Getting Started with Spark Streaming


With the broader adoption of message brokers like Apache Kafka as well as distributed, message-sending architectures, the need for tools which can process vast amounts of data quickly became critical. To fill this need, we have several competing products, including Spark Streaming. In this talk, we will understand the use cases for stream processing and how Spark's concept of distributed batch processing reduces down to micro batches in the streaming case. We will understand the two streaming models for Spark, DStreams and Structured Streaming with DataFrames, and will see examples of streaming applications in Scala and F#.


No recordings or additional media are available for this talk.