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gRPC Basics - Java

This tutorial provides a basic Java programmer’s introduction to working with gRPC.

By walking through this example you’ll learn how to:

It assumes that you have read the Overview and are familiar with protocol buffers. Note that the example in this tutorial uses the proto3 version of the protocol buffers language: you can find out more in the proto3 language guide and Java generated code guide.

Why use gRPC?

Our example is a simple route mapping application that lets clients get information about features on their route, create a summary of their route, and exchange route information such as traffic updates with the server and other clients.

With gRPC we can define our service once in a .proto file and implement clients and servers in any of gRPC’s supported languages, which in turn can be run in environments ranging from servers inside Google to your own tablet - all the complexity of communication between different languages and environments is handled for you by gRPC. We also get all the advantages of working with protocol buffers, including efficient serialization, a simple IDL, and easy interface updating.

Example code and setup

The example code for our tutorial is in grpc/grpc-java/examples/src/main/java/io/grpc/examples. To download the example, clone the latest release in grpc-java repository by running the following command:

$ git clone -b v1.24.0 https://github.com/grpc/grpc-java.git

Then change your current directory to grpc-java/examples:

$ cd grpc-java/examples

Defining the service

Our first step (as you’ll know from the Overview) is to define the gRPC service and the method request and response types using protocol buffers. You can see the complete .proto file in grpc-java/examples/src/main/proto/route_guide.proto.

As we’re generating Java code in this example, we’ve specified a java_package file option in our .proto:

option java_package = "io.grpc.examples.routeguide";

This specifies the package we want to use for our generated Java classes. If no explicit java_package option is given in the .proto file, then by default the proto package (specified using the “package” keyword) will be used. However, proto packages generally do not make good Java packages since proto packages are not expected to start with reverse domain names. If we generate code in another language from this .proto, the java_package option has no effect.

To define a service, we specify a named service in the .proto file:

service RouteGuide {
   ...
}

Then we define rpc methods inside our service definition, specifying their request and response types. gRPC lets you define four kinds of service methods, all of which are used in the RouteGuide service:

// Obtains the feature at a given position.
rpc GetFeature(Point) returns (Feature) {}
// Obtains the Features available within the given Rectangle.  Results are
// streamed rather than returned at once (e.g. in a response message with a
// repeated field), as the rectangle may cover a large area and contain a
// huge number of features.
rpc ListFeatures(Rectangle) returns (stream Feature) {}
// Accepts a stream of Points on a route being traversed, returning a
// RouteSummary when traversal is completed.
rpc RecordRoute(stream Point) returns (RouteSummary) {}
// Accepts a stream of RouteNotes sent while a route is being traversed,
// while receiving other RouteNotes (e.g. from other users).
rpc RouteChat(stream RouteNote) returns (stream RouteNote) {}

Our .proto file also contains protocol buffer message type definitions for all the request and response types used in our service methods - for example, here’s the Point message type:

// Points are represented as latitude-longitude pairs in the E7 representation
// (degrees multiplied by 10**7 and rounded to the nearest integer).
// Latitudes should be in the range +/- 90 degrees and longitude should be in
// the range +/- 180 degrees (inclusive).
message Point {
  int32 latitude = 1;
  int32 longitude = 2;
}

Generating client and server code

Next we need to generate the gRPC client and server interfaces from our .proto service definition. We do this using the protocol buffer compiler protoc with a special gRPC Java plugin. You need to use the proto3 compiler (which supports both proto2 and proto3 syntax) in order to generate gRPC services.

When using Gradle or Maven, the protoc build plugin can generate the necessary code as part of the build. You can refer to the README for how to generate code from your own .proto files.

The following classes are generated from our service definition:

Creating the server

First let’s look at how we create a RouteGuide server. If you’re only interested in creating gRPC clients, you can skip this section and go straight to Creating the client (though you might find it interesting anyway!).

There are two parts to making our RouteGuide service do its job:

You can find our example RouteGuide server in grpc-java/examples/src/main/java/io/grpc/examples/routeguide/RouteGuideServer.java. Let’s take a closer look at how it works.

Implementing RouteGuide

As you can see, our server has a RouteGuideService class that extends the generated RouteGuideGrpc.RouteGuideImplBase abstract class:

private static class RouteGuideService extends RouteGuideGrpc.RouteGuideImplBase {
...
}

Simple RPC

RouteGuideService implements all our service methods. Let’s look at the simplest type first, GetFeature, which just gets a Point from the client and returns the corresponding feature information from its database in a Feature.

