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Spark Module 4 Streaming and Structured Streaming
featuring Structured Streaming and Apache Kafka
The course is over 3 hours long and with practical work should take a day or two to complete
- Learn how to use Apache Spark for real-time streaming big data!
- Both DStreams and Structured Streaming are covered
- Use Apache Kafka to build a near-continuous realtime big data pipeline
Contents
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Introduction and DStreams 55m 53s DStreams is an older API but it is still in use, so we'll establish the basics of Streaming with this API. We'll use a simple socket server to simulate a stream of data. |
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Integrating with Apache Kafka 77m 52s Apache Kafka is a highly performant, distributed event log and is perfect for use in streaming applications. Here we use it as a repository for holding a real time stream of events. We integrate with Spark Streaming using the Kafka module. |
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Structured Streaming 66m 45s This newer API builds on the SparkSQL/DataFrame API and is a much more elegant system. Through this chapter we rebuild our previous work, and we discover how it can be used to build a streaming pipeline. |
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