ncd v0.0.6
Early draft
ncd – not central dispatch
ncd is a library to support asynchronous C++ node addons. It provides a number of primitives to work with the UV thread pool. The library uses semantics familiar to every node developer. It allows for a very casual coding style while still facilitating the development of reusable components.
The core principle of ncd is: Pass code, not data. The user dispatches code to run on the pool or the main thread respectively. The user can choose from plain functions, callable objects or lambda expressions. Anything callable will work.
If you are unfamiliar with lambda expressions read the 20 seconds primer now.
Appetizer
Let's take a look at a first example, the implementation of a simple worker:
void
eventEmittingWorker(Nan::FunctionCallbackInfo<Value> const& args) {
unsigned delay = args[0]->Uint32Value();
unsigned iterations = args[1]->Uint32Value();
ncd::AsyncEventEmitter emitter(args[2].As<v8::Object>()); // ①
ncd::defaultWorkQueue().dispatch([=](){ // ②
for (unsigned i = 0; i < iterations; ++i) {
emitter.emit("progress", i); // ③
usleep(delay);
}
}, std::bind(emitter.emit, "done")); // ④
}After grabbing some arguments the code creates an AsyncEventEmitter in (1). It wraps a javascript EventEmitter for use on a different thread. In (2) a lambda expression is dipatched to the thread pool. The expression captures copies of delay, iterations and the emitter. This is an ncd pattern: An AsyncSomething is first allocated on the main thread and then copied around to different threads. The call to dispatch(...) returns immediately and the lambda is launched on the thread pool. In (3) the async event emitter is invoked, sending progress events back to javascript. After the execution finishes the callback passed in (4) is invoked on the main thread. Here we just emit a done event.
The javascript code looks like this:
const workers = require('workers')
, EventEmitter = require('events')
, ee = new EventEmitter()
. on('progress', (p) => { console.log('progress', p) })
. on('done', () => { console.log('done') })
workers.eventEmittingWorker(10000, 10, ee)Concepts
Callbacks
Like node, ncd uses callbacks. Alot. The code to be run on the thread and the done handler are callbacks as are the asynchronous requests to the main thread. Basically, everything is a callback. Two basic forms of callbacks are supported: Free functions and callable objects:
void done() {}
void free_function() {}
struct CallableObject {
void operator()() {}
};
void
doWork(Nan::FunctionCallbackInfo<Value> const& args) {
ncd::defaultWorkQueue().dispatch(free_function, done);
ncd::defaultWorkQueue().dispatch(CallableObject(), done);
}The key difference is that callable objects have state. Note that we actually construct an object in the second call to dispatch(...). We can use it to pass initial parameters to the work we run on a different thread:
struct WorkWithParam {
WorkWithParam(int theParam) : mParam(theParam) {}
void operator()() { std::cerr << "parameter: " << mParam << std::endl; }
int mParam;
};
void
doWork(Nan::FunctionCallbackInfo<Value> const& args) {
ncd::defaultWorkQueue().dispatch(WorkWithParam(5), done);
}Unlike more traditional C++ callback APIs, ncd callbacks don't necessarily have a fixed signature. Some of them are very flexible and the user can choose from a number of options. This is documented in the reference.
Since ncd is intentionally unspecific about the callback types virtually all C++ callables will work as long as they have a matching signature. This includes callables returned by C++ standard utilities like std::bind(...). In the appetizer above an event name is tied to the asynchronous event emitter. The result is directly used as a done handler.
Lambda Expressions
What about lambda expressions? Isn't that a third kind of callback? Well, yes. You can use lambda expressions as callbacks as shown in the first example. And no, they are not a new kind of callable. What happens is this: The compiler analyzes the lambda and checks if it captures any variables. If it does not capture anything the compiler creates a hidden function. Else it creates a hidden class for a callable object. The object has the necessary members to hold the captured values.
The basic work example covers all three callback flavours.
Queues
At the core of ncd are two types of queues. The user dispatches code to a queue and the code is executed on the other side of a thread boundary.
WorkQueues run code on the thread pool. Although there currently is only one default work queue, this will become a fully user constructable type. Each work queue has a maximum number of threads it will use in parallel. A queue with a maximum thread count of one will execute all items sequentially while queues with more threads execute items concurrently. The default queue uses UV_THREADPOOL_SIZE - 4 threads, with a minimum of one. That is, it is a sequential queue until you start to give it more threads by setting UV_THREADPOOL_SIZE.
Code executing on the thread pool has access to an instance of MainQueue. Code dispatched on this type of queue is executed on the main thread and can use the javascript engine.
std::thread::id threadId() { return std::this_thread::get_id(); }
void
workFunction(Nan::FunctionCallbackInfo<Value> const& args) {
std::cerr << "main thread " << threadId() << std::endl;
ncd::defaultWorkQueue().dispatch([](){
std::cerr << "pool thread " << threadId() << std::endl;
ncd::mainQueue().dispatch([](){
std::cerr << "main thread " << threadId() << std::endl;
});
}, done);
}These pairs of queues provide a generic, bidirectional inter-thread facility not unsimilar to apple's grand central dispatch. Both, the apple and the libuv event loop have a notion of a main thread. They both provide a thread pool. However, as the name suggests the similarities only go so far.
