Spark_Cosmosdb_cassandra.scala

# Spark Streaming with Cassandra (Azure Cosmos DB)
1. https://github.com/mspnp/azure-databricks-streaming-analytics

Spark_EventHub_Integration.scala

//Read from your Event Hub!
val df = spark.readStream
    .format("kafka")
    .option("subscribe", TOPIC)
    .option("kafka.bootstrap.servers", BOOTSTRAP_SERVERS)
    .option("kafka.sasl.mechanism", "PLAIN")
    .option("kafka.security.protocol", "SASL_SSL")
    .option("kafka.sasl.jaas.config", EH_SASL)
    .option("kafka.request.timeout.ms", "60000")
    .option("kafka.session.timeout.ms", "60000")
    .option("kafka.group.id", GROUP_ID)
    .option("failOnDataLoss", "false")
    .load()

//Use dataframe like normal (in this example, write to console)
val df_write = df.writeStream
    .outputMode("append")
    .format("console")
    .start()


Write to Event Hubs for Kafka
Writing to a Kafka-enabled Event Hub is easier than ever before. Just make sure to update the BOOTSTRAP_SERVERS and EH_SASL variables with the information from your EventHub namespace. Check out our example Spark producer for the full sample.

df = /**Dataframe**/

//Write to your Event Hub!
df.writeStream
    .format("kafka")
    .option("topic", TOPIC)
    .option("kafka.bootstrap.servers", BOOTSTRAP_SERVERS)
    .option("kafka.sasl.mechanism", "PLAIN")
    .option("kafka.security.protocol", "SASL_SSL")
    .option("kafka.sasl.jaas.config", EH_SASL)
    .option("checkpointLocation", "./checkpoint")
    .start()