@Override
public void getFeature(Point request, StreamObserver<Feature> responseObserver) {
  responseObserver.onNext(checkFeature(request));
  responseObserver.onCompleted();
}

...

private Feature checkFeature(Point location) {
  for (Feature feature : features) {
    if (feature.getLocation().getLatitude() == location.getLatitude()
        && feature.getLocation().getLongitude() == location.getLongitude()) {
      return feature;
    }
  }

  // No feature was found, return an unnamed feature.
  return Feature.newBuilder().setName("").setLocation(location).build();
}

getFeature() takes two parameters:

To return our response to the client and complete the call:

  1. We construct and populate a Feature response object to return to the client, as specified in our service definition. In this example, we do this in a separate private checkFeature() method.
  2. We use the response observer’s onNext() method to return the Feature.
  3. We use the response observer’s onCompleted() method to specify that we’ve finished dealing with the RPC.
Server-side streaming RPC

Next let’s look at one of our streaming RPCs. ListFeatures is a server-side streaming RPC, so we need to send back multiple Features to our client.

private final Collection<Feature> features;

...

@Override
public void listFeatures(Rectangle request, StreamObserver<Feature> responseObserver) {
  int left = min(request.getLo().getLongitude(), request.getHi().getLongitude());
  int right = max(request.getLo().getLongitude(), request.getHi().getLongitude());
  int top = max(request.getLo().getLatitude(), request.getHi().getLatitude());
  int bottom = min(request.getLo().getLatitude(), request.getHi().getLatitude());

  for (Feature feature : features) {
    if (!RouteGuideUtil.exists(feature)) {
      continue;
    }

    int lat = feature.getLocation().getLatitude();
    int lon = feature.getLocation().getLongitude();
    if (lon >= left && lon <= right && lat >= bottom && lat <= top) {
      responseObserver.onNext(feature);
    }
  }
  responseObserver.onCompleted();
}

Like the simple RPC, this method gets a request object (the Rectangle in which our client wants to find Features) and a StreamObserver response observer.

This time, we get as many Feature objects as we need to return to the client (in this case, we select them from the service’s feature collection based on whether they’re inside our request Rectangle), and write them each in turn to the response observer using its onNext() method. Finally, as in our simple RPC, we use the response observer’s onCompleted() method to tell gRPC that we’ve finished writing responses.

Client-side streaming RPC

Now let’s look at something a little more complicated: the client-side streaming method RecordRoute, where we get a stream of Points from the client and return a single RouteSummary with information about their trip.

@Override
public StreamObserver<Point> recordRoute(final StreamObserver<RouteSummary> responseObserver) {
  return new StreamObserver<Point>() {
    int pointCount;
    int featureCount;
    int distance;
    Point previous;
    long startTime = System.nanoTime();

    @Override
    public void onNext(Point point) {
      pointCount++;
      if (RouteGuideUtil.exists(checkFeature(point))) {
        featureCount++;
      }
      // For each point after the first, add the incremental distance from the previous point
      // to the total distance value.
      if (previous != null) {
        distance += calcDistance(previous, point);
      }
      previous = point;
    }

    @Override
    public void onError(Throwable t) {
      logger.log(Level.WARNING, "Encountered error in recordRoute", t);
    }

    @Override
    public void onCompleted() {
      long seconds = NANOSECONDS.toSeconds(System.nanoTime() - startTime);
      responseObserver.onNext(RouteSummary.newBuilder().setPointCount(pointCount)
          .setFeatureCount(featureCount).setDistance(distance)
          .setElapsedTime((int) seconds).build());
      responseObserver.onCompleted();
    }
  };
}

As you can see, like the previous method types our method gets a StreamObserver response observer parameter, but this time it returns a StreamObserver for the client to write its Points.

In the method body we instantiate an anonymous StreamObserver to return, in which we:

Bidirectional streaming RPC

Finally, let’s look at our bidirectional streaming RPC RouteChat().

