IoTHubReact

IoTHub React is an Akka Stream library that can be used to read data from Azure IoT Hub, via a reactive stream with asynchronous back pressure, and to send messages to connected devices. Azure IoT Hub is a service used to connect thousands to millions of devices to the Azure cloud.

The following is a simple example showing how to use the library in Scala. A stream of incoming telemetry data is read, parsed and converted to a Temperature object, and then filtered based on the temperature value:

IoTHub().source()
    .map(m => parse(m.contentAsString).extract[Temperature])
    .filter(_.value > 100)
    .to(console)
    .run()

and the equivalent code in Java:

TypeReference<Temperature> type = new TypeReference<Temperature>() {};

new IoTHub().source()
    .map(m -> (Temperature) jsonParser.readValue(m.contentAsString(), type))
    .filter(x -> x.value > 100)
    .to(console())
    .run(streamMaterializer);

Streaming from IoT hub to any

A more interesting example is reading telemetry data from Azure IoT Hub, and sending it to a Kafka topic, so that it can be consumed by other services downstream:

... 
import org.apache.kafka.common.serialization.StringSerializer
import org.apache.kafka.common.serialization.ByteArraySerializer
import org.apache.kafka.clients.producer.ProducerRecord
import akka.kafka.ProducerSettings
import akka.kafka.scaladsl.Producer

case class KafkaProducer(bootstrapServer: String)(implicit val system: ActorSystem) {

  protected val producerSettings = ProducerSettings(system, new ByteArraySerializer, new StringSerializer)
    .withBootstrapServers(bootstrapServer)

  def getSink() = Producer.plainSink(producerSettings)

  def packageMessage(elem: String, topic: String): ProducerRecord[Array[Byte], String] = {
    new ProducerRecord[Array[Byte], String](topic, elem)
  }
}

val kafkaProducer = KafkaProducer(bootstrapServer)
 
IoTHub().source()
    .map(m => parse(m.contentAsString).extract[Temperature])
    .filter(_.value > 100)
    .runWith(kafkaProducer.getSink())

Source options

IoT hub partitions

The library supports also reading from a single IoTHub partition, so a service that consumes IoTHub events can create multiple streams and process them independently.

val partitionNumber = 1

IoTHubPartition(partitionNumber).source()
    .map(m => parse(m.contentAsString).extract[Temperature])
    .filter(_.value > 100)
    .to(console)
    .run()

Starting point

Unless specified, the stream starts from the beginning of the data present in each partition. It's possible to start the stream from a given date and time too:

val start = java.time.Instant.now()

IoTHub().source(start)
    .map(m => parse(m.contentAsString).extract[Temperature])
    .filter(_.value > 100)
    .to(console)
    .run()

Stream processing restart - saving the current position

The library provides a mechanism to restart the stream from a recent checkpoint, to be resilient to restarts and crashes. Checkpoints are saved automatically, with a configured frequency, on a storage provided. For instance, the stream position can be saved every 15 seconds, in a table in Cassandra, or using Azure blobs, or a custom backend.

To store checkpoints in Azure blobs the configuration looks like this:

iothub-react{

  [... other settings ...]
  
  checkpointing {
    enabled = true
    frequency = 15s
    countThreshold = 1000
    timeThreshold = 30s
    
    storage {
      rwTimeout = 5s
      namespace = "iothub-react-checkpoints"
      
      backendType = "AzureBlob"
      azureblob {
        lease = 15s
        useEmulator = false
        protocol = "https"
        account = "..."
        key = "..."
      }
    }
  }
}

Similarly, to store checkpoints in Cassandra:

iothub-react{
  [...]
  checkpointing {
    [...]
    storage {
      [...]
      
      backendType = "cassandra"
      cassandra {
        cluster = "localhost:9042"
        replicationFactor = 3
      }
    }
  }
}

There are some configuration settings to manage the checkpoint behavior, and in future it will also be possible to plug-in custom storage backends, implementing a simple interface to read and write the stream position.

