gRPC Basics - Kotlin/JVM

A basic tutorial introduction to gRPC in Kotlin.


This tutorial provides a basic Kotlin 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 Kotlin gRPC API to write a simple client and server for your service.

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.

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-kotlin/examples/src/main/kotlin/io/grpc/examples/routeguide. To download the example, clone the latest release in grpc-kotlin repository by running the following command:

$ git clone https://github.com/grpc/grpc-kotlin.git

Then change to the example’s main source folder:

$ cd grpc-kotlin/examples/src/main/kotlin/io/grpc/examples/routeguide

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-kotlin/examples/src/main/proto/route_guide.proto.

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

service RouteGuide {
   ...
}

Then you define rpc methods inside your 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 client-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 Kotlin and Java plugins. 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. See the grpc-kotlin README for details.

The following classes are generated from our service definition:

  • Feature.java, Point.java, Rectangle.java, and others which contain all the protocol buffer code to populate, serialize, and retrieve our request and response message types.
  • RouteGuideGrpcKt.kt, which contains, among other things:
    • A base class for RouteGuide servers to implement, RouteGuideGrpcKt.RouteGuideCoroutineImplBase, with all the methods defined in the RouteGuide service.
    • The RouteGuideCoroutineStub class that clients use to talk to a RouteGuide server.

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:

  • Overriding the service base class 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-kotlin/examples/src/main/kotlin/io/grpc/examples/routeguide/RouteGuideServer.kt. 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 RouteGuideGrpcKt.RouteGuideCoroutineImplBase abstract class:

class RouteGuideService(
  val features: Collection<Feature>,
  /* ... */
) : RouteGuideGrpcKt.RouteGuideCoroutineImplBase() {
  /* ... */
}

Simple RPC

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

override suspend fun getFeature(request: Point): Feature =
    features.find { it.location == request } ?:
    // No feature was found, return an unnamed feature.
    Feature.newBuilder().apply { location = request }.build()

The method accepts a client’s Point message request as a parameter, and it returns a Feature message as a response. In the method we populate the Feature with the appropriate information, and then return it to the gRPC framework, which sends it back to the client.

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.

override fun listFeatures(request: Rectangle): Flow<Feature> =
  features.asFlow().filter { it.exists() && it.location in request }

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

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.

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 suspend fun recordRoute(requests: Flow<Point>): RouteSummary {
  var pointCount = 0
  var featureCount = 0
  var distance = 0
  var previous: Point? = null
  val stopwatch = Stopwatch.createStarted(ticker)
  requests.collect { request ->
    pointCount++
    if (getFeature(request).exists()) {
      featureCount++
    }
    val prev = previous
    if (prev != null) {
      distance += prev distanceTo request
    }
    previous = request
  }
  return RouteSummary.newBuilder().apply {
    this.pointCount = pointCount
    this.featureCount = featureCount
    this.distance = distance
    this.elapsedTime = Durations.fromMicros(stopwatch.elapsed(TimeUnit.MICROSECONDS))
  }.build()
}

The request parameter is a stream of client request messages represented as a Kotlin Flow. The server returns a single response just like in the simple RPC case.

Bidirectional streaming RPC

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

override fun routeChat(requests: Flow<RouteNote>): Flow<RouteNote> =
  flow {
    // could use transform, but it's currently experimental
    requests.collect { note ->
      val notes: MutableList<RouteNote> = routeNotes.computeIfAbsent(note.location) {
        Collections.synchronizedList(mutableListOf<RouteNote>())
      }
      for (prevNote in notes.toTypedArray()) { // thread-safe snapshot
        emit(prevNote)
      }
      notes += note
    }
  }

This time we get a stream of RouteNote objects that, as in our client-side streaming example, can be used to access messages.

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:

class RouteGuideServer private constructor(
  val port: Int,
  val server: Server
) {
  constructor(port: Int) : this(port, defaultFeatureSource())

  constructor(port: Int, featureData: ByteSource) :
  this(
    serverBuilder = ServerBuilder.forPort(port),
    port = port,
    features = featureData.parseJsonFeatures()
  )

  constructor(
    serverBuilder: ServerBuilder<*>,
    port: Int,
    features: Collection<Feature>
  ) : this(
    port = port,
    server = serverBuilder.addService(RouteGuideService(features)).build()
  )

  fun start() {
    server.start()
    println("Server started, listening on $port")
    /* ... */
  }

  companion object {
    @JvmStatic
    fun main(args: Array<String>) {
      val port = 8980
      val server = RouteGuideServer(port)
      server.start()
      /* ... */
    }
  }

  /* ... */
}

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 client for our RouteGuide service. You can see our complete example client code in grpc-kotlin/examples/src/main/kotlin/io/grpc/examples/routeguide/RouteGuideClient.kt.