@Override
public StreamObserver<RouteNote> routeChat(final StreamObserver<RouteNote> responseObserver) {
  return new StreamObserver<RouteNote>() {
    @Override
    public void onNext(RouteNote note) {
      List<RouteNote> notes = getOrCreateNotes(note.getLocation());

      // Respond with all previous notes at this location.
      for (RouteNote prevNote : notes.toArray(new RouteNote[0])) {
        responseObserver.onNext(prevNote);
      }

      // Now add the new note to the list
      notes.add(note);
    }

    @Override
    public void onError(Throwable t) {
      logger.log(Level.WARNING, "Encountered error in routeChat", t);
    }

    @Override
    public void onCompleted() {
      responseObserver.onCompleted();
    }
  };
}

As with our client-side streaming example, we both get and return a StreamObserver response observer, except this time we return values via our method’s response observer while the client is still writing messages to their message stream. The syntax for reading and writing here is exactly the same as for our client-streaming and server-streaming methods. Although each side will always get the other’s messages in the order they were written, both the client and server can read and write in any order — the streams operate completely independently.

Starting the server

Once we’ve implemented all our methods, we also need to start up a gRPC server so that clients can actually use our service. The following snippet shows how we do this for our RouteGuide service:

public RouteGuideServer(int port, URL featureFile) throws IOException {
  this(ServerBuilder.forPort(port), port, RouteGuideUtil.parseFeatures(featureFile));
}

/** Create a RouteGuide server using serverBuilder as a base and features as data. */
public RouteGuideServer(ServerBuilder<?> serverBuilder, int port, Collection<Feature> features) {
  this.port = port;
  server = serverBuilder.addService(new RouteGuideService(features))
      .build();
}
...
public void start() throws IOException {
  server.start();
  logger.info("Server started, listening on " + port);
 ...
}

As you can see, we build and start our server using a ServerBuilder.

To do this, we:

  1. Specify the address and port we want to use to listen for client requests using the builder’s forPort() method.
  2. Create an instance of our service implementation class RouteGuideService and pass it to the builder’s addService() method.
  3. Call build() and start() on the builder to create and start an RPC server for our service.

Creating the client

In this section, we’ll look at creating a Java client for our RouteGuide service. You can see our complete example client code in grpc-java/examples/src/main/java/io/grpc/examples/routeguide/RouteGuideClient.java.

Creating a stub

To call service methods, we first need to create a stub, or rather, two stubs:

First we need to create a gRPC channel for our stub, specifying the server address and port we want to connect to:

public RouteGuideClient(String host, int port) {
  this(ManagedChannelBuilder.forAddress(host, port).usePlaintext());
}

/** Construct client for accessing RouteGuide server using the existing channel. */
public RouteGuideClient(ManagedChannelBuilder<?> channelBuilder) {
  channel = channelBuilder.build();
  blockingStub = RouteGuideGrpc.newBlockingStub(channel);
  asyncStub = RouteGuideGrpc.newStub(channel);
}

We use a ManagedChannelBuilder to create the channel.

Now we can use the channel to create our stubs using the newStub and newBlockingStub methods provided in the RouteGuideGrpc class we generated from our .proto.

blockingStub = RouteGuideGrpc.newBlockingStub(channel);
asyncStub = RouteGuideGrpc.newStub(channel);

Calling service methods

Now let’s look at how we call our service methods.

Simple RPC

Calling the simple RPC GetFeature on the blocking stub is as straightforward as calling a local method.

Point request = Point.newBuilder().setLatitude(lat).setLongitude(lon).build();
Feature feature;
try {
  feature = blockingStub.getFeature(request);
} catch (StatusRuntimeException e) {
  logger.log(Level.WARNING, "RPC failed: {0}", e.getStatus());
  return;
}

We create and populate a request protocol buffer object (in our case Point), pass it to the getFeature() method on our blocking stub, and get back a Feature.

If an error occurs, it is encoded as a Status, which we can obtain from the StatusRuntimeException.

Server-side streaming RPC

Next, let’s look at a server-side streaming call to ListFeatures, which returns a stream of geographical Features:

Rectangle request =
    Rectangle.newBuilder()
        .setLo(Point.newBuilder().setLatitude(lowLat).setLongitude(lowLon).build())
        .setHi(Point.newBuilder().setLatitude(hiLat).setLongitude(hiLon).build()).build();
Iterator<Feature> features;
try {
  features = blockingStub.listFeatures(request);
} catch (StatusRuntimeException ex) {
  logger.log(Level.WARNING, "RPC failed: {0}", e.getStatus());
  return;
}

As you can see, it’s very similar to the simple RPC we just looked at, except instead of returning a single Feature, the method returns an Iterator that the client can use to read all the returned Features.

