Essential PySpark for Scalable Data Analytics
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491_9781800568877
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Get started with distributed computing using PySpark, a single unified framework to solve end-to-end data analytics at scaleKey Features:Discover how to convert huge amounts of raw data into meaningful and actionable insightsUse Sparks unified analytics engine for end-to-end analytics, from data preparation to predictive analyticsPerform data ingestion, cleansing, and integration for ML, data analytics, and data visualizationBook Description:Apache Spark is a unified data analytics engine designed to process huge volumes of data quickly and efficiently. PySpark is Apache Sparks Python language API, which offers Python developers an easy-to-use scalable data analytics framework.Essential PySpark for Scalable Data Analytics starts by exploring the distributed computing paradigm and provides a high-level overview of Apache Spark. Youll 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 enable you to gain insights much faster. Youll then discover methods for building cloud-based data lakes, and explore Delta Lake, which brings reliability and performance 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, youll perform scalable data science and machine learning tasks using PySpark, such as data preparation, feature engineering, and model training and productionization. Finally, youll learn ways to scale out standard Python ML libraries along with a new pandas API on top of PySpark called Koalas.By the end of this PySpark book, youll be able to harness the power of PySpark to solve business problems.What You Will Learn:Understand the role of distributed computing in the world of big dataGain an appreciation for Apache Spark as the de facto go-to for big data processingScale ou
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