• Stars
    star
    1,905
  • Rank 23,329 (Top 0.5 %)
  • Language
    C++
  • License
    Other
  • Created over 7 years ago
  • Updated about 1 year ago

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Repository Details

A simple C++ based RPC framework.

PhxRPC是微信后台团队推出的一个非常简洁小巧的RPC框架,编译生成的库只有450K。

作者: Sifan Liu, Haochuan Cui 和 Duokai Huang

联系我们:[email protected]

想了解更多, 以及更详细的编译手册,请进入中文WIKI,和扫描右侧二维码关注我们的公众号

PhxRPCBuild Status

总览

  • 使用Protobuf作为IDL用于描述RPC接口以及通信数据结构。
  • 基于Protobuf文件自动生成Client以及Server接口,用于Client的构建,以及Server的实现。
  • 半同步半异步模式,采用独立多IO线程,通过Epoll管理请求的接入以及读写,工作线程采用固定线程池。IO线程与工作线程通过内存队列进行交互。
  • 支持协程Worker,可配置多个线程,每个线程多个协程。
  • 提供完善的过载保护,无需配置阈值,支持动态自适应拒绝请求。
  • 提供简易的Client/Server配置读入方式。
  • 基于lambda函数实现并发访问Server,可以非常方便地实现Google提出的 Backup Requests 模式。

局限

  • 不支持多进程模式。

性能

使用Sample目录下的Search RPC C/S进行Echo RPC调用的压测,相当于Worker空转情况。

运行环境

CPU:24 x Intel(R) Xeon(R) CPU E5-2620 v3 @ 2.40GHz 内存:32 GB 网卡:千兆网卡 Client/Server机器之间PING值: 0.05ms 请求写入并发:1000个线程 业务数据大小:除去HTTP协议部分20b Worker线程数:20

性能测试结果(qps)

短连接

ucontext类型/IO线程 1 3 8 20
system 41k 85k 90k 92k
boost 45k 95k 95k 95k

长连接

ucontext类型/IO线程 1 3 8 20
system 55k 160k 360k 500k
boost 62k 175k 410k 500k

如何编译

Protobuf准备

PhxRPC必须依赖的第三方库只有Protobuf。在编译前,在third_party目录放置好protobuf目录,或者通过软链的形式。

boost优化

PhxRPC在ServerIO以及Client并发连接管理上使用了ucontext,而boost的ucontext实现要比system默认的更为高效,推荐使用boost。如果需要使用boost的话需要在third_party目录放置好boost目录,或者通过软链的形式。

编译环境

  • Linux
  • GCC-4.8及以上版本
  • boost 1.56及以上版本(可选)

编译安装方法

进入PhxRPC根目录。

make (默认是-O2编译,如需编译debug版,执行 make debug=y)
make boost (可选,编译PhxRPC的boost优化插件,编译之前先准备好boost库)

如何使用

编写proto文件

下面是sample目录下的proto文件样例。

syntax = "proto3";
package search;
import "google/protobuf/wrappers.proto";
import "google/protobuf/empty.proto";
import "phxrpc/phxrpc.proto";

enum SiteType {
    BLOG = 0;
    NEWS = 1;
    VIDEO = 2;
    UNKNOWN = 3;
}

message Site {
    string url = 1;
    string title = 2;
    SiteType type = 3;
    tring summary = 4;
}

message SearchRequest {
    string query = 1;
}

message SearchResult {
    repeated Site sites = 1;
}

service Search {
    rpc Search(SearchRequest) returns (SearchResult) {
        option(phxrpc.CmdID) = 1;
        option(phxrpc.OptString) = "q:";
        option(phxrpc.Usage) = "-q <query>";
    }
    rpc Notify(google.protobuf.StringValue) returns (google.protobuf.Empty) {
        option(phxrpc.CmdID) = 2;
        option(phxrpc.OptString) = "m:";
        option(phxrpc.Usage) = "-m <msg>";
    }
}

生成代码

(PhxRPC根目录)/codegen/phxrpc_pb2server -I (PhxRPC根目录) -I (Protobuf include目录) -f (proto文件路径) -d (生成代码放置路径)

