Book Image

Data Engineering with Python

By : Paul Crickard
Book Image

Data Engineering with Python

By: Paul Crickard

Overview of this book

Data engineering provides the foundation for data science and analytics, and forms an important part of all businesses. This book will help you to explore various tools and methods that are used for understanding the data engineering process using Python. The book will show you how to tackle challenges commonly faced in different aspects of data engineering. You’ll start with an introduction to the basics of data engineering, along with the technologies and frameworks required to build data pipelines to work with large datasets. You’ll learn how to transform and clean data and perform analytics to get the most out of your data. As you advance, you'll discover how to work with big data of varying complexity and production databases, and build data pipelines. Using real-world examples, you’ll build architectures on which you’ll learn how to deploy data pipelines. By the end of this Python book, you’ll have gained a clear understanding of data modeling techniques, and will be able to confidently build data engineering pipelines for tracking data, running quality checks, and making necessary changes in production.
Table of Contents (21 chapters)
Section 1: Building Data Pipelines – Extract Transform, and Load
Section 2:Deploying Data Pipelines in Production
Section 3:Beyond Batch – Building Real-Time Data Pipelines

Chapter 12: Building a Kafka Cluster

In this chapter, you will move beyond batch processing – running queries on a complete set of data – and learn about the tools used in stream processing. In stream processing, the data may be infinite and incomplete at the time of a query. One of the leading tools in handling streaming data is Apache Kafka. Kafka is a tool that allows you to send data in real time to topics. These topics can be read by consumers who process the data. This chapter will teach you how to build a three-node Apache Kafka cluster. You will also learn how to create and send messages (produce) and read data from topics (consume).

In this chapter, we're going to cover the following main topics:

  • Creating ZooKeeper and Kafka clusters
  • Testing the Kafka cluster