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gRPC & High Performance APIs · 课时

客户端流式传输详解

学习实现客户端流式传输，使客户端能够向服务器发送一系列消息

客户端流式传输详解 是 CoddyKit 上的免费 gRPC & High Performance APIs 课时。 这是第 2 节课，共 4 节。 你可以在下方免费阅读本课时的完整内容 — 然后在浏览器中使用内置代码编辑器和全天候 AI 导师进行实践。 这是 gRPC & High Performance APIs 学习路径的一部分，你的进度在网页和 CoddyKit 应用中同步。 gRPC & High Performance APIs 课程共包含 4 节课。

本课时的部分内容尚未翻译，以英文显示。

What is Client Streaming?

Welcome to client streaming! In gRPC, client streaming is a communication pattern where the client sends a sequence of messages to the server.

Unlike a simple unary RPC (request-response), the client doesn't just send one message. Instead, it sends a stream of messages, and the server processes them, then sends back a single response at the end.

How Client Streaming Works

Imagine uploading a large file by sending it in many small chunks. The server collects all chunks, rebuilds the file, and then sends a single "upload complete" confirmation.

  • The client initiates the RPC.
  • The client sends multiple messages asynchronously.
  • The server receives and processes these messages.
  • Once the client finishes sending (signals completion), the server sends back a single response.

Defining Client Stream in Protobuf

To define a client-streaming method in your .proto file, you use the stream keyword for the request type, but not for the response type.

Here's an example for a log upload service:

syntax = "proto3";

package client_streaming;

service LogService {
  rpc UploadLogs (stream LogEntry) returns (UploadSummary);
}

message LogEntry {
  string message = 1;
  int64 timestamp = 2;
}

message UploadSummary {
  int32 uploaded_count = 1;
  string status_message = 2;
}

Server: Handling the Client Stream

On the server side, your method will receive a StreamObserver for the client's incoming messages and will use another StreamObserver to send its single response.

The server's StreamObserver will have onNext() for each incoming message, onError() for errors, and onCompleted() when the client finishes sending.

import io.grpc.stub.StreamObserver;
import io.grpc.Server;
import io.grpc.ServerBuilder;
import client_streaming.LogEntry;
import client_streaming.LogServiceGrpc;
import client_streaming.UploadSummary;

public class LogServer {
    private Server server;

    private void start() throws Exception {
        int port = 50051;
        server = ServerBuilder.forPort(port)
            .addService(new LogServiceImpl())
            .build()
            .start();
        System.out.println("Server started, listening on " + port);
        Runtime.getRuntime().addShutdownHook(new Thread(() -> {
            System.err.println("*** shutting down gRPC server since JVM is shutting down");
            LogServer.this.stop();
            System.err.println("*** server shut down");
        }));
    }

    private void stop() {
        if (server != null) {
            server.shutdown();
        }
    }

    private void blockUntilShutdown() throws InterruptedException {
        if (server != null) {
            server.awaitTermination();
        }
    }

    public static void main(String[] args) throws Exception {
        final LogServer logServer = new LogServer();
        logServer.start();
        logServer.blockUntilShutdown();
    }

    static class LogServiceImpl extends LogServiceGrpc.LogServiceImplBase {
        @Override
        public StreamObserver<LogEntry> uploadLogs(StreamObserver<UploadSummary> responseObserver) {
            return new StreamObserver<LogEntry>() {
                private int logCount = 0;

                @Override
                public void onNext(LogEntry log) {
                    // Process each log entry as it arrives
                    System.out.println("Received log: " + log.getMessage() + " at " + log.getTimestamp());
                    logCount++;
                }

                @Override
                public void onError(Throwable t) {
                    System.err.println("UploadLogs cancelled or failed: " + t.getMessage());
                    responseObserver.onError(t);
                }

                @Override
                public void onCompleted() {
                    // After all logs are received, send a single summary response
                    UploadSummary summary = UploadSummary.newBuilder()
                        .setUploadedCount(logCount)
                        .setStatusMessage("Successfully processed " + logCount + " log entries.")
                        .build();
                    responseObserver.onNext(summary);
                    responseObserver.onCompleted();
                    System.out.println("Finished processing client stream. Sent summary.");
                }
            };
        }
    }
}

Client: Sending the Stream

On the client side, you'll get a StreamObserver to send your messages. You call onNext() for each message you want to send and finally onCompleted() to signal the end of the stream.

The server's single response will be handled by a separate StreamObserver you provide.

import io.grpc.ManagedChannel;
import io.grpc.ManagedChannelBuilder;
import io.grpc.stub.StreamObserver;
import client_streaming.LogEntry;
import client_streaming.LogServiceGrpc;
import client_streaming.UploadSummary;

import java.util.concurrent.TimeUnit;

public class LogClient {
    private final LogServiceGrpc.LogServiceStub asyncStub;
    private final ManagedChannel channel;

    public LogClient(String host, int port) {
        channel = ManagedChannelBuilder.forAddress(host, port)
            .usePlaintext() // For demonstration, use plaintext
            .build();
        asyncStub = LogServiceGrpc.newStub(channel);
    }

    public void shutdown() throws InterruptedException {
        channel.shutdown().awaitTermination(5, TimeUnit.SECONDS);
    }

    public void uploadMultipleLogs() throws InterruptedException {
        StreamObserver<UploadSummary> responseObserver = new StreamObserver<UploadSummary>() {
            @Override
            public void onNext(UploadSummary summary) {
                System.out.println("Server Response: " + summary.getStatusMessage() + " (" + summary.getUploadedCount() + " logs)");
            }