# sample
../codegen/phxrpc_pb2server -I ../ -I ../third_party/protobuf/include -f search.proto -d .
../codegen/phxrpc_pb2server -I ../ -I ../third_party/protobuf/include -f search.proto -d . -u

两种生成模式,区别在于-u参数。

第一种生成默认的线程池worker模型。

第二种-u参数指定生成uthread worker模型,也就是工作线程池里面每个线程里面运行着多个协程。

调用完工具后,在生成代码放置目录下执行make,即可生成全部的RPC相关代码。

选择是否启用Boost优化

打开生成代码放置目录下的Makefile文件。

# choose to use boost for network
#LDFLAGS := $(PLUGIN_BOOST_LDFLAGS) $(LDFLAGS)

可以看到以上两行,取消注释掉第二行,重新make clean && make即可开启Boost对PhxRPC的优化。开启前记得编译好PhxRPC的Boost插件。

补充自己的代码

Server(xxx_service_impl.cpp)

int SearchServiceImpl::PHXEcho(const google::protobuf::StringValue &req,
        google::protobuf::StringValue *resp) {
    resp->set_value(req.value());
    return 0;
}

int SearchServiceImpl::Search(const search::SearchRequest &req,
        search::SearchResult *resp) {
    // 这里补充这个RPC调用的Server端代码
    return -1;
}

int SearchServiceImpl::Notify(const google::protobuf::StringValue &req,
        google::protobuf::Empty *resp) {
    // 这里补充这个RPC调用的Server端代码
    return -1;
}

Client (xxx_client.cpp)

// 这个是默认生成的代码,可自行修改,或利用我们提供的stub API自定义封装Client

int SearchClient::PHXEcho(const google::protobuf::StringValue &req,
        google::protobuf::StringValue *resp) {
    const phxrpc::Endpoint_t *ep = global_searchclient_config_.GetRandom();

    if (ep != nullptr) {
        phxrpc::BlockTcpStream socket;
        bool open_ret = phxrpc::PhxrpcTcpUtils::Open(&socket, ep->ip, ep->port,
                    global_searchclient_config_.GetConnectTimeoutMS(), nullptr, 0,
                    *(global_searchclient_monitor_.get()));
        if (open_ret) {
            socket.SetTimeout(global_searchclient_config_.GetSocketTimeoutMS());

            SearchStub stub(socket, *(global_searchclient_monitor_.get()));
            return stub.PHXEcho(req, resp);
        }
    }

    return -1;
}

UThread Client (xxx_client_uthread.cpp)

// 这个是默认生成的代码,可自行修改,或利用我们提供的stub API自定义封装Client
// UThread Client只能在采用PhxRPC uthread worker模型的server中调用。
// UThread Client构造函数需要传入UThreadEpollScheduler*类型参数,
// 这个参数来源可以在xxx_service_impl.h的私有变量中获得。

int SearchClientUThread::PHXEcho(const google::protobuf::StringValue &req,
        google::protobuf::StringValue *resp) {
    const phxrpc::Endpoint_t *ep = global_searchclientuthread_config_.GetRandom();

    if (uthread_scheduler_ != nullptr && ep != nullptr) {
        phxrpc::UThreadTcpStream socket;
        bool open_ret = phxrpc::PhxrpcTcpUtils::Open(uthread_scheduler_, &socket, ep->ip, ep->port,
                    global_searchclientuthread_config_.GetConnectTimeoutMS(),
                    *(global_searchclientuthread_monitor_.get()));
        if (open_ret) {
            socket.SetTimeout(global_searchclientuthread_config_.GetSocketTimeoutMS());

            SearchStub stub(socket, *(global_searchclientuthread_monitor_.get()));
            return stub.PHXEcho(req, resp);
        }
    }

