Kafka and Spark

Advanced Stream Processing you own this product

This project is part of the liveProject series Stream Processing with Kafka and Spark
prerequisites
intermediate Scala • basic Spark (DataFrame)
skills learned
perform complex arbitrary stateful computation on streams (such as handling out-of-order data and custom computation) • set up a Spark cluster • test your solution on the local cluster

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Look inside

You’re the star data engineer at Free Power Corporation Limited (FPCL). The London-based power company is interested in gaining insight into its customers’ energy usage patterns, and it’s up to you to deliver a data-rich solution that satisfies the requirements of FPCL’s various teams. You’ll create a streaming Spark application to read the consumer event stream from Kafka, you’ll add information that helps the teams determine when data was generated, ingested, and processed, and you’ll write logic to reorder any late or out-of-order data. To provide vital household energy consumption statistics to the sales and electrical engineering teams, you’ll join Kafka data streams and perform complex computations on the resulting stream. To be sure your solution is ready for the teams to use, you’ll test it on the local Spark cluster. When you’ve finished, you’ll have learned advanced stream processing skills that empower you to meet the different business requirements of various enterprise departments.

This project is designed for learning purposes and is not a complete, production-ready application or solution.

book resources

When you start your liveProject, you get full access to the following books for 90 days.

project author

Gaurav Bhardwaj

Gaurav Bhardwaj has almost two decades of experience designing and developing enterprise software for large-scale data processing and machine learning. Currently working as a Big Data Architect for an IT consulting firm, he helps clients build mature data platforms (on-prem, cloud, and hybrid) and develops solutions involving large-scale data processing, data management and governance, machine learning models, and more. He has also authored official documentation for Apache HBase coprocessor.

prerequisites

This liveProject is for basic Scala developers and data engineers who want to learn advanced real-time data streaming skills using Apache Spark and Kafka. To begin these liveProjects you’ll need to be familiar with the following:

TOOLS
  • The data stream from the first liveProject in this series, Ingest Consumer Data
  • Spark
  • Command-line tools
  • Intermediate Scala knowledge
  • An IDE (such as IntelliJ, Eclipse, or VS Code)
TECHNIQUES
  • Spark basics (including reading, writing, and performing simple transformations on DataFrames)

you will learn

In this liveProject, you’ll learn to perform advanced data stream processing in order to meet the different business requirements of various enterprise departments.

  • Different notions of event times in real-time stream processing
  • Handle late and out-of-order data
  • Join two streams
  • Use arbitrary stateful processing for advanced stream processing
  • Deploy and test on a local cluster

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book resources
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