How to Write Events to Azure Event Hub in Scala Spark Job?

[Lomanu4]

Introduction


Writing events to Azure Event Hub using Scala can be quite challenging, especially if you're new to both Scala and the Azure ecosystem. If you're working with Spark v3.4 in an Azure Synapse Spark pool and you intend to utilize managed identities for authentication, you're on the right track. This blog post will walk you through how to correctly set up your Scala function to send messages to Azure Event Hub, while also addressing common issues, like the one you're encountering with class loading errors.

Understanding the Problem


From your description, it's clear that you're facing an IllegalAccessError when calling producer.createBatch() in your function. This issue arises when there are conflicts in class loading, which can often happen in environments like Spark where multiple libraries might be trying to load the same class from different sources.

The specific error message indicates that the class com.microsoft.aad.msal4j.AADAuthority cannot be accessed from com.microsoft.aad.msal4j.AbstractApplicationBase$Builder. This typically suggests that your project's classpath does not include the necessary libraries that are expected to be there for managing Azure Active Directory (AAD) authentication.

Step-by-Step Solution

1. Verify Your Dependencies


First and foremost, let's ensure that your build.gradle file is complete with the right dependencies. Although you already have the azure-messaging-eventhubs and azure-identity packages, you should also include msal4j, since it is required for AAD authentication.

Here's how your dependencies should look:

dependencies {
implementation 'com.azure:azure-messaging-eventhubs:5.20.2'
implementation 'com.azure:azure-identity:1.15.4'
implementation 'com.microsoft.azure:msal4j:1.10.0' // Add this dependency
}

2. Class Loading Issues


As you suspect, Spark can sometimes cause conflicts between different libraries due to the way it handles class loaders. Follow these configuration tips:

• Set user class path priority to ensure that user-defined classes take precedence over Spark’s internal classes:
  --conf spark.executor.userClassPathFirst=true
  --conf spark.driver.userClassPathFirst=true

This change can provide a potential fix and help avoid conflicts.

3. Writing Your Function


Now that dependencies and class loading are addressed, let's revisit your function:

import com.azure.messaging.eventhubs._
import com.azure.identity.ManagedIdentityCredentialBuilder

def sendMessageToEventHub(json: String, eventHubNamespace: String, eventHubName: String): Unit = {
// Use managed identity for authentication
val credential = new ManagedIdentityCredentialBuilder().build()

val producer = new EventHubClientBuilder()
.fullyQualifiedNamespace(eventHubNamespace)
.eventHubName(eventHubName)
.credential(credential)
.buildProducerClient()

val allEvents = Array(json)
println("Creating the batch")

try {
val eventDataBatch = producer.createBatch() // Create the batch
println("Batch created")

for (event <- allEvents) {
// Prepare your Event Data
val eventData = new EventData(event)
if (!eventDataBatch.tryAdd(eventData)) {
println("Event is too large for the current batch!")
}
}

// Send the event batch to Event Hub
producer.send(eventDataBatch)
println("Messages sent successfully.")
} catch {
case e: Exception => println(s"Failed to send messages: ${e.getMessage}")
} finally {
producer.close()
}
}

4. Testing Your Implementation


Now, deploy and test your functionality in Azure Synapse. Make sure you are running Spark v3.4 and that your Azure Event Hub is properly set up with access rights assigned to the managed identity your code is using.

Frequently Asked Questions (FAQ)

What if the problem persists after adding dependencies?


If you still encounter issues, you might want to check the versions of all the Azure SDK libraries you are using to ensure compatibility with Spark and Scala.

How do I verify my Managed Identity is set up correctly?


Use the Azure portal or CLI to check your Managed Identity’s permissions on the Event Hub. Ensure it has ‘Data Sender’ rights at the Event Hub namespace level.

Can I use other authentication methods?


While managed identity is recommended in Azure environments for better security, you can alternatively use connection strings for Event Hub if you encounter ongoing issues with managed identities.

Conclusion


By ensuring you have the right dependencies and configurations in place, you should be able to successfully send events from your Scala Spark job to Azure Event Hub using managed identities. Remember to check for version compatibility among the Azure libraries you’re using, especially when dealing with Spark environments.

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