Working with streaming IO

Dependency

To use Pekko Streams, add the module to your project:

sbt

val PekkoVersion = "1.0.3"
libraryDependencies += "org.apache.pekko" %% "pekko-stream" % PekkoVersion

Maven

<properties>
  <scala.binary.version>2.13</scala.binary.version>
</properties>
<dependencyManagement>
  <dependencies>
    <dependency>
      <groupId>org.apache.pekko</groupId>
      <artifactId>pekko-bom_${scala.binary.version}</artifactId>
      <version>1.0.3</version>
      <type>pom</type>
      <scope>import</scope>
    </dependency>
  </dependencies>
</dependencyManagement>
<dependencies>
  <dependency>
    <groupId>org.apache.pekko</groupId>
    <artifactId>pekko-stream_${scala.binary.version}</artifactId>
  </dependency>
</dependencies>

Gradle

def versions = [
  ScalaBinary: "2.13"
]
dependencies {
  implementation platform("org.apache.pekko:pekko-bom_${versions.ScalaBinary}:1.0.3")

  implementation "org.apache.pekko:pekko-stream_${versions.ScalaBinary}"
}

Introduction

Pekko Streams provides a way of handling File IO and TCP connections with Streams. While the general approach is very similar to the Actor based TCP handling using Pekko IO, by using Pekko Streams you are freed of having to manually react to back-pressure signals, as the library does it transparently for you.

Streaming TCP

Accepting connections: Echo Server

In order to implement a simple EchoServer we bind to a given address, which returns a SourceSource[IncomingConnectionIncomingConnection, Future[ServerBindingServerBinding]SourceSource<IncomingConnectionIncomingConnection, CompletionStage<ServerBindingServerBinding>>, which will emit an IncomingConnection element for each new connection that the Server should handle:

Scala

copysourceval binding: Future[ServerBinding] =
  Tcp(system).bind("127.0.0.1", 8888).to(Sink.ignore).run()

binding.map { b =>
  b.unbind().onComplete {
    case _ => // ...
  }
}

Java

copysource// IncomingConnection and ServerBinding imported from Tcp
final Source<IncomingConnection, CompletionStage<ServerBinding>> connections =
    Tcp.get(system).bind("127.0.0.1", 8888);

Next, we handle each incoming connection using a FlowFlow which will be used as the operator to handle and emit ByteStringByteString s from and to the TCP Socket. Since one ByteString does not have to necessarily correspond to exactly one line of text (the client might be sending the line in chunks) we use the Framing.delimiterFraming.delimiter helper Flow to chunk the inputs up into actual lines of text. The last boolean argument indicates that we require an explicit line ending even for the last message before the connection is closed. In this example we add exclamation marks to each incoming text message and push it through the flow:

Scala

copysourceimport org.apache.pekko.stream.scaladsl.Framing

val connections: Source[IncomingConnection, Future[ServerBinding]] =
  Tcp(system).bind(host, port)
connections.runForeach { connection =>
  println(s"New connection from: ${connection.remoteAddress}")

  val echo = Flow[ByteString]
    .via(Framing.delimiter(ByteString("\n"), maximumFrameLength = 256, allowTruncation = true))
    .map(_.utf8String)
    .map(_ + "!!!\n")
    .map(ByteString(_))

  connection.handleWith(echo)
}

Java

copysourceconnections.runForeach(
    connection -> {
      System.out.println("New connection from: " + connection.remoteAddress());

      final Flow<ByteString, ByteString, NotUsed> echo =
          Flow.of(ByteString.class)
              .via(
                  Framing.delimiter(
                      ByteString.fromString("\n"), 256, FramingTruncation.DISALLOW))
              .map(ByteString::utf8String)
              .map(s -> s + "!!!\n")
              .map(ByteString::fromString);

      connection.handleWith(echo, system);
    },
    system);

Notice that while most building blocks in Pekko Streams are reusable and freely shareable, this is not the case for the incoming connection Flow, since it directly corresponds to an existing, already accepted connection its handling can only ever be materialized once.

Closing connections is possible by cancelling the incoming connection FlowFlow from your server logic (e.g. by connecting its downstream to a Sink.cancelledSink.cancelled and its upstream to a Source.emptySource.empty. It is also possible to shut down the server’s socket by cancelling the IncomingConnectionIncomingConnection source connections.