Instantiating a stub

To call service methods, we first need to create a gRPC channel to communicate with the server. We use a ManagedChannelBuilder to create the channel:

val channel = ManagedChannelBuilder.forAddress("localhost", 8980).usePlaintext()

Once the gRPC channel is setup, we need a client stub to perform RPCs. We get it by instantiating RouteGuideCoroutineStub, which is available from the package that we generated from our .proto file.

val stub = RouteGuideCoroutineStub(channel)

Calling service methods

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

Simple RPC

Calling the simple RPC GetFeature() is as straightforward as calling a local method.

val request = point(latitude, longitude)
val feature = stub.getFeature(request)

The stub method getFeature() executes the corresponding RPC, suspending until the RPC completes. We want the client to await (or block) until the RPC completes, so we make the stub method call inside a [runBlocking][] coroutine builder. We wrap the entire body of the client class’s getFeature() helper method like this:

fun getFeature(latitude: Int, longitude: Int) = runBlocking {
  val request = point(latitude, longitude)
  val feature = stub.getFeature(request)
  if (feature.exists()) { /* ... */ }
}
Server-side streaming RPC

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

fun listFeatures(lowLat: Int, lowLon: Int, hiLat: Int, hiLon: Int) = runBlocking {
  val request = Rectangle.newBuilder()
    .setLo(point(lowLat, lowLon))
    .setHi(point(hiLat, hiLon))
    .build()
  var i = 1
  stub.listFeatures(request).collect { feature ->
    println("Result #${i++}: $feature")
  }
}

The stub listFeatures() method returns a stream of features in the form of a Flow<Feature> instance. The flow collect method allows the client to processes the server-provided features as they become available.

Client-side streaming RPC

With the client-side streaming RecordRoute() RPC, we send a stream of Point messages to the server and get back a single RouteSummary.

fun recordRoute(points: Flow<Point>) = runBlocking {
  println("*** RecordRoute")
  val summary = stub.recordRoute(points)
  println("Finished trip with ${summary.pointCount} points.")
  println("Passed ${summary.featureCount} features.")
  println("Travelled ${summary.distance} meters.")
  val duration = summary.elapsedTime.seconds
  println("It took $duration seconds.")
}

We generate the route points from the points associated with a randomly selected list of features. The random selection is taken from a previously loaded feature collection:

fun generateRoutePoints(features: List<Feature>, numPoints: Int): Flow<Point> = flow {
  for (i in 1..numPoints) {
    val feature = features.random(random)
    println("Visiting point ${feature.location.toStr()}")
    emit(feature.location)
    delay(timeMillis = random.nextLong(500L..1500L))
  }
}

Note that flow points are emitted lazily, that is, only once the server requests them. Once a point has been emitted to the flow, the point generator suspends until the server requests the next point.

Bidirectional streaming RPC

Finally, let’s look at our bidirectional streaming RPC RouteChat(). As in the case of RecordRoute(), we pass to the method a stream that we’ll use to write the request messages to; like in ListFeatures(), we get back a stream that we can use to read response messages from. However, this time we’ll send values via our method’s stream while the server is also writing messages to its message stream.

fun routeChat() = runBlocking {
  println("*** RouteChat")
  val requests = generateOutgoingNotes()
  stub.routeChat(requests).collect { note ->
    println("Got message \"${note.message}\" at ${note.location.toStr()}")
  }
  println("Finished RouteChat")
}

private fun generateOutgoingNotes(): Flow<RouteNote> = flow {
  val notes = listOf(/* ... */)
  for (note in notes) {
    println("Sending message \"${note.message}\" at ${note.location.toStr()}")
    emit(note);
    delay(500)
  }
}

The syntax for reading and writing here is very similar to our client-side and server-side 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.

Try it out!

  1. Work from the example directory:

    $ cd examples/route_guide
    
  2. Compile the client and server

    $ ./gradlew installDist
    
  3. Run the server:

    $ ./build/install/examples/bin/route-guide-server
    
  4. From another terminal, run the client:

    $ ./build/install/examples/bin/route-guide-client
    

You’ll see output like this:

*** GetFeature: lat=409146138 lon=-746188906
Found feature called "Berkshire Valley Management Area Trail, Jefferson, NJ, USA" at 40.9146138, -74.6188906
*** GetFeature: lat=0 lon=0
Found no feature at 0.0, 0.0
*** ListFeatures: lowLat=400000000 lowLon=-750000000 hiLat=420000000 liLon=-730000000
Result #1: name: "Patriots Path, Mendham, NJ 07945, USA"
location {
  latitude: 407838351
  longitude: -746143763
}
...
Result #64: name: "3 Hasta Way, Newton, NJ 07860, USA"
location {
  latitude: 410248224
  longitude: -747127767
}

*** RecordRoute
Visiting point 40.0066188, -74.6793294
...
Visiting point 40.4318328, -74.0835638
Finished trip with 10 points.
Passed 3 features.
Travelled 93238790 meters.
It took 9 seconds.
*** RouteChat
Sending message "First message" at 0.0, 0.0
Sending message "Second message" at 0.0, 0.0
Got message "First message" at 0.0, 0.0
Sending message "Third message" at 1.0, 0.0
Sending message "Fourth message" at 1.0, 1.0
Sending message "Last message" at 0.0, 0.0
Got message "First message" at 0.0, 0.0
Got message "Second message" at 0.0, 0.0
Finished RouteChat