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intermediate Scala • run simple shell/bash commands • basic Kafka (topics, partitions)
skills learned
set up Kafka Cluster • write a Kafka Producer • add real-life complexities to data • ingest the data into the Kafka cluster

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As a first step in dealing with surging energy prices, Free Power Corporation Limited (FPCL) has installed Smart Meters, which generate energy readings every thirty minutes, in households across London in order to analyze consumers’ energy usage. As a new data engineer for the power company, your task is to ingest the data from the Smart Meter readings and stream it to FPCL data centers for processing. Using the Kafka command-line tool, you’ll create topics in a Kafka cluster for storing the data, and you’ll create partitions for distributing the load within the topics. You’ll add logic to deal with potential problems such as data loss and duplicate records, and you’ll add a method to convert the energy readings to the widely used, easy-to-parse JSON format before the final step of ingesting the data. When you’re finished, FPCL will have pertinent data for analyzing energy consumption patterns, and you’ll have practical experience using Kafka to ingest large amounts of data.

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

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.


This liveProject is for basic Scala developers and data engineers who want to learn to ingest large amounts of data using Kafka. To begin these liveProjects you’ll need to be familiar with the following:

  • Command-line tools
  • Intermediate Scala knowledge
  • An IDE (such as IntelliJ, Eclipse, or VS Code)
  • Use Kafka command-line tools to create topics and partitions and start/stop a local Kafka cluster
  • Delete logs and events


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