Reactive programming and thread sharing.

Javascript, Node.js, Go, Rails, Elixir and Erlang.

Rewind the clocks to Windows 3.1

In 1992 with Windows 3.1 we had this thing non-preemptive multitasking, i.e. “Cooperative Multitasking”. Cooperation is a funny term, it should actually be “Programmer Controlled Multitasking” because you don’t have to be cooperative if yo don’t want to :) There was an event loop that was controlled by the Windows system. You got message and you did work on those messages. We repeated the rules: don’t do any long computations, and if you have to do that, break it up into a state machine that is then driven by messages. And most of all don’t crash, because you will make users very unhappy.

In 1994 Microsoft started working on Windows NT. This was great, we had true pre-emptive multitasking. But thread creation and context switching was really slow. We could only spawn like 5 threads a second. So the “Fiber” was invented. This allowed threads to be shared. But fibers could not be pre-empted because they were not true threads.

The problems with fibers were the same problems that we had with non-preemptive multitasking all over again. Eventually thread creation and context switching got fast, and fibers were relegated to ‘special problems’. (Like external iterators in Ruby are nice with fibers)

Reactive programming is also known as non-blocking I/O, but it is not the same thing. Reactive programming has these characteristics:

It uses a central event loop to dispatch control,

It uses run-to-completion, i.e. there is no preemption,

Present Day and Reactive Programming

Operating systems are built around processes for reliability. Each (user mode) process is protected has its own memory and should not crash the entire system. Threads run concurrently but share memory. That’s the main different between a process and thread in a nutshell.

So, why the need for Node.js and ‘reactive’ style programming? Node.js works just like Windows 3.1. There is an event loop, each time you run, it runs to completion, meaning that the code that is running cannot be interrupted. So you have the same rules as we used back in Windows 3.1.

I’ve heard a few reasons:

Concurrency is hard, so by doing everything on a single thread we have no problem,

Thread scheduling is expensive, so by sharing a thread we gain efficiencies.

But at what cost?

Concurrency is Hard

Concurrency is hard. If you want concurrency you have two choices - processes or threads, take your pick. If you pick processes then concurrency is easy, but you can’t share memory. If you pick threads, then you can share memory, but you have to understand synchronization. If you pick neither, and run everything on a single thread, then you don’t have concurrency (you have an optimization).

Using a single thread with a dispatch loop is not concurrency. What you are doing is optimizing the use of a single thread. And by doing so, you must take over the role of thread scheduling, thread fairness, etc. Not only that, but in order to achieve any real concurrency you must run multiple instances of your application (processes) whether that makes sense or not.

Sequential Logic

Most programmers would agree that a sequential program, one that says do a) and then b) and then c):

10 A = 1 20 A = A + 1 30 PRINT "HELLO " + A 40 PRINT "YES" 50 GOTO 20

is easier to understand than one that breaks up the processing sequence just because b takes too long (and we don’t want everything else in the program to pause).

10 A = 1 20 A = A + 1 30 PRINT_NON_BLOCKING "HELLO" + "A", when done callback { LINE 40 } 40 PRINT "YES" 50 GOTO 20

In this example, the PRINT statement is very slow and uses I/O. So to avoid us blocking the entire program, we have call a non-blocking routine PRINT_NON_BLOCKING, and give it a callback on what to do when it is complete.

A common quiz for Javascript is to ask: which is printed first? “YES” or “HELLO3”? It’s always going to be “YES” first, because there is no way for the callback even to try to run until you give up the thread, i.e. run to completion. Actually, in this sillly example the callback can never run, because our code never returns :)

This means that the programmer must think about the scheduling in addition to the logic, even if the piece of code he/she is working doesn’t need to be ‘responsive’. Although, this does often result in faster executing programs because the programmer themselves optimize the context switching (i.e. where the callbacks are in Javascript).

If we wanted to do this in Elixir it would work like this:

10 A = 1 20 A = A + 1 30 PID = PRINT_NON_BLOCKING "HELLO" + "A" 40 PRINT "YES" 35 WAIT FOR MESSAGE ON PID 50 GOTO 20

I remember an article (where is it?) that showed that on Java using blocking threads was faster or basically equivalent to non-blocking I/O for most “things”. But that was up to 10K connections and processors were slower back then. Nowadays we have to do much better!

Starting Multiple Processes

Starting multiple processes in Node.js

The common configuration Node.js is that in order to achieve concurrency you start multiple instances of an application. But what if every process talks to a database. If your application is talking to a database, you might be able to start a maximum of 10 concurrent requests (handled by the driver). At the same time your database may have a maximum of 100 connections. If you arbitrarily add more instances you may be surprise that the 11th instance of your application causes things to start failing.

What you want is to say that your “application” can have a maximum of 100 connections to the database. How can you fairly share this across your separate processes?

Thread Sharing

Why is Node.js so popular, and why does it work so well?

Node.js was created because threads are once again too slow & expensive. Rails uses threads, and if you create 2000 threads you will find your system performance degraded. But the style of programming in Rails is great. Very clear sequential code, easy to understand. And if you use JRuby you get true multi-tasking.

Popular frameworks like Play on Scala achieve performance by mixing threads and reactive programming (callbacks). And if you read the text on the Play website, it states that the reason that it has reactive routines, i.e. shares requests on the same thread, is primarily for performance reasons. But watch of for nasty problems, like remember that you can’t do anything expensive in that callback or other things will stop that share the same thread.

Try as much as you can, anything that can get stuck will get stuck. Maybe it’s something as simple as a log statement, for example, the logger is now blocked writing to a file. The synchronous version worked in tests, but now something happened in production, the permissions were wrong, a backup has locked a file, etc., and everything pauses. (Not only what you’re trying to do - but everything else that coincidentally might be using the same thread.)