There is also one API parameter to enabled/disable the checkpointing feature, for example:

val start = java.time.Instant.now()
val withCheckpoints = false

IoTHub().source(start, withCheckpoints)
    .map(m => parse(m.contentAsString).extract[Temperature])
    .filter(_.value > 100)
    .to(console)
    .run()

Build configuration

IoTHubReact is available on Maven Central, you just need to add the following reference in your build.sbt file:

libraryDependencies ++= {
  val iothubReactV = "0.8.0"
  
  Seq(
    "com.microsoft.azure.iot" %% "iothub-react" % iothubReactV
  )
}

or this dependency in pom.xml file if working with Maven:

<dependency>
    <groupId>com.microsoft.azure.iot</groupId>
    <artifactId>iothub-react_2.12</artifactId>
    <version>0.8.0</version>
</dependency>

IoTHub configuration

IoTHubReact uses a configuration file to fetch the parameters required to connect to Azure IoT Hub. The exact values to use can be found in the Azure Portal:

hubName: see Endpoints ⇒ Messaging ⇒ Events ⇒ Event Hub-compatible name
hubEndpoint: see Endpoints ⇒ Messaging ⇒ Events ⇒ Event Hub-compatible endpoint
hubPartitions: see Endpoints ⇒ Messaging ⇒ Events ⇒ Partitions
accessPolicy: usually service, see Shared access policies
accessKey: see Shared access policies ⇒ key name ⇒ Primary key (it's a base64 encoded string)
accessHostName: see Shared access policies ⇒ key name ⇒ Connection string ⇒ HostName

The values should be stored in your application.conf resource (or equivalent). Optionally you can reference environment settings if you prefer, for example to hide sensitive data.

iothub-react {

  connection {
    hubName        = "<Event Hub compatible name>"
    hubEndpoint    = "<Event Hub compatible endpoint>"
    hubPartitions  = <the number of partitions in your IoT Hub>
    accessPolicy   = "<access policy name>"
    accessKey      = "<access policy key>"
    accessHostName = "<access host name>"
  }
  
  [... other settings...]
}

Example using environment settings:

iothub-react {

  connection {
    hubName        = ${?IOTHUB_EVENTHUB_NAME}
    hubEndpoint    = ${?IOTHUB_EVENTHUB_ENDPOINT}
    hubPartitions  = ${?IOTHUB_EVENTHUB_PARTITIONS}
    accessPolicy   = ${?IOTHUB_ACCESS_POLICY}
    accessKey      = ${?IOTHUB_ACCESS_KEY}
    accessHostName = ${?IOTHUB_ACCESS_HOSTNAME}
  }
  
  [... other settings...]
}

The logging level can be managed via akka configuration, for example:

akka {
  # Options: OFF, ERROR, WARNING, INFO, DEBUG
  loglevel = "WARNING"
}

There are other settings, to tune performance and connection details:

streaming.consumerGroup: the consumer group used during the connection
streaming.receiverBatchSize: the number of messages retrieved on each call to Azure IoT hub. The default (and maximum) value is 999.
streaming.receiverTimeout: timeout applied to calls while retrieving messages. The default value is 3 seconds.
checkpointing.enabled: whether checkpointing is eanbled

The complete configuration reference is available in reference.conf.

Samples

The project includes 4 demos, showing some of the use cases and how IoThub React API works. All the demos require an instance of Azure IoT hub, with some devices, and messages.

DisplayMessages [Java]: how to stream Azure IoT hub withing a Java application, filtering temperature values greater than 60C
OutputMessagesToConsole [Scala]: stream all Temeprature events to console
MessagesThroughput [Scala]: stream all IoT hub messages, showing the current speed, and optionally throttling the speed to 200 msg/sec
Checkpoints [Scala]: demonstrate how the stream can be restarted without losing its position. The current position is stored in a Cassandra table (we suggest to run a docker container for the purpose of the demo, e.g. docker run -ip 9042:9042 --rm cassandra)

We provide a device simulator in the tools section, which will help setting up these requirements.

When ready, you should either edit the application.conf configuration files (scala and java) with your credentials, or set the corresponding global variables. Follow the instructions in the previous section on how to set the correct values.

samples-scala: You can use sbt run to run the demos (or the run_samples.* scripts)
samples-java: You can use mvn clean compile exec:java -Dexec.mainClass="DisplayMessages.Demo" to run the demo app (or the run_samples.* scripts)

Future work

improve asynchronicity by using EventHub SDK async APIs
add Sink for Cloud2Device scenarios. IoTHub.Sink will allow cloud services to send messages to devices (via Azure IoTHub)

Contribute Code

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dluc / azure-iot-hub-reactive-akka-stream