We can then test the TCP server by sending data to the TCP Socket using netcat:

$ echo -n "Hello World" | netcat 127.0.0.1 8888
Hello World!!!

Connecting: REPL Client

In this example we implement a rather naive Read Evaluate Print Loop client over TCP. Let’s say we know a server has exposed a simple command line interface over TCP, and would like to interact with it using Pekko Streams over TCP. To open an outgoing connection socket we use the outgoingConnection method:

Scala

copysourceval connection = Tcp(system).outgoingConnection("127.0.0.1", 8888)

val replParser =
  Flow[String].takeWhile(_ != "q").concat(Source.single("BYE")).map(elem => ByteString(s"$elem\n"))

val repl = Flow[ByteString]
  .via(Framing.delimiter(ByteString("\n"), maximumFrameLength = 256, allowTruncation = true))
  .map(_.utf8String)
  .map(text => println("Server: " + text))
  .map(_ => readLine("> "))
  .via(replParser)

val connected = connection.join(repl).run()

Java

copysourcefinal Flow<ByteString, ByteString, CompletionStage<OutgoingConnection>> connection =
    Tcp.get(system).outgoingConnection("127.0.0.1", 8888);
final Flow<String, ByteString, NotUsed> replParser =
    Flow.<String>create()
        .takeWhile(elem -> !elem.equals("q"))
        .concat(Source.single("BYE")) // will run after the original flow completes
        .map(elem -> ByteString.fromString(elem + "\n"));

final Flow<ByteString, ByteString, NotUsed> repl =
    Flow.of(ByteString.class)
        .via(Framing.delimiter(ByteString.fromString("\n"), 256, FramingTruncation.DISALLOW))
        .map(ByteString::utf8String)
        .map(
            text -> {
              System.out.println("Server: " + text);
              return "next";
            })
        .map(elem -> readLine("> "))
        .via(replParser);

CompletionStage<OutgoingConnection> connectionCS = connection.join(repl).run(system);

The repl flow we use to handle the server interaction first prints the servers response, then awaits on input from the command line (this blocking call is used here for the sake of simplicity) and converts it to a ByteStringByteString which is then sent over the wire to the server. Then we connect the TCP pipeline to this operator–at this point it will be materialized and start processing data once the server responds with an initial message.

A resilient REPL client would be more sophisticated than this, for example it should split out the input reading into a separate mapAsync step and have a way to let the server write more data than one ByteString chunk at any given time, these improvements however are left as exercise for the reader.

Avoiding deadlocks and liveness issues in back-pressured cycles

When writing such end-to-end back-pressured systems you may sometimes end up in a situation of a loop, in which either side is waiting for the other one to start the conversation. One does not need to look far to find examples of such back-pressure loops. In the two examples shown previously, we always assumed that the side we are connecting to would start the conversation, which effectively means both sides are back-pressured and can not get the conversation started. There are multiple ways of dealing with this which are explained in depth in Graph cycles, liveness and deadlocks, however in client-server scenarios it is often the simplest to make either side send an initial message.

To break this back-pressure cycle we need to inject some initial message, a “conversation starter”. First, we need to decide which side of the connection should remain passive and which active. Thankfully in most situations finding the right spot to start the conversation is rather simple, as it often is inherent to the protocol we are trying to implement using Streams. In chat-like applications, which our examples resemble, it makes sense to make the Server initiate the conversation by emitting a “hello” message:

Scala

copysourceconnections
  .to(Sink.foreach { connection =>
    // server logic, parses incoming commands
    val commandParser = Flow[String].takeWhile(_ != "BYE").map(_ + "!")

    import connection._
    val welcomeMsg = s"Welcome to: $localAddress, you are: $remoteAddress!"
    val welcome = Source.single(welcomeMsg)

    val serverLogic = Flow[ByteString]
      .via(Framing.delimiter(ByteString("\n"), maximumFrameLength = 256, allowTruncation = true))
      .map(_.utf8String)
      .via(commandParser)
      // merge in the initial banner after parser
      .merge(welcome)
      .map(_ + "\n")
      .map(ByteString(_))

    connection.handleWith(serverLogic)
  })
  .run()

