Developing a stream processing solution using ASA, Azure Databricks, and Azure Event Hubs

In this section, we will look at two examples: one with ASA as the streaming engine and another with Spark as the streaming engine. We will use a dummy event generator to continuously generate trip events. We will configure both ASA and Azure Databricks Spark to perform real-time processing and publish the results. First, let's start with ASA.

A streaming solution using Event Hubs and ASA

In this example, we will be creating a streaming pipeline by creating an Event Hubs instance, an ASA instance, and linking them together. The pipeline will then read a sample stream of events, process the data, and display the result in Power BI:

1. First, let's create an Event Hub instance. From the Azure portal, search for Event Hubs and click on the Create button, as shown in the following screenshot:

Figure 10.3 – The Event Hubs creation screen

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