服务网格GRPC协议多种编程语言实践-2.GRPC协议示例的实现-阿里云开发者社区

1 Generated-code

首先本地开发环境需要安装grpc和protobuf，这里以macos为例：brew install grpc protobuf。

无论使用什么编程语言实现GRPC协议的服务，都需要将protobuf定义转换为该语言的代码。

Java的构建工具Maven提供了自动转换插件protobuf-maven-plugin，执行mvn package会自动使用protoc-gen-grpc-java创建grpc的模板代码。详见hello-grpc-java/pom.xml。
Go需要执行go get github.com/golang/protobuf/protoc-gen-go安装，然后使用protoc命令生成grpc代码。详见hello-grpc-go/proto2go.sh。
NodeJs需要执行npm install -g grpc-tools安装grpc_tools_node_protoc，然后使用protoc命令生成grpc代码。详见hello-grpc-nodejs/proto2js.sh。
Python需要执行pip install grpcio-tools安装grpcio-tools ，然后使用protoc命令生成grpc代码。详见hello-grpc-python/proto2py.sh。

在示例工程中，每种语言的代码目录中都有一个proto目录，其中的landing.proto文件是示例根目录下proto/landing.proto文件的软连接，这样有利于统一更新protobuf的定义。

2 通信实现

hello数组

private final List<String> HELLO_LIST = Arrays.asList("Hello", "Bonjour", "Hola", "こんにちは", "Ciao", "안녕하세요");

kv.put("data", HELLO_LIST.get(index));

var helloList = []string{"Hello", "Bonjour", "Hola", "こんにちは", "Ciao", "안녕하세요"}

kv["data"] = helloList[index]

let hellos = ["Hello", "Bonjour", "Hola", "こんにちは", "Ciao", "안녕하세요"]

kv.set("data", hellos[index])

hellos = ["Hello", "Bonjour", "Hola", "こんにちは", "Ciao", "안녕하세요"]

result.kv["data"] = hellos[index]

talk

Unary RPC类型的实现是最经典的，阻塞式一发一收。

// 使用blockingStub与服务端通信
public TalkResponse talk(TalkRequest talkRequest) {
    return blockingStub.talk(talkRequest);
}
//服务端处理请求后触发StreamObserver实例的两个事件onNext和onCompleted
public void talk(TalkRequest request, StreamObserver<TalkResponse> responseObserver) {
    ...
    responseObserver.onNext(response);
    responseObserver.onCompleted();
}

func talk(client pb.LandingServiceClient, request *pb.TalkRequest) {
    r, err := client.Talk(context.Background(), request)
}

func (s *ProtoServer) Talk(ctx context.Context, request *pb.TalkRequest) (*pb.TalkResponse, error) {
    return &pb.TalkResponse{
        Status:  200,
        Results: []*pb.TalkResult{s.buildResult(request.Data)},
    }, nil
}

function talk(client, request) {
    client.talk(request, function (err, response) {
            ...
    })
}
                
function talk(call, callback) {
    const talkResult = buildResult(call.request.getData())
    ...
    callback(null, response)
}

def talk(stub):
    response = stub.talk(request)
    
def talk(self, request, context):
    result = build_result(request.data)
    ...
    return response

talkOneAnswerMore

Server streaming RPC类型的实现重点是客户端在发送请求后如何处理流式响应数据，以及服务端的流式返回响应。

public List<TalkResponse> talkOneAnswerMore(TalkRequest request) {
    Iterator<TalkResponse> talkResponses = blockingStub.talkOneAnswerMore(request);
    talkResponses.forEachRemaining(talkResponseList::add);
    return talkResponseList;
}

public void talkOneAnswerMore(TalkRequest request, StreamObserver<TalkResponse> responseObserver) {
    String[] datas = request.getData().split(",");
    for (String data : datas) {...}
    talkResponses.forEach(responseObserver::onNext);
    responseObserver.onCompleted();
}

func talkOneAnswerMore(client pb.LandingServiceClient, request *pb.TalkRequest) {
    stream, err := client.TalkOneAnswerMore(context.Background(), request)
    for {
        r, err := stream.Recv()
        if err == io.EOF {
            break
        }
    ...
    }
}

func (s *ProtoServer) TalkOneAnswerMore(request *pb.TalkRequest, stream pb.Landing..Server) error {
    datas := strings.Split(request.Data, ",")
    for _, d := range datas {
        stream.Send(&pb.TalkResponse{...})
}

