Build data-intensive applications locally and deploy at scale using thecombined powers of Python and Spark 2.0 About This Book - Learn why and howyou can efficiently use Python to process data and build machine learningmodels in Apache Spark 2.0 - Develop and deploy efficient, scalable real-timeSpark solutions - Take your understanding of using Spark with Python to thenext level with this jump start guide Who This Book Is For If you are a Pythondeveloper who wants to learn about the Apache Spark 2.0 ecosystem, this bookis for you. A firm understanding of Python is expected to get the best out ofthe book. Familiarity with Spark would be useful, but is not mandatory. WhatYou Will Learn - Learn about Apache Spark and the Spark 2.0 architecture -Build and interact with Spark DataFrames using Spark SQL - Learn how to solvegraph and deep learning problems using GraphFrames and TensorFramesrespectively - Read, transform, and understand data and use it to trainmachine learning models - Build machine learning models with MLlib and ML -Learn how to submit your applications programmatically using spark-submit -Deploy locally built applications to a cluster In Detail Apache Spark is anopen source framework for efficient cluster computing with a strong interfacefor data parallelism and fault tolerance. This book will show you how toleverage the power of Python and put it to use in the Spark ecosystem. Youwill start by getting a firm understanding of the Spark 2.0 architecture andhow to set up a Python environment for Spark. You will get familiar with themodules available in PySpark. You will learn how to abstract data with RDDsand DataFrames and understand the streaming capabilities of PySpark. Also, youwill get a thorough overview of machine learning capabilities of PySpark usingML and MLlib, graph processing using GraphFrames, and polyglot persistenceusing Blaze. Finally, you will learn how to deploy your applications to thecloud using the spark-submit command. By the end of this book, you will haveestablished a firm understanding of the Spark Python API and how it can beused to build data-intensive applications. Style and approach This book takesa very comprehensive, step-by-step approach so you understand how the Sparkecosystem can be used with Python to develop efficient, scalable solutions.Every chapter is standalone and written in a very easy-to-understand manner,with a focus on both the hows and the whys of each concept.words : 54396