Skip to content

C++ Parallel Computing and Asynchronous Networking Engine

License

Notifications You must be signed in to change notification settings

cixingguangming55555/workflow

 
 

Repository files navigation

中文版入口

Sogou C++ Workflow

License Language Platform Build Status

As Sogou`s C++ server engine, Sogou C++ Workflow supports almost all back-end C++ online services of Sogou, including all search services, cloud input method,online advertisements, etc., handling more than 10 billion requests every day. This is an enterprise-level programming engine in light and elegant design which can satisfy most C++ back-end development requirements.

You can use it:

  • To quickly build an HTTP server:
#include <stdio.h>
#include "workflow/WFHttpServer.h"

int main()
{
    WFHttpServer server([](WFHttpTask *task) {
        task->get_resp()->append_output_body("<html>Hello World!</html>");
    });

    if (server.start(8888) == 0) { // start server on port 8888
        getchar(); // press "Enter" to end.
        server.stop();
    }

    return 0;
}
  • As a multifunctional asynchronous client, it currently supports HTTP, Redis, MySQL and Kafka protocols.
  • To implement client/server on user-defined protocol and build your own RPC system.
    • srpc is based on it and it is an independent open source project, which supports srpc, brpc, trpc and thrift protocols.
  • To build asynchronous workflow; support common series and parallel structures, and also support any DAG structures.
  • As a parallel computing tool. In addition to networking tasks, Sogou C++ Workflow also includes the scheduling of computing tasks. All types of tasks can be put into the same flow.
  • As a asynchronous file IO tool in Linux system, with high performance exceeding any system call. Disk file IO is also a task.
  • To realize any high-performance and high-concurrency back-end service with a very complex relationship between computing and networking.
  • To build a micro service system.
    • This project has built-in service governance and load balancing features.

Compiling and running environment

  • This project supports Linux, macOS, Windows, Android and other operating systems.
    • Windows version is currently released as an independent branch, using iocp to implement asynchronous networking. All user interfaces are consistent with the Linux version.
  • Supports all CPU platforms, including 32 or 64-bit x86 processors, big-endian or little-endian arm processors.
  • Relies on OpenSSL; OpenSSL 1.1 and above is recommended. If you don't like SSL, you may checkout the nossl branch. But still need to link crypto for md5 and sha1.
  • Uses the C++11 standard and therefore, it should be compiled with a compiler which supports C++11. Does not rely on boost or asio.
  • No other dependencies. However, if you need Kafka protocol, some compression libraries should be installed, including lz4, zstd and snappy.

Get started (Linux, macOS):

$ git clone https://github.com/sogou/workflow
$ make
$ cd tutorial
$ make

Tutorials

System design features

We believe that a typical back-end program=protocol+algorithm+workflow and should be developed completely independently.

  • Protocol
    • In most cases, users use built-in common network protocols, such as HTTP, Redis or various rpc.
    • Users can also easily customize user-defined network protocol. In the customization, they only need to provide serialization and deserialization functions to define their own client/server.
  • Algorithm
    • In our design, the algorithm is a concept symmetrical to the protocol.
      • If protocol call is rpc, then algorithm call is an apc (Async Procedure Call).
    • We have provided some general algorithms, such as sort, merge, psort, reduce, which can be used directly.
    • Compared with a user-defined protocol, a user-defined algorithm is much more common. Any complicated computation with clear boundaries should be packaged into an algorithm.
  • Workflow
    • Workflow is the actual bussiness logic, which is to put the protocols and algorithms into the flow graph for use.
    • The typical workflow is a closed series-parallel graph. Complex business logic may be a non-closed DAG.
    • The workflow graph can be constructed directly or dynamically generated based on the results of each step. All tasks are executed asynchronously.

Basic task, task factory and complex task

  • Our system contains six basic tasks: networking, file IO, CPU, GPU, timer, and counter.
  • All tasks are generated by the task factory and automatically recycled after callback.
    • Server task is one kind of special networking task, generated by the framework which calls the task factory, and handed over to the user through the process function.
  • In most cases, the task generated by the user through the task factory is a complex task, which is transparent to the user.
    • For example, an HTTP request may include many asynchronous processes (DNS, redirection), but for user, it is just a networking task.
    • File sorting seems to be an algorithm, but it actually includes many complex interaction processes between file IO and CPU computation.
    • If you think of business logic as building circuits with well-designed electronic components, then each electronic component may be a complex circuit.

Asynchrony and encapsulation based on C++11 std::function

  • Not based on user mode coroutines. Users need to know that they are writing asynchronous programs.
  • All calls are executed asynchronously, and there are almost no operation that occupys a thread.
    • Although we also provide some facilities with semi-synchronous interfaces, they are not core features.
  • We try to avoid user's derivations, and encapsulate user behavior with std::function instead, including:
    • The callback of any task.
    • Any server's process. This conforms to the FaaS (Function as a Service) idea.
    • The realization of an algorithm is simply a std::function. But the algorithm can also be implemented by derivation.

Memory reclamation mechanism

  • Every task will be automatically reclaimed after the callback. If a task is created but a user does not want to run it, the user needs to release it through the dismiss method.
  • Any data in the task, such as the response of the network request, will also be recycled with the task. At this time, the user can use std::move() to move the required data.
  • SeriesWork and ParallelWork are two kinds of framework objects, which are also recycled after their callback.
    • When a series is a branch of a parallel, it will be recycled after the callback of the parallel that it belongs to.
  • This project doesn’t use std::shared_ptr to manage memory.

More design documents

To be continued...

About

C++ Parallel Computing and Asynchronous Networking Engine

Resources

License

Code of conduct

Stars

Watchers

Forks

Packages

No packages published

Languages

  • C++ 79.7%
  • C 18.6%
  • CMake 1.3%
  • Makefile 0.4%