function talkOneAnswerMore(client, request) {
    let call = client.talkOneAnswerMore(request)
    call.on('data', function (response) {
        ...
    })
}

function talkOneAnswerMore(call) {
    let datas = call.request.getData().split(",")
    for (const data in datas) {
        ...
        call.write(response)
    }
    call.end()
}

def talk_one_answer_more(stub):
    responses = stub.talkOneAnswerMore(request)
    for response in responses:
        logger.info(response)

def talkOneAnswerMore(self, request, context):
    datas = request.data.split(",")
    for data in datas:
        yield response

talkMoreAnswerOne

Client streaming RPC类型的实现重点是客户端以流式发送请求后，告诉服务端请求结束，服务端会将多次请求分别处理，在收到结束时一次返回给客户端。

public void talkMoreAnswerOne(List<TalkRequest> requests) throws InterruptedException {
    final CountDownLatch finishLatch = new CountDownLatch(1);
    StreamObserver<TalkResponse> responseObserver = new StreamObserver<TalkResponse>() {
        @Override
        public void onNext(TalkResponse talkResponse) {
            log.info("Response=\n{}", talkResponse);
        }
        @Override
        public void onCompleted() {
            finishLatch.countDown();
        }
    };
    final StreamObserver<TalkRequest> requestObserver = asyncStub.talkMoreAnswerOne(responseObserver);
    try {
        requests.forEach(request -> {
            if (finishLatch.getCount() > 0) {
                requestObserver.onNext(request);
        });
    requestObserver.onCompleted();
}
                         
public StreamObserver<TalkRequest> talkMoreAnswerOne(StreamObserver<TalkResponse> responseObserver) {
    return new StreamObserver<TalkRequest>() {
        @Override
        public void onNext(TalkRequest request) {
            talkRequests.add(request);
        }
        @Override
        public void onCompleted() {
            responseObserver.onNext(buildResponse(talkRequests));
            responseObserver.onCompleted();
        }
    };
}

func talkMoreAnswerOne(client pb.LandingServiceClient, requests []*pb.TalkRequest) {
    stream, err := client.TalkMoreAnswerOne(context.Background())
    for _, request := range requests {
        stream.Send(request)
    }
    r, err := stream.CloseAndRecv()
}

func (s *ProtoServer) TalkMoreAnswerOne(stream pb.LandingService_TalkMoreAnswerOneServer) error {
    for {
        in, err := stream.Recv()
        if err == io.EOF {
            talkResponse := &pb.TalkResponse{
                Status:  200,
                Results: rs,
            }
            stream.SendAndClose(talkResponse)
            return nil
        }
        rs = append(rs, s.buildResult(in.Data))
    }
}

function talkMoreAnswerOne(client, requests) {
    let call = client.talkMoreAnswerOne(function (err, response) {
        ...
    })
    requests.forEach(request => {
        call.write(request)
    })
    call.end()
}

function talkMoreAnswerOne(call, callback) {
    let talkResults = []
    call.on('data', function (request) {
        talkResults.push(buildResult(request.getData()))
    })
    call.on('end', function () {
        let response = new messages.TalkResponse()
        response.setStatus(200)
        response.setResultsList(talkResults)
        callback(null, response)
    })
}

def talk_more_answer_one(stub):
    response_summary = stub.talkMoreAnswerOne(request_iterator)

def generate_request():
    for _ in range(0, 3):
        yield request
        
def talkMoreAnswerOne(self, request_iterator, context):
    for request in request_iterator:
        response.results.append(build_result(request.data))
    return response

talkBidirectional

Bidirectional streaming RPC类型的实现重点是客户端以流式发送请求后，告诉服务端请求结束，服务端会在每次请求后将结果返回，并在收到结束时，告诉客户端结束。

public void talkBidirectional(List<TalkRequest> requests) throws InterruptedException {
    final CountDownLatch finishLatch = new CountDownLatch(1);
    StreamObserver<TalkResponse> responseObserver = new StreamObserver<TalkResponse>() {
        @Override
        public void onNext(TalkResponse talkResponse) {
            log.info("Response=\n{}", talkResponse);
        }
        @Override
        public void onCompleted() {
            finishLatch.countDown();
        }
    };
    final StreamObserver<TalkRequest> requestObserver = asyncStub.talkBidirectional(responseObserver);
    try {
        requests.forEach(request -> {
            if (finishLatch.getCount() > 0) {
                requestObserver.onNext(request);
    ...
    requestObserver.onCompleted();
}

