service that you access asynchronously and that is what matters.
The same is with web workers. It's just an API to communicate with code that runs in a completely separate context and whether it is in different thread, different process, different cgroup, zone, container or different machine is completely irrelevant, because of a strictly asynchronous, non-blocking API, with all data passed by value.
As a matter of fact web workers are conceptually a perfect fit for Node which - as many people are not aware of - incidentally uses threads quite heavily, and in fact "everything runs in parallel except your code" - see:
Understanding the node.js event loop by Mikito Takada
Understanding node.js by Felix Geisendörfer
Understanding the Node.js Event Loop by Trevor Norris
Node.js itself is blocking, only its I/O is non-blocking by Jeremy Epstein
But the web workers don't even need to be implemented using threads. You could use processes, green threads, or even RESTful services in the cloud - as long as the web worker API is used. The whole beauty of the message passing API with call by value semantics is that the underlying implementation is pretty much irrelevant, as the details of the concurrency model will not get exposed.
A single-threaded event loop is perfect for I/O-bound operations. It doesn't work that well for CPU-bound operations, especially long running ones. For that we need to spawn more processes or use threads. Managing child processes and the inter-process communication in a portable way can be quite difficult and it is often seen as an overkill for simple tasks, while using threads means dealing with locks and synchronization issues that are very difficult to do right.
What is often recommended is to divide long-running CPU-bound operations into smaller tasks (something like the example in the "Original answer" section of my answer to Speed up setInterval) but it is not always practical and it doesn't use more than one CPU core.
I'm writing it to clarify the comments that were basically saying that web workers were created for browsers, not servers (forgetting that it can be said about pretty much everything in JavaScript).
Node modules
There are few modules that are supposed to add Web Workers to Node:
https://github.com/pgriess/node-webworker
https://github.com/audreyt/node-webworker-threads
I haven't used any of them but I have two quick observations that may be relevant: as of March 2015, node-webworker was last updated 4 years ago and node-webworker-threads was last updated a month ago. Also I see in the example of node-webworker-threads usage that you can use a function instead of a file name as an argument to the Worker constructor which seems that may cause subtle problems if it is implemented using threads that share memory (unless the functions is used only for its .toString() method and is otherwise compiled in a different environment, in which case it may be fine - I have to look more deeply into it, just sharing my observations here).
If there is any other relevant project that implements web workers API in Node, please leave a comment.
Update 1
I didn't know it yet at the time of writing but incidentally one day before I wrote this answer Web Workers were added to io.js.
(io.js is a fork of Node.js - see: Why io.js decided to fork Node.js, an InfoWorld interview with Mikeal Rogers, for more info.)
Not only does it prove the point that there is nothing in web workers that is against the philosophy of JavaScript in general and Node in particular regarding concurrency, but it may result in web workers being a first class citizen in server-side JavaScript like io.js (and possibly Node.js in the future) just as it already is in client-side JavaScript in all modern browsers.
Update 2
In Update 1 and my tweet I was referring to io.js pull request #1159
which now redirects to
Node PR #1159
that was closed on Jul 8 and replaced with Node PR #2133 - which is still open.
There is some discussion taking place under those pull requests that may provide some more up to date info on the status of Web workers in io.js/Node.js.
Update 3
Latest info - thanks to NiCk Newman for posting it in
the comments: There is the workers: initial implementation commit by Petka Antonov from Sep 6, 2015
that can be downloaded and tried out in
this tree. See comments by NiCk Newman for details.
Update 4
As of May 2016 the last comments on the still open PR #2133 - workers: initial implementation were 3 months old. On May 30 Matheus Moreira asked me to post an update to this answer in the comments below and he asked for the current status of this feature in the PR comments.
The first answers in the PR discussion were skeptical but later
Ben Noordhuis wrote that "Getting this merged in one shape or another is on my todo list for v7".
All other comments seemed to second that and as of July 2016 it seems that Web Workers should be available in the next version of Node, version 7.0 that is planned to be released on October 2016 (not necessarily in the form of this exact PR).
Thanks to Matheus Moreira for pointing it out in the comments and reviving the discussion on GitHub.
Update 5
As of July 2016 there are few modules on npm that were not available before - for a complete list of relevant modules, search npm for workers, web workers, etc. If anything in particular does or doesn't work for you, please post a comment.
Update 6
As of January 2017 it is unlikely that web workers will get merged into Node.js.
