Essential PySpark for Scalable Data Analytics: A beginner's guide to harnessing the power and ease of PySpark 3
Essential PySpark for Scalable Data Analytics: A beginner's guide to harnessing the power and ease of PySpark 3
English | 2021 | ISBN: 1800568878 | 322 Pages | EPUB | 5 MB
English | 2021 | ISBN: 1800568878 | 322 Pages | EPUB | 5 MB
Essential PySpark for Scalable Data Analytics starts by exploring the distributed computing paradigm and provides a high-level overview of Apache Spark. You'll begin your analytics journey with the data engineering process, learning how to perform data ingestion, cleansing, and integration at scale. This book helps you build real-time analytics pipelines that help you gain insights faster. You'll then discover methods for building cloud-based data lakes, and explore Delta Lake, which brings reliability to data lakes. The book also covers Data Lakehouse, an emerging paradigm, which combines the structure and performance of a data warehouse with the scalability of cloud-based data lakes. Later, you'll perform scalable data science and machine learning tasks using PySpark, such as data preparation, feature engineering, and model training and productionization. Finally, you'll learn ways to scale out standard Python ML libraries along with a new pandas API on top of PySpark called Koalas.