If you are familiar with libuv programming you already guessed it. Behind the scenes the work queue deals with items of type uv_work_t. The main queue handles the other direction and holds a uv_async_t that is the backchannel for the current work function.
Queue Invariants
WorkQueues always launch their work in sequential orderWorkQueues with a single thread are strictly sequential. The previous item is finished before the next item is launched.MainQueues are always strictly sequential- Additionally, all items dispatched on a
MainQueueare executed before the done handler.
Handles
ncd introduces AsyncHandle<>s. These handles are used to keep javascript objects alive while work is executing on a thread. This solves many common housekeeping tasks in an unobtrusive way:
void
workFunction(Nan::FunctionCallbackInfo<Value> const& args) {
ncd::AsyncHandle<v8::Object> pinnedObject(args[0].As<v8::Object>()); // ①
ncd::defaultWorkQueue().dispatch([=](){ // ②
for (unsigned i = 0; i < 10; ++i) {
usleep(10000);
ncd::mainQueue().dispatch([=](){ // ③
Nan::HandleScope scope;
v8::Local<v8::Object> object = pinnedObject.jsValue(); // ④
object->Set(Nan::New("progress").ToLocalChecked(), Nan::New(i));
});
}
}, done);
}The code creates an AsyncHandle<v8::Object> in (1) pinning an object for later use. The handle is copied
to the worker thread in (2) and back to the main thread in (3). Finally, back on the main thread the javascript value is extracted in (4). The code above can be found in the main queue examples.
Utilities
AsyncFunctions are thread-safe wrappers of javascript functions. They are invoked like regular functions but behind the scenes they emit an event on the main thread and invoke the javascript function there.
Appendices
C++ Lambda Expression Primer
Since C++11 there is a new way to write C++ callbacks: lambda expressions. Like javasscript functions lambda expressions can be defined inline within another function. Also like with javascript, they can capture values from their parent scopes. Assume the following ES6 arrow function:
var f = (status) => { return status >= 0 }
f(5)The equivalent C++ lambda expression looks like this:
auto f = [](int status) { return status >= 0; };
f(5);We traded an arrow for a pair of brackets, but the similarities are obvious, right? The currently empty brackets are used to tell the compiler what variables are captured and how. It is called the capture list. The examples most commonly use a capture list that consists of a single equal sign:
int minimum = 0;
auto f = [=](int status) { return status >= minimum; };This instructs the compiler to capture all variables we use. In javascript that is the default. It will capture them by copy and not by reference. The lambda above holds a copy of minimum. With ncd the containing function often returns immediately, destroying all local variables. So, copying is the way to go.
Since this is C++ the actual details of lambda expressions are quite baroque. Please refer to the wider web for additional tutorials.
Design Notes
ncd hides many of the more daunting details of libuv/C++ multi-threading. It employs C++ best practices to arrive at an API that feels familiar to node/javascript developers. The goal here is to be as javascripty as possible without creating awkward C++ or (unwarrented) overhead. It aims to be a semantic fusion without bending things to far.
- By using C++ callables as the core abstraction, we gain flexibility. Mixing and matching free functions, callable objects and lambda expressions gives us a semantic reach similar to javascript functions. We can keep state, use inline syntax and capture variables. ncd also follows nodes signature for callbacks: error first, result second.
- ncd tries to avoid burdening the user with housekeeping tasks. It mostly uses automatic RAII-style memory management. In general it avoids user-facing symmetries like new/delete, lock/unlock, &c. Anything the user has to remember is bad, because we tend to forget.
- ncd directly implements a number of high level components from the node universe, event emitters and streams and makes them available to multi-threaded addons. The hope is that reusing these familiar async primitives will make it easier to reason about these addons.
Code Walkthrough
ncd core consists of three basic primitives: WorkQueue, MainQueue, and AsyncHandle. Everything else is either standalone or build on top of the core.
Main Queue
A natural place to start reading is work_queue.hpp. The queue files each contain the actual queue class like WorkQueue and the items managed by that queue: WorkRequestBase and the derieved template `WorkRequest<...>. This is an interesting (albeit not new) pattern. A template derieves from an abstract base class filling in the pure virtual functions:
struct Base {
virtual ~Base() {}
virtual void doThing() = 0;
};
template <typename Callable>
struct Derieved : Base {
void doThing() override { /* do things depending on Callable */ }
};Note how this is similar to the current AsyncWorker. Except that from the users point of view the derieved type is automatically generated to fit the callable. Think of the pattern as a polymorphic factory. Given this setup, we can stuff pointers to the base class into standard containers and do things with them without knowing about the actual callable.
Work Queue
The class WorkRequestBase manages the MainQueue for a given work function. Looking through main_queue.hpp you'll see it's much less complex and uses a similar pattern like the WorkQueue.