Eric Tome, Rupam Bhattacharjee, David Radford

Data Engineering with Scala and Spark (eBook, ePUB)

Build streaming and batch pipelines that process massive amounts of data using Scala

• Format: ePub

Produktbeschreibung

Most data engineers know that performance issues in a distributed computing environment can easily lead to issues impacting the overall efficiency and effectiveness of data engineering tasks. While Python remains a popular choice for data engineering due to its ease of use, Scala shines in scenarios where the performance of distributed data processing is paramount.
This book will teach you how to leverage the Scala programming language on the Spark framework and use the latest cloud technologies to build continuous and triggered data pipelines. You’ll do this by setting up a data engineering environment for local development and scalable distributed cloud deployments using data engineering best practices, test-driven development, and CI/CD. You’ll also get to grips with DataFrame API, Dataset API, and Spark SQL API and its use. Data profiling and quality in Scala will also be covered, alongside techniques for orchestrating and performance tuning your end-to-end pipelines to deliver data to your end users.
By the end of this book, you will be able to build streaming and batch data pipelines using Scala while following software engineering best practices.

Produktdetails

• Verlag: Packt Publishing
• Seitenzahl: 300
• Erscheinungstermin: 31. Januar 2024
• Englisch
• ISBN-13: 9781804614327
• Artikelnr.: 69998344

Autorenporträt

Eric Tome has over 25 years of experience working with data. He has contributed to and led teams that ingested, cleansed, standardized, and prepared data used by business intelligence, data science, and operations teams. He has a background in mathematics and currently works as a senior solutions architect at Databricks, helping customers solve their data and AI challenges.