Learning PySpark
by Tomasz Drabas(Author), Denny Lee(Author)
Publisher finelybook 出版社: Packt Publishing (February 27, 2017)
Language 语言: English
Print Length 页数: 274 pages
ISBN-10: 1786463709
ISBN-13: 9781786463708
Book Description
By finelybook
Build data-intensive applications locally and deploy at scale using the combined capabilities of Python and Spark 2.0
Key Features
Get up to speed with Spark 2.0 architecture and techniques for using Spark with Python
Learn how you can efficiently use Python to process data and build machine learning models in Apache Spark 2.0
Develop and deploy efficient, scalable real-time Spark solutions
Book Description
By finelybook
Apache Spark is an open source framework for efficient cluster computing with a strong interface for data parallelism and fault tolerance. This book will demonstrate how you can leverage the power of Python and put it to use in the Spark ecosystem.
You will start by understanding Spark 2.0 architecture and learning how to set up a Python environment for Spark. You will then get familiar with the modules available in PySpark such as MLib. The book will also guide you on how to abstract data with RDDs and DataFrames. In later chapters, you’ll get up to speed with the streaming capabilities of PySpark. Toward the end, you will gain insights into the machine learning capabilities of PySpark using ML and MLlib, graph processing using GraphFrames, and polyglot persistence using Blaze. Finally, you will learn how to deploy your applications to the cloud using the spark-submit command.
By the end of this book, you will have a strong understanding of the Spark Python API and how it can be used to build data-intensive applications.
What you will learn
Learn how to solve graph and deep learning problems using GraphFrames and TensorFrames respectively
Build and interact with Spark DataFrames using Spark SQL
Read, transform, and understand data and use it to train machine learning models
Develop machine learning models with MLlib
Learn to submit your applications programmatically using spark-submit
Deploy locally built applications to a cluster
Who this book is for
If you are a Python developer who wants to learn about the Apache Spark 2.0 ecosystem, this book is for you. A strong understanding of Python is expected to get the most out of this book. Familiarity with Spark will be useful, but is not mandatory.
Table of Contents
Understanding Spark
Resilient Distributed Datasets
DataFrames
Prepare Data for Modeling
Introducing MLlib
Introducing the ML Package
GraphFrames
TensorFrames
Polyglot Persistence with Blaze
Structured Streaming
Packaging Spark Applications
