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Machine Learning with Spark - Second Edition by Nick Pentreath, Manpreet Singh Ghotra, Rajdeep Dua

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Input sources

Spark Streaming receivers are responsible for receiving data from an input source and converting the raw data into a DStream made up of Spark RDDs.

Spark Streaming supports various input sources, including file-based sources (where the receiver watches for new files arriving at the input location and creates the DStream from the contents read from each new file) and network-based sources (such as receivers that communicate with socket-based sources, the Twitter API stream, Akka actors, or message queues and distributed stream and log transfer frameworks, such as Flume, Kafka, and Amazon Kinesis).

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