Streaming is the process of dividing continuously flowing input data into discreet units so that it can be processed easily. Familiar examples in real life are streaming video and audio content (though a user can download the full movie before he/she can watch it, a faster solution is to stream data in small chunks that start playing for the user while the rest of the data is being downloaded in the background).

Real-world examples of streaming, besides multimedia, are the processing of market feeds, weather data, electronic stock trading data, and so on. All of these applications produce large volumes of data at very fast rates and require special handling of the data so that insights can be derived from data in real time.

Streaming has a few basic concepts, which are better to understand before we focus on Spark Streaming. The rate at which a streaming application receives data is called data rate and is expressed in the form of kilobytes per second (kbps) or megabytes per second...