In this blog we’ll discuss the concept of Structured Streaming and how a data ingestion path can be built using Azure Databricks to enable the streaming of data in near-real-time. We’ll touch on some of the analysis capabilities which can be called from directly within Databricks utilising the Text Analytics API and also discuss how Databricks can be connected directly into Power BI for further analysis and reporting. As a final step we cover how streamed data can be sent from Databricks to Cosmos DB as the persistent storage.
Structured streaming is a stream processing engine which allows express computation to be applied on streaming data (e.g. a Twitter feed). In this sense it is very similar to the way in which batch computation is executed on a static dataset. Computation is performed incrementally via the Spark SQL engine which updates the result as a continuous process as the streaming data flows in.
Read more about it in the Azure blog.