The pull request #2133 workers: initial implementation by Petka Antonov from July 8, 2015 was finally closed by Ben Noordhuis on December 11, 2016 who commented that "multi-threading support adds too many new failure modes for not enough benefit" and "we can also accomplish that using more traditional means like shared memory and more efficient serialization."
For more information see the comments to the PR 2133 on GitHub.
Thanks again to Matheus Moreira for pointing it out in the comments.
Update 6
I'm happy to announce that few days ago, in June 2018 web workers appeared in Node v10.5.0 as an experimental feature activated with the --experimental-worker flag.
For more info, see:
Node v10.5.0 release blog post
Pull Request #20876 - worker: initial implementation by Anna Henningsen
My original tweet of happiness when I learned that this got into v10.5.0:
🎉🎉🎉 Finally! I can make the 7th update to my 3 year old Stack Overflow answer where I argue that threading a la web workers is not against Node philosophy, only this time saying that we finally got it! 😜👍
I come from the old school of thought where we used multi-threading to make software fast. For past 3 years i have been using Node.js and a big supporter of it. As hasanyasin explained in detail how node works and the concept of asyncrous functionality. But let me add few things here.
Back in the old days with single cores and lower clock speeds we tried various ways to make software work fast and parallel. in DOS days we use to run one program at a time. Than in windows we started running multiple applications (processes) together. Concepts like preemptive and non-preemptive (or cooperative) where tested. we know now that preemptive was the answer for better multi-processing task on single core computers. Along came the concepts of processes/tasks and context switching. Than the concept of thread to further reduce the burden of process context switching. Thread where coined as light weight alternative to spawning new processes.
So like it or not signal thread or not multi-core or single core your processes will be preempted and time sliced by the OS.
Nodejs is a single process and provides async mechanism. Here jobs are dispatched to under lying OS to perform tasks while we waiting in an event loop for the task to finish. Once we get a green signal from OS we perform what ever we need to do. Now in a way this is cooperative/non-preemptive multi-tasking, so we should never block the event loop for a very long period of time other wise we will degrade our application very fast.
So if there is ever a task that is blocking in nature or is very time consuming we will have to branch it out to the preemptive world of OS and threads.
there are good examples of this is in the libuv documentation. Also if you read the documentation further you find that FileI/O is handled in threads in node.js.
So Firstly its all in the design of our software. Secondly Context switching is always happening no matter what they tell you. Thread are there and still there for a reason, the reason is they are faster to switch in between then processes.
Under hood in node.js its all c++ and threads. And node provides c++ way to extend its functionality and to further speed out by using threads where they are a must i.e., blocking tasks such as reading from a source writing to a source, large data analysis so on so forth.
I know hasanyasin answer is the accepted one but for me threads will exist no matter what you say or how you hide them behind scripts, secondly no one just breaks things in to threads just for speed it is mostly done for blocking tasks. And threads are in the back bone of Node.js so before completely bashing multi-threading is in correct. Also threads are different from processes and the limitation of having node processes per core don't exactly apply to number of threads, threads are like sub tasks to a process. in fact threads won;t show up in your windows task manager or linux top command. once again they are more little weight then processes
I'm not sure if webworkers are relevant in this case, they are client-side tech (run in the browser), while node.js runs on the server. Fibers, as far as I understand, are also blocking, i.e. they are voluntary multitasking, so you could use them, but should manage context switches yourself via yield. Threads might be actually what you need, but I don't know how mature they are in node.js.
worker_threads has been implemented and shipped behind a flag in node#10.5.0. It's still an initial implementation and more efforts are needed to make it more efficient in future releases. Worth giving it a try in latest node.
In many Node developers' opinions one of the best parts of Node is actually its single-threaded nature. Threads introduce a whole slew of difficulties with shared resources that Node completely avoids by doing nothing but non-blocking IO.
That's not to say that Node is limited to a single thread. It's just that the method for getting threaded concurrency is different from what you're looking for. The standard way to deal with threads is with the cluster module that comes standard with Node itself. It's a simpler approach to threads than manually dealing with them in your code.
For dealing with asynchronous programming in your code (as in, avoiding nested callback pyramids), the [Future] component in the Fibers library is a decent choice. I would also suggest you check out Asyncblock which is based on Fibers. Fibers are nice because they allow you to hide callback by duplicating the stack and then jumping between stacks on a single-thread as they're needed. Saves you the hassle of real threads while giving you the benefits. The downside is that stack traces can get a bit weird when using Fibers, but they aren't too bad.
If you don't need to worry about async stuff and are more just interested in doing a lot of processing without blocking, a simple call to process.nextTick(callback) every once in a while is all you need.
