{Download Ebook} Ä Learning PySpark - Second Edition: Build faster data processing applications with Spark 2.3 ⚢ eBook or Kindle ePUB free

{Download Ebook} Ö Learning PySpark - Second Edition: Build faster data processing applications with Spark 2.3 ⛈ Build and deploy data intensive applications at scale using the combined capability of Python and Spark Key Features Build ETL pipelines with PySpark and Spark MLlib Apply Spark Streaming and Spark SQL with Python Perform distributed machine learning and work with Gradient Boosted Trees and Random Forests Book Description Apache Spark is an open source analytics engine for big data processing application, with built in modules for streaming, SQL, machine learning, and graph processing This second edition of Learning PySpark teaches you how to use the PySpark API to good effect and handle big data processing and live streaming applicationsTo start with, you ll discover how to use Apache Spark capabilities without learning Scala or Java, and execute simple batch and real time stream processing tasks The book focuses on performing machine learning tasks using the PySpark API You ll explore the latest features of PySpark , followed by understanding the challenges faced in building real time data processing applicationsThe book also teaches you how to leverage the benefits of Spark DataFrames and address your day to day big data problems You ll explore practical coverage, along with other Python libraries such as NumPy, Pandas, and Matplotlib, applied in streaming applicationsBy the end of this book, you will have established a firm understanding of the Spark Python API and how it can be used to build data intensive applications What you will learn Get to grips with Apache Spark and the Sparkarchitecture Build and interact with Spark DataFrames using Spark SQL Solve graph and deep learning problems using GraphFrames and TensorFrames respectively Read, transform, and understand data, and use it to train machine learning models Build machine learning models with MLlib and ML Submit your applications using the spark submit command Deploy locally built applications to a cluster Run Spark on AWS, Azure, Google Cloud Platform Who This Book Is For Learning PySpark is for big data professionals and data scientists who want to accelerate their data tasks and deliver real time data analytics This book is also a good starting point for Python programmers who want to enter the data analytics field and get up and running with Apache Spark and its Python interface