            @Override
            public void onError(Throwable t) {
                System.err.println("UploadLogs failed: " + t.getMessage());
            }

            @Override
            public void onCompleted() {
                System.out.println("Server has completed processing.");
            }
        };

        StreamObserver<LogEntry> requestObserver = asyncStub.uploadLogs(responseObserver);

        try {
            // Send multiple log entries
            LogEntry log1 = LogEntry.newBuilder().setMessage("User login attempt").setTimestamp(System.currentTimeMillis()).build();
            LogEntry log2 = LogEntry.newBuilder().setMessage("Database query executed").setTimestamp(System.currentTimeMillis() + 100).build();
            LogEntry log3 = LogEntry.newBuilder().setMessage("API call completed").setTimestamp(System.currentTimeMillis() + 200).build();

            requestObserver.onNext(log1);
            System.out.println("Client sent log 1");
            Thread.sleep(100); // Simulate some delay
            requestObserver.onNext(log2);
            System.out.println("Client sent log 2");
            Thread.sleep(100);
            requestObserver.onNext(log3);
            System.out.println("Client sent log 3");

            // Mark the end of the client stream
            requestObserver.onCompleted();
            System.out.println("Client finished sending logs.");

            // Wait for server response (handled by responseObserver)
            Thread.sleep(1000); // Give time for server to respond
        } catch (RuntimeException e) {
            requestObserver.onError(e);
            throw e;
        }
    }

    public static void main(String[] args) throws Exception {
        LogClient client = new LogClient("localhost", 50051);
        try {
            client.uploadMultipleLogs();
        } finally {
            client.shutdown();
        }
    }
}

Running the Example

To see client streaming in action:

  1. First, compile your .proto file to generate the necessary Java classes.
  2. Run the LogServer application. It will start listening for requests.
  3. Then, run the LogClient application. It will send three log entries and wait for the server's summary.

Observe the console output from both the client and server to understand the flow of messages.

Key StreamObserver Methods

The StreamObserver interface is crucial for handling streaming RPCs. Both the client and server use implementations of this interface.

  • onNext(T value): Called for each message received in the stream. The client uses this to send messages, the server uses it to receive.
  • onError(Throwable t): Called if an RPC fails or is cancelled.
  • onCompleted(): Called when the stream has finished. The client calls this after sending all messages; the server calls it after sending its final response.

When to Use Client Streaming

Client streaming is ideal for scenarios where a client needs to send a large amount of data or a series of related messages to a server, and only cares about a single final result.

  • Large File Uploads: Sending a file chunk by chunk.
  • Log Aggregation: A client sending many log entries to a central logging service.
  • Batch Operations: Sending a list of items to be processed as a single batch, receiving a summary.
  • Sensor Data Collection: Continuously sending readings from a sensor device.

Quick Check

You're designing a gRPC service where a client needs to send a series of sensor readings to a server, and the server will process them and return a single summary report.

Recap: Client Streaming

You've learned about client-side streaming in gRPC!

  • Client streaming allows a client to send a sequence of messages.
  • The server processes these messages and sends a single response back.
  • In Protobuf, you define it by using the stream keyword for the request type.
  • Both client and server use StreamObserver to manage the flow of messages (onNext(), onError(), onCompleted()).
  • It's great for tasks like uploading large data or sending continuous log entries.

Next, we'll explore server-side streaming!

常见问题解答

「客户端流式传输详解」课时是免费的吗？

是的 — 「客户端流式传输详解」的完整文本可在网页上免费阅读。要进行交互式练习（内置代码编辑器和全天候 AI 导师）并解锁 gRPC & High Performance APIs 课程的其余内容，请升级到 CoddyKit PRO。 gRPC & High Performance APIs 课程共包含 4 节课。

「客户端流式传输详解」这节课中我会学到什么？

学习实现客户端流式传输，使客户端能够向服务器发送一系列消息 你通过在浏览器中直接运行的动手代码来练习 gRPC & High Performance APIs，全天候 AI 导师会在你学习这节课的过程中回答你的问题。

学习 gRPC & High Performance APIs 需要有经验吗？

无需任何先前经验。CoddyKit 上的 gRPC & High Performance APIs 课程适合初学者到高级学习者，你可以从这里开始或从头开始，按照自己的节奏学习。 这是第 2 节课，共 4 节。

「客户端流式传输详解」课时需要多长时间？

大多数 CoddyKit 课程大约需要 5–10 分钟。每节课都很精短且互动，所以你能稳步进步，并在网页和应用中从离开的地方继续。

我能在这节 gRPC & High Performance APIs 课中编写并运行代码吗？

能。每节 gRPC & High Performance APIs 课都包含内置代码编辑器，你可以在浏览器中直接编写并运行真实代码，并获得即时 AI 反馈 — 无需本地设置。

此课程中的所有课时

  1. 服务器流式传输详解
  2. 客户端流式传输详解
  3. 双向流式传输
  4. 流式控制与背压
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