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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:
- Define a service in a .proto file.
- Generate server and client code using the protocol buffer compiler.
- Use the Java gRPC API to write a simple client and server for your service.
It assumes that you have read the Getting started guide and are familiar with [protocol buffers] (https://developers.google.com/protocol-buffers/docs/overview). Note that the example in this tutorial uses the proto3 version of the protocol buffers language, which is currently in alpha release: you can see the release notes for the new version in the protocol buffers Github repository.
This isn't a comprehensive guide to using gRPC in Java: more reference documentation is coming soon.
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 grpc-java
repository by running the following command:
$ git clone https://github.com/google/grpc-java.git
Then change your current directory to grpc-java/examples
:
$ cd grpc-java/examples
You also should have the relevant tools installed to generate the server and client interface code - if you don't already, follow the setup instructions in the Java quick start guide.
Defining the service
Our first step (as you'll know from Getting started) is to define the gRPC service and the method request and response types using [protocol buffers] (https://developers.google.com/protocol-buffers/docs/overview). 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";
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 method, all of which are used in the RouteGuide
service:
- A simple RPC where the client sends a request to the server using the stub and waits for a response to come back, just like a normal function call.
// Obtains the feature at a given position.
rpc GetFeature(Point) returns (Feature) {}
- A server-side streaming RPC where the client sends a request to the server and gets a stream to read a sequence of messages back. The client reads from the returned stream until there are no more messages. As you can see in our example, you specify a server-side streaming method by placing the
stream
keyword before the response type.
// 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) {}
- A client-side streaming RPC where the client writes a sequence of messages and sends them to the server, again using a provided stream. Once the client has finished writing the messages, it waits for the server to read them all and return its response. You specify a server-side streaming method by placing the
stream
keyword before the request type.
// Accepts a stream of Points on a route being traversed, returning a
// RouteSummary when traversal is completed.
rpc RecordRoute(stream Point) returns (RouteSummary) {}
- A bidirectional streaming RPC where both sides send a sequence of messages using a read-write stream. The two streams operate independently, so clients and servers can read and write in whatever order they like: for example, the server could wait to receive all the client messages before writing its responses, or it could alternately read a message then write a message, or some other combination of reads and writes. The order of messages in each stream is preserved. You specify this type of method by placing the
stream
keyword before both the request and the response.
// 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.
For simplicity, we've provided a Gradle build file that runs protoc
for you with the appropriate plugin, input, and output (if you want to run this yourself, make sure you've installed protoc and followed the gRPC code installation instructions first):
gradle build
which actually runs:
[actual command]
Running this command generates the following files:
RouteGuideOuterClass.java
[cheeeeeeck], which contains all the protocol buffer code to populate, serialize, and retrieve our request and response message typesRouteGuideGrpc.java
which contains (along with some other useful code):- an interface for
RouteGuide
servers to implement,RouteGuideGrpc.Service
, with all the methods defined in theRouteGuide
service. - stub classes that clients can use to talk to a
RouteGuide
server. These also implement theRouteGuide
interface.
- an interface for
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:
- Implementing the service interface generated from our service definition: doing the actual "work" of our service.
- Running a gRPC server to listen for requests from clients and return the service responses.
You can find our example RouteGuide
server in grpc-java/examples/src/main/java/io/grpc/examples/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 implements the generated RouteGuideGrpc.Service
interface:
private static class RouteGuideService implements RouteGuideGrpc.RouteGuide {
...
}
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.onValue(getFeature(request));
responseObserver.onCompleted();
}
...
private Feature getFeature(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:
Point
: the requestStreamObserver<Feature>
: a response observer, which is a special interface for the server to call with its response.
To return our response to the client and complete the call:
- 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 privategetFeature()
method. - We use the response observer's
onValue()
method to return theFeature
. - We use the response observer's
onCompleted()
method to specify that we've finished dealing with the RPC.
Next let's look at a streaming RPC. ListFeatures
is a server-side streaming RPC, so we need to send back multiple Feature
s 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.onValue(feature);
}
}
responseObserver.onCompleted();
}
Like the simple RPC, this method gets a request object (the Rectangle
in which our client wants to find Feature
s) 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 Write()
method. Finally, as in our simple RPC, we use the response observer's onCompleted()
method to tell gRPC that we've finished writing responses.
Now let's look at something a little more complicated: the client-side streaming method RecordRoute
, where we get a stream of Point
s 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 onValue(Point point) {
pointCount++;
if (RouteGuideUtil.exists(getFeature(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.onValue(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 Point
s.
In the method body we instantiate an anonymous StreamObserver
to return, in which we:
- Override the
onValue()
method to get features and other information each time the client writes aPoint
to the message stream. - Override the
onCompleted()' method (called when the *client* has finished writing messages) to populate and build our
RouteSummary. We then call our method's own response observer's
onValue()with our
RouteSummary, and then call its
onCompleted()` method to finish the call from the server side.
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 onValue(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.onValue(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 void start() {
gRpcServer = NettyServerBuilder.forPort(port)
.addService(RouteGuideGrpc.bindService(new RouteGuideService(features)))
.build().start();
logger.info("Server started, listening on " + port);
...
}
As you can see, we build and start our server using a NettyServerBuilder
. To do this, we:
- Create an instance of our service implementation class
RouteGuideService
and pass it to the generatedRouteGuideGrpc
class's staticbindService()
method to get a service definition. - Specify the address and port we want to use to listen for client requests using the builder's
forPort()
method. - Register our service implementation with the builder by passing the service definition returned from
bindService()
to the builder'saddService()
method. - Call
build()
andstart()
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/RouteGuideClient.java.
Creating a stub
To call service methods, we first need to create a stub, or rather, two stubs:
- a blocking/synchronous stub: this means that the RPC call waits for the server to respond, and will either return a response or raise an exception.
- a non-blocking/asynchronous stub that makes non-blocking calls to the server, where the response is returned asynchronously. You can make certain types of streaming call only using the asynchronous stub.
First we need to create a gRPC channel for our stub, specifying the server address and port we want to connect to:
channel = NettyChannelBuilder.forAddress(host, port)
.negotiationType(NegotiationType.PLAINTEXT)
.build();
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
Streaming RPCs
Try it out!
[need build and run instructions here]