public StreamObserver<TalkRequest> talkBidirectional(StreamObserver<TalkResponse> responseObserver) {
    return new StreamObserver<TalkRequest>() {
        @Override
        public void onNext(TalkRequest request) {
            responseObserver.onNext(TalkResponse.newBuilder()
                    .setStatus(200)
                    .addResults(buildResult(request.getData())).build());
        }
        @Override
        public void onCompleted() {
            responseObserver.onCompleted();
        }
    };
}

func talkBidirectional(client pb.LandingServiceClient, requests []*pb.TalkRequest) {
    stream, err := client.TalkBidirectional(context.Background())
    waitc := make(chan struct{})
    go func() {
        for {
            r, err := stream.Recv()
            if err == io.EOF {
                // read done.
                close(waitc)
                return
            }
        }
    }()
    for _, request := range requests {
        stream.Send(request)
    }
    stream.CloseSend()
    <-waitc
}

func (s *ProtoServer) TalkBidirectional(stream pb.LandingService_TalkBidirectionalServer) error {
    for {
        in, err := stream.Recv()
        if err == io.EOF {
            return nil
        }
        stream.Send(talkResponse)
    }
}

function talkBidirectional(client, requests) {
    let call = client.talkBidirectional()
    call.on('data', function (response) {
        ...
    })
    requests.forEach(request => {
        call.write(request)
    })
    call.end()
}

function talkBidirectional(call) {
    call.on('data', function (request) {
        call.write(response)
    })
    call.on('end', function () {
        call.end()
    })
}

def talk_bidirectional(stub):
    responses = stub.talkBidirectional(request_iterator)
    for response in responses:
        logger.info(response)

def talkBidirectional(self, request_iterator, context):
    for request in request_iterator:
        yield response

2 要点实现

环境变量

private static String getGrcServer() {
    String server = System.getenv("GRPC_SERVER");
    if (server == null) {
        return "localhost";
    }
    return server;
}

func grpcServer() string {
    server := os.Getenv("GRPC_SERVER")
    if len(server) == 0 {
        return "localhost"
    } else {
        return server
    }
}

function grpcServer() {
    let server = process.env.GRPC_SERVER;
    if (typeof server !== 'undefined' && server !== null) {
        return server
    } else {
        return "localhost"
    }
}

def grpc_server():
    server = os.getenv("GRPC_SERVER")
    if server:
        return server
    else:
        return "localhost"

随机数

public static String getRandomId() {
    return String.valueOf(random.nextInt(5));
}

func randomId(max int) string {
    return strconv.Itoa(rand.Intn(max))
}

function randomId(max) {
    return Math.floor(Math.random() * Math.floor(max)).toString()
}

def random_id(end):
    return str(random.randint(0, end))

时间戳

TalkResult.newBuilder().setId(System.nanoTime())

result.Id = time.Now().UnixNano()

result.setId(Math.round(Date.now() / 1000))

result.id = int((time.time()))

UUID

kv.put("id", UUID.randomUUID().toString());

import (
    "github.com/google/uuid"
)
kv["id"] = uuid.New().String()

kv.set("id", uuid.v1())

result.kv["id"] = str(uuid.uuid1())

Sleep

TimeUnit.SECONDS.sleep(1);

time.Sleep(2 * time.Millisecond)

let sleep = require('sleep')

sleep.msleep(2)

time.sleep(random.uniform(0.5, 1.5))

3 验证

功能验证

完成功能开发后，我们在一个终端启动GRPC服务，在另一个终端启动客户端。客户端分别对4个通信接口进行请求。

java

mvn exec:java -Dexec.mainClass="org.feuyeux.grpc.server.ProtoServer"

mvn exec:java -Dexec.mainClass="org.feuyeux.grpc.client.ProtoClient"

go

go run server.go

go run client/proto_client.go

nodejs

node proto_server.js

node proto_client.js

python

python server/protoServer.py

python client/protoClient.py

交叉通信

在功能验证基础上，我们启动任意一种编程语言实现的Server端，然后使用其他4种客户端进行验证。以确保不同编程语言实现的GRPC通信行为一致。这步验证是后续容器化和网格化的基础，因为每种编程语言的Server端都会作为同一个Kubernetes Service的一个版本的Deployment发布，它们的行为必须一致，以保证路由到不同版本，结果是一致的。