Maybe some more information on what tasks you are performing would help. Why would you need to (as you mentioned in your comment to genericdave's answer) need to create many thousands of them? The usual way of doing this sort of thing in Node is to start up a worker process (using fork or some other method) which always runs and can be communicated to using messages. In other words, don't start up a new worker each time you need to perform whatever task it is you're doing, but simply send a message to the already running worker and get a response when it's done. Honestly, I can't see that starting up many thousands of actual threads would be very efficient either, you are still limited by you CPUs.
Now, after saying all of that, I have been doing a lot of work with Hook.io lately which seems to work very well for this sort of off-loading tasks into other processes, maybe it can accomplish what you need.
I was going through the details of node.jsand came to know that, It supports asynchronous programming though essentially it provides a single threaded model.
How is asynchronous programming handled in such cases? Is it like runtime itself creates and manages threads, but the programmer cannot create threads explicitly? It would be great if someone could point me to some resources to learn about this.
Say it with me now: async programming does not necessarily mean multi-threaded.
Javascript is a single-threaded runtime - you simply aren't able to create new threads in JS because the language/runtime doesn't support it.
Frank says it correctly (although obtusely) In English: there's a main event loop that handles when things come into your app. So, "handle this HTTP request" will get added to the event queue, then handled by the event loop when appropriate.
When you call an async operation (a mysql db query, for example), node.js sends "hey, execute this query" to mysql. Since this query will take some time (milliseconds), node.js performs the query using the MySQL async library - getting back to the event loop and doing something else there while waiting for mysql to get back to us. Like handling that HTTP request.
Edit: By contrast, node.js could simply wait around (doing nothing) for mysql to get back to it. This is called a synchronous call. Imagine a restaurant, where your waiter submits your order to the cook, then sits down and twiddles his/her thumbs while the chef cooks. In a restaurant, like in a node.js program, such behavior is foolish - you have other customers who are hungry and need to be served. Thus you want to be as asynchronous as possible to make sure one waiter (or node.js process) is serving as many people as they can.
Edit done
Node.js communicates with mysql using C libraries, so technically those C libraries could spawn off threads, but inside Javascript you can't do anything with threads.
Ryan said it best: sync/async is orthogonal to single/multi-threaded. For single and multi-threaded cases there is a main event loop that calls registered callbacks using the Reactor Pattern. For the single-threaded case the callbacks are invoked sequentially on main thread. For the multi-threaded case they are invoked on separate threads (typically using a thread pool). It is really a question of how much contention there will be: if all requests require synchronized access to a single data structure (say a list of subscribers) then the benefits of having multiple threaded may be diminished. It's problem dependent.
As far as implementation, if a framework is single threaded then it is likely using poll/select system call i.e. the OS is triggering the asynchronous event.
To restate the waiter/chef analogy:
Your program is a waiter ("you") and the JavaScript runtime is a kitchen full of chefs doing the things you ask.
The interface between the waiter and the kitchen is mediated by queues so requests are not lost in instances of overcapacity.
So your program is assigned one thread of execution. You can only wait one table at a time. Each time you want to offload some work (like making the food/making a network request), you run to the kitchen and pin the order to a board (queue) for the chefs (runtime) to pick-up when they have spare capacity. The chefs will let you know when the order is ready (they will call you back). In the meantime, you go wait another table (you are not blocked by the kitchen).
So the accepted answer is misleading. The JavaScript runtime is definitionally multithreaded because I/O does not block your JavaScript program. As a waiter you can continue serving customers, while the kitchen cooks. That involves at least two threads of execution. The reality is that the runtime will maintain several threads of execution behind the scenes, in order to efficiently serve the single thread directly corresponding to your script.
By design, only one thread of execution is assigned to the synchronous running of your JavaScript program. This is a good thing because it makes your program easier to reason about than having to handle multiple threads of execution yourself. Don't worry: your JavaScript program can still get plenty complicated though!
As multi-processor and multi-core computers become more and more ubiquitous, is simply firing off a new thread a (relatively) simple and painless way of simplifying code? For instance, in a current personal project, I have a network server listening on a port. Since this is just a personal project, it's just a desktop app, with a GUI integrated into it for configuration. So, the app reads something like this:
Main()
Read configuration
Start listener thread
Run GUI
Listener Thread
While the app is running
Wait for a new connection
Run a client thread for the new connection
Client Thread
Write synchronously
Read synchronously
ad inifinitum, or till they disconnect
This approach means that while I have to worry about alot of locking, with the potential issues that involves, I avoid alot of spaghetti code from assynchronous calls, etc.
