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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.
Himanshu Gupta is a lead consultant having more than 4 years of experience. He is always keen to learn new technologies. He not only likes programming languages but Data Analytics too. He has sound knowledge of "Machine Learning" and "Pattern Recognition". He believes that best result comes when everyone works as a team. He likes listening to Coding, music, watch movies, and read science fiction books in his free time.
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