Basics tutorial

A basic tutorial introduction to gRPC in Kotlin.

Basics tutorial

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.

You should already be familiar gRPC and protocol buffers; if not, see Introduction to gRPC and 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 generate clients and servers in any of gRPC’s supported languages, which in turn can be run in environments ranging from servers inside a large data center 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.

Setup

This tutorial has the same prerequisites as the Quick start. Install the necessary SDKs and tools before proceeding.

Get the example code

The example code is part of the grpc-kotlin repo.

  1. Download the repo as a zip file and unzip it, or clone the repo:

    git clone --depth 1 https://github.com/grpc/grpc-kotlin

  2. Change to the examples directory:

    cd grpc-kotlin/examples

Defining the service

Your first step (as you’ll know from the Introduction to gRPC) is to define the gRPC service and the method request and response types using protocol buffers.

If you’d like to follow along by looking at the complete .proto file, see routeguide/route_guide.proto from the protos/src/main/proto/io/grpc/examples folder.

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

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) {}

The .proto file also contains protocol buffer message type definitions for all the request and response types used by the 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, you need to generate the gRPC client and server interfaces from the .proto service definition. You do this using the protocol buffer compiler protoc with special gRPC Kotlin and Java plugins.

When using Gradle or Maven, the protoc build plugin will generate the necessary code as part of the build process. For a Gradle example, see stub/build.gradle.kts.

If you run ./gradlew installDist from the examples folder, the following files are generated from the service definition – you’ll find the generated files in subdirectories below stub/build/generated/source/proto/main:

  • 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.

    You’ll find these files in the java/io/grpc/examples/routeguide subdirectory.

  • RouteGuideOuterClassGrpcKt.kt, which contains, among other things:

    • RouteGuideGrpcKt.RouteGuideCoroutineImplBase, an abstract base class for RouteGuide servers to implement, with all the methods defined in the RouteGuide service.
    • RouteGuideGrpcKt.RouteGuideCoroutineStub, a class that clients use to talk to a RouteGuide server.

    You’ll find this Kotlin file under grpckt/io/grpc/examples/routeguide.

Creating the server

First consider how to create a RouteGuide server. If you’re only interested in creating gRPC clients, skip ahead to Creating the client – though you might find this section interesting anyway!

There are two main things that you need to do when creating a RouteGuide server:

  • Extend the RouteGuideCoroutineImplBase service base class to do the actual service work.
  • Create and run a gRPC server to listen for requests from clients and return the service responses.

Open the example RouteGuide server code in routeguide/RouteGuideServer.kt under the server/src/main/kotlin/io/grpc/examples folder.

Implementing RouteGuide

As you can see, the server has a RouteGuideService class that extends the generated service base class:

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

RouteGuideService implements all the service methods. Consider the simplest method first, GetFeature(), which gets a Point from the client and returns a Feature built from the corresponding feature information in the database.

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. The method populates the Feature with the appropriate information, and then returns it to the gRPC framework, which sends it back to the client.

Server-side streaming RPC

Next, consider one of the streaming RPCs. ListFeatures() is a server-side streaming RPC, so the server gets to send back multiple Feature messages to the client.

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

The request object is a Rectangle. The server collects, and returns to the client, all the Feature objects in its collection that are inside the given Rectangle.

Client-side streaming RPC

Now consider something a little more complicated: the client-side streaming method RecordRoute(), where the server gets a stream of Point objects from the client, and returns a single RouteSummary with information about their trip through the given points.

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, consider the 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
    }
  }

Similar to the client-side streaming example, for this method, the server gets a stream of RouteNote objects as a Flow. However, this time the server returns RouteNote instances via the method’s returned stream while the client is still writing messages to its message stream.

Starting the server

Once all the server’s methods are implemented, you need code to create a gRPC server instance, something like this:

class RouteGuideServer(
    val port: Int,
    val features: Collection<Feature> = Database.features(),
    val server: Server =
      ServerBuilder.forPort(port)
        .addService(RouteGuideService(features)).build()
) {

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

fun main(args: Array<String>) {
  val port = 8980
  val server = RouteGuideServer(port)
  server.start()
  server.awaitTermination()
 }

A server instance is built and started using a ServerBuilder as follows:

  1. Specify the port, that the server will listen for client requests on, using forPort().
  2. Create an instance of the 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 the route guide service.
  4. Call awaitTermination() on the server to block the main function until the application receives a signal to terminate.

Creating the client

In this section, you’ll look at a client for the RouteGuide service.

For the complete client code, open routeguide/RouteGuideClient.kt under the client/src/main/kotlin/io/grpc/examples folder.

Instantiating a stub

To call service methods, you first need to create a gRPC channel using a ManagedChannelBuilder. You’ll use this channel to communicate with the server.

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

Once the gRPC channel is setup, you need a client stub to perform RPCs. Get it by instantiating RouteGuideCoroutineStub, which is available from the package that was generated from the .proto file.

val stub = RouteGuideCoroutineStub(channel)

Calling service methods

Now consider how you’ll call 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:

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

Next, consider the server-side streaming ListFeatures() RPC, which returns a stream of geographical features:

suspend fun listFeatures(lowLat: Int, lowLon: Int, hiLat: Int, hiLon: Int) {
  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

The client-side streaming RecordRoute() RPC sends a stream of Point messages to the server and gets back a single RouteSummary.

suspend fun recordRoute(points: Flow<Point>) {
  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.")
}

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

suspend fun 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 the 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!

Run the following commands from the grpc-kotlin/examples directory:

  1. Compile the client and server

    ./gradlew installDist

  2. Run the server:

    ./server/build/install/server/bin/route-guide-server
Server started, listening on 8980

  3. From another terminal, run the client:

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

You’ll see client 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
Last modified November 25, 2024: feat: move the $ shell line indicator to scss (#1354) (ab8b3af)
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