In streaming applications domain there are many use cases where we require more advanced stateful operations than aggregations. For example, to track sessions from data streams of events, or for deduplicating data. For doing such sessionization, we will have to save arbitrary types of data as state, and perform arbitrary operations on the state using the data stream events in every trigger.

In this webinar explore more about Arbitrary Stateful Operations in Spark Structured Streaming.