A slightly more insidious version of this came up today when I was working on the startup code. The startup was quick, but it was using lazy loading for alot of the configuration, which meant that while startup was quick, actually connecting to and using the service was difficult because of the lag while it loaded different sections (this was actually measurable in real time, up to 3-10 seconds sometimes). So I moved to a different strategy, on startup, loop through everything and force the lazy loading to kick in... but this made it start prohibitively slow; get up, go get a coffee slow. Final solution: throw the loop into a seperate thread with feedback in the system tray while it's still loading.
Is this "Meh, throw it in another thread, it'll be fine" attitude ok? At what point do you start getting diminishing returns and/or even reduced performance?
Multithreading does a lot of things, but I don't think "simplification" is ever one of them.
It's a great way to introduce bugs into code.
Using multiple threads properly is not easy. It should not be attempted by new developers.
In my opinion, multi-threaded programming is pretty high up on the difficulty (and complexity) scale, along with memory management. To me, the "Meh, throw it in another thread, it'll be fine" attitude is a bit too casual. Think long and hard you must, before forking threads you do.
No.
Plainly and simply, multithreading increases complexity and is a nearly trivial way to add bugs to code. There are concurrency issues such as synchronization, deadlock, race conditions, and priority inversion to name a few.
Secondly, the performance gains are not automatic. Recently, there was an excellent article in MSDN Magazine along these lines. The salient details are that a certain operation was taking 46 seconds per ten iterations coded as a single-threaded operation. The author parallelized the operation naively (one thread per four cores) and the operation dropped to 30 seconds per ten iterations. Sounds great until you take into consideration that the operation now eats 300% more processing power but only experienced a 34% gain in efficiency. It's not worth consuming all available processing power for a gain like that.
This gives you the extra job of debugging race conditions, and handling locks and sycronisation issues.
I would not use this unless there was a real need.
Read up on Amdahl's law, best summarized by "The speedup of a program using multiple processors in parallel computing is limited by the time needed for the sequential fraction of the program."
As it turns out, if only a small part of your app can run in parallel you won't get much gains, but potentially many hard-to-debug bugs.
I don't mean to be flip but what's in that configuration file that it takes so long to load? That's the origin of your problem, right?
Before spawning another thread to handle it, perhaps it can be parred down? Reduced, perhaps put in another data format that would be quicker, etc?
How often does it change? Is it something you can parse once at the beginning of the day and put the variables in shared memory so subsequent runs of your main program can just attach and get the needed values from there?
While I agree with everyone else here in saying that multithreading does not simplify code, it can be used to greatly simplify the user experience of your application.
Consider an application that has a lot of interactive widgets (I am currently developing one where this helps) - in the workflow of my application, a user can "build" the current project they are working on. This requires disabling the interactive widgets my application presents to the user and presenting a dialog with a indeterminate progress bar and a friendly "please wait" message.
The "build" occurs on a background thread; if it were to happen on the UI thread it would make the user experience less enjoyable - after all, it's no fun not being able to tell whether or not you are able to click on a widget in an application while a background task is running (cough, Visual Studio). Not to say that VS doesn't use background threads, I'm just saying their user experience could use some improvement. But I digress.
The one thing I take issue with in the title of your post is that you think of firing off threads when you need to perform tasks - I generally prefer to reuse threads - in .NET, I generally favor using the system thread pool over creating a new thread each time I want to do something, for the sake of performance.
I'm going to provide some balance against the unanimous "no".
DISCLAIMER: Yes, threads are complicated and can cause a whole bunch of problems. Everyone else has pointed this out.
From experience, a sequence of blocking reads/writes to a socket (which requires a separate thead) is much simpler than non-blocking ones. With blocking calls, you can tell the state of the connection just by looking at where you are in the function. With non-blocking calls, you need a bunch of variables to record the state of the connection, and check and modify them every time you interact with the connection. With blocking calls, you can just say "read the next X bytes" or "read until you find X" and it will actually do it (or fail). With non-blocking calls, you have to deal with fragmented data which usually requires keeping temporary buffers and filling them as necessary. You also end up checking if you've received enough data every time you receive little more. Plus you have to keep a list of open connections and handle unexpected closes for all of them.
It doesn't get much simpler than this:
void WorkerThreadMain(Connection connection) {
Request request = ReadRequest(connection);
if(!request) return;
Reply reply = ProcessRequest(request);
if(!connection.isOpen) return;
SendReply(reply, connection);
connection.close();
}
I'd like to note that this "listener spawns off a worker thread per connection" pattern is how web servers are designed, and I assume it's how a lot of request/response soft of server applications are designed.