Java

copysourceconnections
    .to(
        Sink.foreach(
            (IncomingConnection connection) -> {
              // server logic, parses incoming commands
              final Flow<String, String, NotUsed> commandParser =
                  Flow.<String>create()
                      .takeWhile(elem -> !elem.equals("BYE"))
                      .map(elem -> elem + "!");

              final String welcomeMsg =
                  "Welcome to: "
                      + connection.localAddress()
                      + " you are: "
                      + connection.remoteAddress()
                      + "!";

              final Source<String, NotUsed> welcome = Source.single(welcomeMsg);
              final Flow<ByteString, ByteString, NotUsed> serverLogic =
                  Flow.of(ByteString.class)
                      .via(
                          Framing.delimiter(
                              ByteString.fromString("\n"), 256, FramingTruncation.DISALLOW))
                      .map(ByteString::utf8String)
                      .via(commandParser)
                      .merge(welcome)
                      .map(s -> s + "\n")
                      .map(ByteString::fromString);

              connection.handleWith(serverLogic, system);
            }))
    .run(system);

To emit the initial message we merge a SourceSource with a single element, after the command processing but before the framing and transformation to ByteStringByteString s this way we do not have to repeat such logic.

In this example both client and server may need to close the stream based on a parsed command - BYE in the case of the server, and q in the case of the client. This is implemented by taking from the stream until q and and concatenating a Source with a single BYE element which will then be sent after the original source completedusing a custom operator extending GraphStage which completes the stream once it encounters such command.

Using framing in your protocol

Streaming transport protocols like TCP only pass streams of bytes, and does not know what is a logical chunk of bytes from the application’s point of view. Often when implementing network protocols you will want to introduce your own framing. This can be done in two ways: An end-of-frame marker, e.g. end line \n, can do framing via Framing.delimiterFraming.delimiter. Or a length-field can be used to build a framing protocol. There is a bidi implementing this protocol provided by Framing.simpleFramingProtocolFraming.simpleFramingProtocol.

JsonFramingJsonFraming separates valid JSON objects from incoming ByteStringByteString objects:

Scala

copysourceval input =
  """
    |[
    | { "name" : "john" },
    | { "name" : "Ég get etið gler án þess að meiða mig" },
    | { "name" : "jack" },
    |]
    |""".stripMargin // also should complete once notices end of array

val result =
  Source.single(ByteString(input)).via(JsonFraming.objectScanner(64)).runFold(Seq.empty[String]) {
    case (acc, entry) => acc ++ Seq(entry.utf8String)
  }

Java

copysourceString input =
    "[{ \"name\" : \"john\" }, { \"name\" : \"Ég get etið gler án þess að meiða mig\" }, { \"name\" : \"jack\" }]";
CompletionStage<ArrayList<String>> result =
    Source.single(ByteString.fromString(input))
        .via(JsonFraming.objectScanner(Integer.MAX_VALUE))
        .runFold(
            new ArrayList<String>(),
            (acc, entry) -> {
              acc.add(entry.utf8String());
              return acc;
            },
            system);

TLS

Similar factories as shown above for raw TCP but where the data is encrypted using TLS are available from Tcp through outgoingConnectionWithTls, bindWithTls and bindAndHandleWithTls, see the `Tcp Scaladoc``Tcp Javadoc` for details.

Using TLS requires a keystore and a truststore and then a somewhat involved dance of configuring the SSLEngine and the details for how the session should be negotiated:

Scala

copysourceimport java.security.KeyStore
import javax.net.ssl.KeyManagerFactory
import javax.net.ssl.SSLContext
import javax.net.ssl.SSLEngine
import javax.net.ssl.TrustManagerFactory

import org.apache.pekko.stream.TLSRole

// initialize SSLContext once
lazy val sslContext: SSLContext = {
  // Don't hardcode your password in actual code
  val password = "abcdef".toCharArray

  // trust store and keys in one keystore
  val keyStore = KeyStore.getInstance("PKCS12")
  keyStore.load(getClass.getResourceAsStream("/tcp-spec-keystore.p12"), password)

  val trustManagerFactory = TrustManagerFactory.getInstance("SunX509")
  trustManagerFactory.init(keyStore)

  val keyManagerFactory = KeyManagerFactory.getInstance("SunX509")
  keyManagerFactory.init(keyStore, password)

