Structured streaming is a scalable and fault-tolerant stream processing engine built on top of Spark SQL engine. This brings stream processing and computations closer to batch processing, rather than the DStream paradigm and challenges involved with Spark streaming APIs at this time. The structured streaming engine takes care of several challenges like exactly-once stream processing, incremental updates to results of processing, aggregations, and so on.
The structured streaming API also provides the means to tackle a big challenge of Spark streaming, that is, Spark streaming processes incoming data in micro-batches and uses the received time as a means of splitting the data, thus not considering the actual event time of the data. The structured streaming allows you to specify such an event time in the data being received so that any late coming data is automatically...