If you are running single threaded, then you have no other choice then to use some sort of reactive programming (i.e. event loop + callbacks), or some sort of yielding as is done with fibers because a single thread cannot be pre-empted by the system.

What if Processes Were Not Expensive?

What if processes were not expensive? Would you use them instead of callbacks (reactive)?

In Elixir processes are not expensive and they are protected in the same way operating system processes are protected. Of course you can have tons of asynchronous stuff happening, but if all your processes are waiting on I/O, for example waiting for a database request to complete, they all would be blocked. But blocking is not the problem.

it’s the expense & overhead of the process (or thread).

Node.js (Reactive programming) tell us that blocking is the problem that is being solved. Blocking is not the problem.

I’ve seen several articles about reactive programming with this kind of statement: rather than hog a thread even while it’s blocked . and don't hog the thread . The first thing that comes to my mind is, for example, “what else am I supposed to do when I’m waiting for a result from the database”? I can’t do anything else until I have that result. I need the result to make give to a template to give to the renderer, etc.

What are you hogging and from whom are you hogging it? These statements mislead coders into thinking that blocking is bad, when really the problem is that threads are a limited resource and context switching (between threads) is expensive. Just for clarity: there is nothing bad about blocking. If your code needs to wait for a result, then it needs to wait for a result. You can transpose this into a callback or promise, but you haven’t changed the logic.

If you block a thread that is implementing the user interface then the user interface would pause if is a single threaded user interface. Don’t do that. But that’s because the user interface is typically implemented as a single resource, and it makes sense for it to be synchronous.

In Elixir (thanks to Erlang) you have true pre-emptive multi-tasking, and processes are efficient and inexpensive. You don’t have to think about where to break up your code because of long-running tasks etc. And an errant processes can simply be shut down and restarted without taking down the entire system.

In Elixir most I/O functions block, so your code stays sequential. If you don’t want to wait, then don’t. Why might you not want to wait? Maybe you want to start 2 or 3 things in parallel, or maybe there is something useful you can do before you get your result from the blocking function, or maybe you are drawing a user interface and don’t want it to pause.

Any blocking function can easily be made non-blocking by simply wrapping it in a spawn() so that it starts asynchronously. In fact the logger in Elixir (Erlang) will automatically switch between synchronous and asynchronous modes based on the feedback it gets from the system.

The reason for not blocking is because:

You can do something useful in the meanwhile and get the result later,

Or, you don’t even care about the result.

It has nothing to do with hogging or stealing resources.

Erlang Processes

An Erlang process is not a system process. An Erlang process is a lightweight process. But here’s a key difference: there is no way in Erlang for processes to share memory, or mutate data. Data is always immutable, and never shared. People miss that point because most other languages talk about things you shouldn’t use, in Erlang those mechanism don’t exist.

So, yes, often Elixir is slower than Javascript because sometimes Erlang will interrupt a process and give control to another process even though it would have been more efficient not to do so. But this is all about fairness. Erlang wants all processes to play nicely, so no one process is allowed to hog the system.

Erlang (the VM) basically is an operating system: it is the scheduler. It is very difficult to make your own fair scheduler. Most languages won’t even try, and instead rely on the native threads and processes. And Javascript resorts to ‘thread-sharing’ when this performance is not good enough. Take a look at the Erlang scheduler and you see how difficult it is, and how elegantly Erlang solves this - from 30 years of experience!

Usually, at this point someone will say “Yes, that may be true, but between processes you’re going to have to do a lot of copying - sharing memory between threads is much more efficient”. This is true, but sharing memory is also a lot more dangerous and couples the code together.

Performance is great, but not when at the cost of safety

This is Erlang’s mantra: It is better to be safe, and fair, than it is to be fast. The world seems to be obsessed with performance. Elixir performs well, And it does that in a fair and safe manner.

You can read about that in one of my other posts: The world has changed

Short summary: Using Elixir doesn’t work well for everything, but you’d be surprised how often it does

Conclusion

It’s no wonder why programmers who have enough experience to remember the good old days of Windows 3.1 are not the biggest fans of Node.js. A tuned Windows 3.1 application often outperformed pre-emptive systems of the day!

Languages like Elixir offer both fully pre-emptive sequential programming (and are functional too), performance and protection. You get to focus on making your algorithms and logic, and not the scheduling - let the scheduler do the scheduling and you get on with your program. Wait if you want to, or don’t wait if you don’t want or don’t need to - take your pick. This is a joy to a programmer (or coder as we call them nowadays).

Event based programming is good, and is useful in a lot of situations. However, using it to share a thread because of the expense of having a thread is conflating the two concepts. If you are afraid of concurrency primitives, and you want concurrency you’ll be better served by Go. That’s why I see Go as mainly an alternative to Javascript Go provides a much safer way to do concurrency, but it still uses shared threads via Goroutines.

Thread sharing as a performance optimization is a temporary artifact, and will eventually fade away into the history books. Better still, don’t use threads at all, use processes that don’t/can’t share memory.

Afterward

Some of you web developers might be thinking: “yeah, true, but you need to keep things responsive for the user, so you do have to think about scheduling”.

Very true. However, a complete application, whether it is a desktop application or web application, usually does more than just respond to user clicks. There are long running reporting jobs, talking to external REST API services, etc. In Rails or Node.js it’s typically an all or nothing decision about what should be run on background tasks and requires using external databases like Redis, and external monitoring tools.

Elixir provides a much more predictive environment for your code. You can easily refactor code that was previously synchronous to run asynchronously with little changes to your sequential logic. Nothing prevents you from using Redis, etc., but use it only when you need a persistent task, not just because something needs to run asynchronusly.