  // init ssl context
  val context = SSLContext.getInstance("TLSv1.2")
  context.init(keyManagerFactory.getKeyManagers, trustManagerFactory.getTrustManagers, new SecureRandom)
  context
}

// create new SSLEngine from the SSLContext, which was initialized once
def createSSLEngine(role: TLSRole): SSLEngine = {
  val engine = sslContext.createSSLEngine()

  engine.setUseClientMode(role == pekko.stream.Client)
  engine.setEnabledCipherSuites(Array("TLS_RSA_WITH_AES_128_CBC_SHA"))
  engine.setEnabledProtocols(Array("TLSv1.2"))

  engine
}

Java

copysource// imports
import java.security.KeyStore;
import java.security.SecureRandom;
import javax.net.ssl.KeyManagerFactory;
import javax.net.ssl.SSLContext;
import javax.net.ssl.SSLEngine;
import javax.net.ssl.TrustManagerFactory;
import org.apache.pekko.stream.TLSRole;

  // initialize SSLContext once
  private final SSLContext sslContext;

  {
    try {
      // Don't hardcode your password in actual code
      char[] password = "abcdef".toCharArray();

      // trust store and keys in one keystore
      KeyStore keyStore = KeyStore.getInstance("PKCS12");
      keyStore.load(getClass().getResourceAsStream("/tcp-spec-keystore.p12"), password);

      TrustManagerFactory trustManagerFactory = TrustManagerFactory.getInstance("SunX509");
      trustManagerFactory.init(keyStore);

      KeyManagerFactory keyManagerFactory = KeyManagerFactory.getInstance("SunX509");
      keyManagerFactory.init(keyStore, password);

      // init ssl context
      SSLContext context = SSLContext.getInstance("TLSv1.2");
      context.init(
          keyManagerFactory.getKeyManagers(),
          trustManagerFactory.getTrustManagers(),
          new SecureRandom());

      sslContext = context;

    } catch (KeyStoreException
        | IOException
        | NoSuchAlgorithmException
        | CertificateException
        | UnrecoverableKeyException
        | KeyManagementException e) {
      throw new RuntimeException(e);
    }
  }

  // create new SSLEngine from the SSLContext, which was initialized once
  public SSLEngine createSSLEngine(TLSRole role) {
    SSLEngine engine = sslContext.createSSLEngine();

    engine.setUseClientMode(role.equals(org.apache.pekko.stream.TLSRole.client()));
    engine.setEnabledCipherSuites(new String[] {"TLS_DHE_RSA_WITH_AES_256_GCM_SHA384"});
    engine.setEnabledProtocols(new String[] {"TLSv1.2"});

    return engine;
  }

The SSLEngine instance can then be used with the binding or outgoing connection factory methods.

Streaming File IO

Pekko Streams provide simple Sources and Sinks that can work with ByteStringByteString instances to perform IO operations on files.

Streaming data from a file is as easy as creating a FileIO.fromPath given a target path, and an optional chunkSize which determines the buffer size determined as one “element” in such stream:

Scala

copysourceimport org.apache.pekko.stream.scaladsl._
val file = Paths.get("example.csv")

val foreach: Future[IOResult] = FileIO.fromPath(file).to(Sink.ignore).run()

Java

copysourcefinal Path file = Paths.get("example.csv");
  Sink<ByteString, CompletionStage<Done>> printlnSink =
      Sink.<ByteString>foreach(chunk -> System.out.println(chunk.utf8String()));

  CompletionStage<IOResult> ioResult = FileIO.fromPath(file).to(printlnSink).run(system);

Please note that these operators are backed by Actors and by default are configured to run on a pre-configured threadpool-backed dispatcher dedicated for File IO. This is very important as it isolates the blocking file IO operations from the rest of the ActorSystem allowing each dispatcher to be utilised in the most efficient way. If you want to configure a custom dispatcher for file IO operations globally, you can do so by changing the pekko.stream.materializer.blocking-io-dispatcher, or for a specific operator by specifying a custom Dispatcher in code, like this:

Scala

copysourceFileIO.fromPath(file).withAttributes(ActorAttributes.dispatcher("custom-blocking-io-dispatcher"))

Java

copysourceFileIO.toPath(file)
    .withAttributes(ActorAttributes.dispatcher("custom-blocking-io-dispatcher"));