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.
publication date
2024-01-31
what you will learn
Set up your development environment to build pipelines in Scala
Get to grips with polymorphic functions, type parameterization, and Scala implicits
Use Spark DataFrames, Datasets, and Spark SQL with Scala
Read and write data to object stores
Profile and clean your data using Deequ
Performance tune your data pipelines using Scala
key features
Transform data into a clean and trusted source of information for your organization using Scala * Build streaming and batch-processing pipelines with step-by-step explanations * Implement and orchestrate your pipelines by following CI/CD best practices and test-driven development (TDD) * Purchase of the print or Kindle book includes a free PDF eBook
approach
Complete with step-by-step explanations of essential concepts, and practical examples, you will begin by learning the basics of Scala and Spark, and how to build real-time and batch data pipelines from start to finish.
audience
This book is for data engineers who have experience in working with data and want to understand how to transform raw data into a clean, trusted, and valuable source of information for their organization using Scala and the latest cloud technologies.
short description
Learn new techniques to ingest, transform, merge, and deliver trusted data to downstream users using modern cloud data architectures and Scala, and learn end-to-end data engineering that will make you the most valuable asset on your data team.
subtitle
Build streaming and batch pipelines that process massive amounts of data using Scala
keywords
Data Engineering, Data Processing, ETL, ELT, Data Transformation, Data Ingestion, Data Quality, Spark, Scala, Apache Spark, Software Engineering, Stream Processing, Batch Processing, Real-time analytical processing, Data Analysis, CI/CD, Test-driven development
Product ISBN
9781804612583
