Spark Streaming concepts
The Spark framework and all its extensions together provide one universal solution to handle all enterprise data needs from batch to analytics to real time. To be able to handle the real-time data processing, the framework should be capable of processing unbounded streams of data as close to the time of occurrence of the event as possible. This capability is provided by virtue of microbatching and stream processing under the Spark Streaming extension of the Spark framework.
In very simple terms, we can understand that a data stream is an unbounded sequence of data that is being generated in real-time continuously. Now to be able to process these continuously arriving data streams, various frameworks handle them as follows:
- Distinct discrete events that are processed individually
- Microbatching the individual events into very small-sized batches that are processed as a single unit
Spark provides this streaming API as an extension to its core API which is a scalable, low...