    return -1;
}

Client并发调用样例

int SearchClient::PHXBatchEcho(const google::protobuf::StringValue &req,
        google::protobuf::StringValue *resp) {
    int ret = -1;
    size_t echo_server_count = 2;
    uthread_begin;
    for (size_t i = 0; i < echo_server_count; i++) {
        uthread_t [=, &uthread_s, &ret](void *) {
            const phxrpc::Endpoint_t *ep = global_searchclient_config_.GetByIndex(i);
            if (ep != nullptr) {
                phxrpc::UThreadTcpStream socket;
                if(phxrpc::PhxrpcTcpUtils::Open(&uthread_s, &socket, ep->ip, ep->port,
                            global_searchclient_config_.GetConnectTimeoutMS(),
                            *(global_searchclient_monitor_.get()))) {
                    socket.SetTimeout(global_searchclient_config_.GetSocketTimeoutMS());
                    SearchStub stub(socket, *(global_searchclient_monitor_.get()));
                    int this_ret = stub.PHXEcho(req, resp);
                    if (this_ret == 0) {
                        ret = this_ret;
                        uthread_s.Close();
                    }
                }
            }
        };
    }
    uthread_end;
    return ret;
}

uthread_begin, uthread_end, uthread_s, uthread_t这几个关键字是PhxRPC自定义的宏,分别表示协程的准备、结束,协程调度器以及协程的创建。

上面的代码实现了Google提出的 Backup Requests 模式。实现的功能是分别对两个Server同时发起Echo调用,当有一个Server响应的时候,则整个函数结束。在这段代码里面,我们提供了一种异步IO的同步写法,并给予了一些方便使用的宏定义。首先使用uthread_begin进行准备,然后使用uthread_t以lambda的形式创建一个协程,而在任意一个协程里面都可使用我们PhxRPC生成的Client API进行RPC调用,并可使用uthread_s随时结束所有RPC调用。最后的uthread_end真正通过协程调度发起这些lambda内的RPC调用,并等待结束。

当然你可以借用这4个宏定义,以同步代码的写法,进行更自定义的并发访问。

Server配置说明 (xxx_server.conf)

[Server]
BindIP = 127.0.0.1              // Server IP
Port = 16161                    // Server Port
MaxThreads = 16                 // Worker 线程数
WorkerUThreadCount = 50         // 每个线程开启的协程数,采用-u生成的Server必须配置这一项
WorkerUThreadStackSize = 65536  // UThread worker的栈大小
IOThreadCount = 3               // IO线程数,针对业务请自行调节
PackageName = search            // Server 名字,用于自行实现的监控统计上报
MaxConnections = 800000         // 最大并发连接数
MaxQueueLength = 20480          // IO队列最大长度
FastRejectThresholdMS = 20      // 快速拒绝自适应调节阀值,建议保持默认20ms,不做修改

[ServerTimeout]
SocketTimeoutMS = 5000          // Server读写超时,Worker处理超时

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953
star
88

FAutoTest

A UI automated testing framework for H5 and applets
Python
927
star
89

TencentKona-8

Tencent Kona is a no-cost, production-ready distribution of the Open Java Development Kit (OpenJDK), Long-term support(LTS) with quarterly updates. Tencent Kona serves as the default JDK internally at Tencent Cloud for cloud computing and other Java applications.
Java
910
star
90

tquic

A high-performance, lightweight, and cross-platform QUIC library
Rust
874
star
91

tdesign-vue

A Vue.js UI components lib for TDesign.
TypeScript
862
star
92

hel

A module federation SDK which is unrelated to tool chain for module consumer. 工具链无关的运行时模块联邦sdk.
JavaScript
861
star
93

Pebble

Pebble分布式开发框架
C++
861
star
94

mxflutter

使用 TypeScript/JavaScript 来开发 Flutter 应用的框架。
Dart
818
star
95

Face2FaceTranslator

面对面翻译小程序是微信团队针对面对面沟通的场景开发的流式语音翻译小程序,通过微信同声传译插件提供了语音识别,文本翻译等功能。
JavaScript
804
star
96

tdesign-react

A React UI components lib for TDesign.
TypeScript
779
star
97

DCache

A distributed in-memory NOSQL system based on TARS framework, support LRU algorithm and data persists on back-end database. Users can easily deploy, publish, and scale services on the web interface.
C++
745
star
98

Real-SR

Real-World Super-Resolution via Kernel Estimation and Noise Injection
Python
740
star
99

PatrickStar

PatrickStar enables Larger, Faster, Greener Pretrained Models for NLP and democratizes AI for everyone.
Python
734
star
100

HaboMalHunter

HaboMalHunter is a sub-project of Habo Malware Analysis System (https://habo.qq.com), which can be used for automated malware analysis and security assessment on the Linux system.
Python
721
star