4 构建和分发

构建

通信功能验证完毕后，接下来是将4个工程编译、构建、打包。这一步的输出是制作镜像的输入。

java

分别构建服务端和客户端的jar，将其拷贝到docker目录备用。

mvn clean install -DskipTests -f server_pom
cp target/hello-grpc-java.jar ../docker/

mvn clean install -DskipTests -f client_pom
cp target/hello-grpc-java.jar ../docker/

go

go编译的二进制是平台相关的，因为我们最终要部署到linux上，因此构建命令如下。然后将二进制拷贝到docker目录备用。

env GOOS=linux GOARCH=amd64 go build -o proto_server server.go
mv proto_server ../docker/

env GOOS=linux GOARCH=amd64 go build -o proto_client client/proto_client.go
mv proto_client ../docker/

nodejs

node需要在docker镜像中进行构建，才能支持运行时所需的各种c++依赖。因此这一步主要是拷贝备用。

cp ../hello-grpc-nodejs/proto_server.js node
cp ../hello-grpc-nodejs/package.json node
cp -R ../hello-grpc-nodejs/common node
cp -R ../proto node
cp ../hello-grpc-nodejs/*_client.js node

python

python无需编译，直接拷贝备用即可。

cp -R ../hello-grpc-python/server py
cp ../hello-grpc-python/start_server.sh py
cp -R ../proto py
cp ../hello-grpc-python/proto2py.sh py
cp -R ../hello-grpc-python/client py
cp ../hello-grpc-python/start_client.sh py

dockerfile

构建完毕后，docker路径下存储了dockerfile所需的全部文件。这里将dockerfile中重点信息说明如下。

基础镜像我们尽量选择alpine，因为尺寸最小。python的基础镜像注意选择2.7版本的python:2，因为示例使用的是python2。如果对python3有强需求，请基于示例代码酌情修改。
nodejs需要安装c++及编译器make，npm包需要安装grpc-tools。

这里以nodejs server的镜像作为示例，说明构建镜像的过程。

grpc-server-node.dockerfile

FROM node:14.11-alpine
RUN apk add --update \
      python \
      make \
      g++ \
  && rm -rf /var/cache/apk/*
RUN npm config set registry https://registry.npm.taobao.org && npm install -g node-pre-gyp grpc-tools --unsafe-perm
COPY node/package.json .
RUN npm install --unsafe-perm
COPY node .
ENTRYPOINT ["node","proto_server.js"]

docker build

docker build -f grpc-server-node.dockerfile -t registry.cn-beijing.aliyuncs.com/asm_repo/grpc_server_node:1.0.0 .

镜像列表

最终我们会构建出8个镜像，使用push命令将镜像分发到到阿里云ACR服务，作为下一篇kube的基础。

registry.cn-beijing.aliyuncs.com/asm_repo/grpc_server_java:1.0.0
registry.cn-beijing.aliyuncs.com/asm_repo/grpc_client_java:1.0.0
registry.cn-beijing.aliyuncs.com/asm_repo/grpc_server_go:1.0.0
registry.cn-beijing.aliyuncs.com/asm_repo/grpc_client_go:1.0.0
registry.cn-beijing.aliyuncs.com/asm_repo/grpc_server_node:1.0.0
registry.cn-beijing.aliyuncs.com/asm_repo/grpc_client_node:1.0.0
registry.cn-beijing.aliyuncs.com/asm_repo/grpc_server_python:1.0.0
registry.cn-beijing.aliyuncs.com/asm_repo/grpc_client_python:1.0.0

服务网格GRPC协议多种编程语言实践-2.GRPC协议示例的实现

1 Generated-code

2 通信实现

hello数组

talk

talkOneAnswerMore

talkMoreAnswerOne

talkBidirectional

2 要点实现

环境变量

随机数

时间戳

UUID

Sleep

3 验证

功能验证

java

go

nodejs

python

交叉通信

4 构建和分发

构建

java

go

nodejs

python

dockerfile

grpc-server-node.dockerfile

docker build

镜像列表

容器服务

热门文章

最新文章

相关课程

相关电子书