You're reading from Data Engineering with Scala and Spark

Product typeBook

Published inJan 2024

PublisherPackt

ISBN-139781804612583

Edition1st Edition

Concepts

Data Engineering

Authors (3):

Eric Tome

Rupam Bhattacharjee

David Radford

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Part 2 – Data Ingestion, Transformation, Cleansing, and Profiling Using Scala and Spark

In this part, Chapter 3 introduces Apache Spark as a scalable data processing framework, covering its basics, Scala application development, and the Dataset/DataFrame APIs. Chapter 4 explores relational databases in data pipelines, highlighting Spark’s JDBC API. Chapter 5 discusses the rise of data lakes and lake houses, while Chapter 6 delves into advanced Spark data transformation. Chapter 7 focuses on data quality with the Deequ library for checks and metrics.

This part has the following chapters:

Chapter 3, An Introduction to Apache Spark and Its APIs – DataFrame, Dataset, and Spark SQL
Chapter 4, Working with Databases
Chapter 5, Object Stores and Data Lakes
Chapter 6, Understanding Data Transformation
Chapter 7, Data Profiling and Data Quality

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Authors (3)

Eric Tome

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.
Read more about Eric Tome

Rupam Bhattacharjee

Rupam Bhattacharjee works as a lead data engineer at IBM. He has architected and developed data pipelines, processing massive structured and unstructured data using Spark and Scala for on-premises Hadoop and K8s clusters on the public cloud. He has a degree in electrical engineering.
Read more about Rupam Bhattacharjee

David Radford

David Radford has worked in big data for over 10 years, with a focus on cloud technologies. He led consulting teams for several years, completing a migration from legacy systems to modern data stacks. He holds a master's degree in computer science and works as a senior solutions architect at Databricks.
Read more about David Radford

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