So in conclusion, I have experienced the asynchronous socket spaghetti code you mentioned, and spawning off worker threads for every connection ended up being a good solution. Having said all this, throwing threads at a problem should usually be your last resort.
I think your have no choice but to deal with threads especially with networking and concurrent connections. Do threads make code simpler? I don't think so. But without them how would you program a server that can handle more than 1 client at the same time?
How do you make your application multithreaded ?
Do you use asynch functions ?
or do you spawn a new thread ?
I think that asynch functions are already spawning a thread so if your job is doing just some file reading, being lazy and just spawning your job on a thread would just "waste" ressources...
So is there some kind of design when using thread or asynch functions ?
If you are talking about .Net, then don't forget the ThreadPool. The thread pool is also what asynch functions often use. Spawning to much threads can actually hurt your performance. A thread pool is designed to spawn just enough threads to do the work the fastest. So do use a thread pool instead of spwaning your own threads, unless the thread pool doesn't meet your needs.
PS: And keep an eye out on the Parallel Extensions from Microsoft
Spawning threads is only going to waste resources if you start spawning tons of them, one or two extra threads isn't going to effect the platforms proformance, infact System currently has over 70 threads for me, and msn is using 32 (I really have no idea how a messenger can use that many threads, exspecialy when its minimised and not really doing anything...)
Useualy a good time to spawn a thread is when something will take a long time, but you need to keep doing something else.
eg say a calculation will take 30 seconds. The best thing to do is spawn a new thread for the calculation, so that you can continue to update the screen, and handle any user input because users will hate it if your app freezes untill its finished doing the calculation.
On the other hand, creating threads to do something that can be done almost instantly is nearly pointless, since the overhead of creating (or even just passing work to an existing thread using a thread pool) will be higher than just doing the job in the first place.
Sometimes you can break your app into a couple of seprate parts which run in their own threads. For example in games the updates/physics etc may be one thread, while grahpics are another, sound/music is a third, and networking is another. The problem here is you really have to think about how these parts will interact or else you may have worse proformance, bugs that happen seemingly "randomly", or it may even deadlock.
I'll second Fire Lancer's answer - creating your own threads is an excellent way to process big tasks or to handle a task that would otherwise be "blocking" to the rest of synchronous app, but you have to have a clear understanding of the problem that you must solve and develope in a way that clearly defines the task of a thread, and limits the scope of what it does.
For an example I recently worked on - a Java console app runs periodically to capture data by essentially screen-scraping urls, parsing the document with DOM, extracting data and storing it in a database.
As a single threaded application, it, as you would expect, took an age, averaging around 1 url a second for a 50kb page. Not too bad, but when you scale out to needing to processes thousands of urls in a batch, it's no good.
Profiling the app showed that most of the time the active thread was idle - it was waiting for I/O operations - opening of a socket to the remote URL, opening a connection to the database etc. It's this sort of situation that can easily be improved with multithreading. Rewriting to be multi-threaded and with just 5 threads instead of one, even on a single core cpu, gave an increase in throughput of over 20 times.
In this example, each "worker" thread was explicitly limited to what it did - open the remote a remote url, parse the data, store it in the db. All the "high level" processing - generating the list of urls to parse, working out which next, handling errors, all remained with the control of the main thread.
The use of threads makes you think more about the way your application needs threading and can in the long run make it easier to improve / control your performance.
Async methods are faster to use but they are a bit magic - a lot of things happen to make them possible - so it's probable that at some point you will need something that they can't give you. Then you can try and roll some custom threading code.
It all depends on your needs.
The answer is "it depends".
It depends on what you're trying to achieve. I'm going to assume that you're aiming for more performance.
The simplest solution is to find another way to improve your performance. Run a profiler. Look for hot spots. Reduce unnecessary IO.
The next solution is to break your program into multiple processes, each of which can run in their own address space. This is easiest because there is no chance of the individual processes messing each other up.
The next solution is to use threads. At this point you're opening a major can of worms, so start small, and only multi-thread the critical path of the code.
The next solution is to use asynch IO. Generally only recommended for people writing some of very heavily loaded server, and even then I would rather re-use one of the existing frameworks that abstract away the details e.g. the C++ framework ICE, or an EJB server under java.
Note that each of these solutions has multiple sub-solutions - there are different breeds of threads and different kinds of asynch IO, each with slightly different performance characteristics, but again, it's generally best to let the framework handle it for you.