You're reading from Data Engineering with AWS - Second Edition

Product typeBook

Published inOct 2023

PublisherPackt

ISBN-139781804614426

Edition2nd Edition

Concepts

Data Engineering

Author (1)

Gareth Eagar

Types of data transformation tools

As we covered in Chapter 3, The AWS Data Engineer’s Toolkit, there are a number of AWS services that can be used for data transformation. We reviewed a number of these services in that chapter, so make sure to review it again, but in this section, we will look more broadly at the different types of data transformation engines.

Apache Spark

Apache Spark is an in-memory engine for working with large datasets, providing a mechanism to split a dataset among multiple nodes in a cluster for efficient processing. Spark is an extremely popular engine to use for processing and transforming big datasets, and there are multiple ways to run Spark jobs within AWS.

With Apache Spark, you can either process data in batches (such as on a daily basis or every few hours) or process near real-time streaming data using Spark Streaming. In addition, you can use Spark SQL to process data using standard SQL, and Spark ML for applying machine learning...

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Data Engineering with AWS - Second Edition

Published in: Oct 2023Publisher: PacktISBN-13: 9781804614426

Author (1)

Gareth Eagar

Gareth Eagar has over 25 years of experience in the IT industry, starting in South Africa, working in the United Kingdom for a while, and now based in the USA. Having worked at AWS since 2017, Gareth has broad experience with a variety of AWS services, and deep expertise around building data platforms on AWS. While Gareth currently works as a Solutions Architect, he has also worked in AWS Professional Services, helping architect and implement data platforms for global customers. Gareth frequently speaks on data related topics.
Read more about Gareth Eagar

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You're reading from Data Engineering with AWS - Second Edition

Types of data transformation tools

Apache Spark

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