Client-side streaming RPC

Now for something a little more complicated: the client-side streaming method RecordRoute, where we send a stream of Points to the server and get back a single RouteSummary. For this method we need to use the asynchronous stub. If you’ve already read Creating the server some of this may look very familiar - asynchronous streaming RPCs are implemented in a similar way on both sides.

public void recordRoute(List<Feature> features, int numPoints) throws InterruptedException {
  info("*** RecordRoute");
  final CountDownLatch finishLatch = new CountDownLatch(1);
  StreamObserver<RouteSummary> responseObserver = new StreamObserver<RouteSummary>() {
    @Override
    public void onNext(RouteSummary summary) {
      info("Finished trip with {0} points. Passed {1} features. "
          + "Travelled {2} meters. It took {3} seconds.", summary.getPointCount(),
          summary.getFeatureCount(), summary.getDistance(), summary.getElapsedTime());
    }

    @Override
    public void onError(Throwable t) {
      Status status = Status.fromThrowable(t);
      logger.log(Level.WARNING, "RecordRoute Failed: {0}", status);
      finishLatch.countDown();
    }

    @Override
    public void onCompleted() {
      info("Finished RecordRoute");
      finishLatch.countDown();
    }
  };

  StreamObserver<Point> requestObserver = asyncStub.recordRoute(responseObserver);
  try {
    // Send numPoints points randomly selected from the features list.
    Random rand = new Random();
    for (int i = 0; i < numPoints; ++i) {
      int index = rand.nextInt(features.size());
      Point point = features.get(index).getLocation();
      info("Visiting point {0}, {1}", RouteGuideUtil.getLatitude(point),
          RouteGuideUtil.getLongitude(point));
      requestObserver.onNext(point);
      // Sleep for a bit before sending the next one.
      Thread.sleep(rand.nextInt(1000) + 500);
      if (finishLatch.getCount() == 0) {
        // RPC completed or errored before we finished sending.
        // Sending further requests won't error, but they will just be thrown away.
        return;
      }
    }
  } catch (RuntimeException e) {
    // Cancel RPC
    requestObserver.onError(e);
    throw e;
  }
  // Mark the end of requests
  requestObserver.onCompleted();

  // Receiving happens asynchronously
  finishLatch.await(1, TimeUnit.MINUTES);
}

As you can see, to call this method we need to create a StreamObserver, which implements a special interface for the server to call with its RouteSummary response. In our StreamObserver we:

We then pass the StreamObserver to the asynchronous stub’s recordRoute() method and get back our own StreamObserver request observer to write our Points to send to the server. Once we’ve finished writing points, we use the request observer’s onCompleted() method to tell gRPC that we’ve finished writing on the client side. Once we’re done, we check our CountDownLatch to check that the server has completed on its side.

Bidirectional streaming RPC

Finally, let’s look at our bidirectional streaming RPC RouteChat().

public void routeChat() throws Exception {
  info("*** RoutChat");
  final CountDownLatch finishLatch = new CountDownLatch(1);
  StreamObserver<RouteNote> requestObserver =
      asyncStub.routeChat(new StreamObserver<RouteNote>() {
        @Override
        public void onNext(RouteNote note) {
          info("Got message \"{0}\" at {1}, {2}", note.getMessage(), note.getLocation()
              .getLatitude(), note.getLocation().getLongitude());
        }

        @Override
        public void onError(Throwable t) {
          Status status = Status.fromThrowable(t);
          logger.log(Level.WARNING, "RouteChat Failed: {0}", status);
          finishLatch.countDown();
        }

        @Override
        public void onCompleted() {
          info("Finished RouteChat");
          finishLatch.countDown();
        }
      });

  try {
    RouteNote[] requests =
        {newNote("First message", 0, 0), newNote("Second message", 0, 1),
            newNote("Third message", 1, 0), newNote("Fourth message", 1, 1)};

    for (RouteNote request : requests) {
      info("Sending message \"{0}\" at {1}, {2}", request.getMessage(), request.getLocation()
          .getLatitude(), request.getLocation().getLongitude());
      requestObserver.onNext(request);
    }
  } catch (RuntimeException e) {
    // Cancel RPC
    requestObserver.onError(e);
    throw e;
  }
  // Mark the end of requests
  requestObserver.onCompleted();

  // Receiving happens asynchronously
  finishLatch.await(1, TimeUnit.MINUTES);
}

As with our client-side streaming example, we both get and return a StreamObserver response observer, except this time we send values via our method’s response observer while the server is still writing messages to their message stream. The syntax for reading and writing here is exactly the same as for our client-streaming method. Although each side will always get the other’s messages in the order they were written, both the client and server can read and write in any order — the streams operate completely independently.

Try it out!

Follow the instructions in the example directory README to build and run the client and server.