文件名称：Spark.for.Python.Developers.1784399
文件大小：4.42MB
文件格式：PDF
更新时间：2019-02-04 03:17:13
Python Developers Spark
Key Features Set up real-time streaming and batch data intensive infrastructure using Spark and Python Deliver insightful visualizations in a web app using Spark (PySpark) Inject live data using Spark Streaming with real-time events Book Description Looking for a cluster computing system that provides high-level APIs? Apache Spark is your answer―an open source, fast, and general purpose cluster computing system. Spark's multi-stage memory primitives provide performance up to 100 times faster than Hadoop, and it is also well-suited for machine learning algorithms. Are you a Python developer inclined to work with Spark engine? If so, this book will be your companion as you create data-intensive app using Spark as a processing engine, Python visualization libraries, and web frameworks such as Flask. To begin with, you will learn the most effective way to install the Python development environment powered by Spark, Blaze, and Bookeh. You will then find out how to connect with data stores such as MySQL, MongoDB, Cassandra, and Hadoop. You'll expand your skills throughout, getting familiarized with the various data sources (Github, Twitter, Meetup, and Blogs), their data structures, and solutions to effectively tackle complexities. You'll explore datasets using iPython Notebook and will discover how to optimize the data models and pipeline. Finally, you'll get to know how to create training datasets and train the machine learning models. By the end of the book, you will have created a real-time and insightful trend tracker data-intensive app with Spark. Table of Contents Chapter 1: Setting Up a Spark Virtual Environment Chapter 2: Building Batch and Streaming Apps with Spark Chapter 3: Juggling Data with Spark Chapter 4: Learning from Data Using Spark Chapter 5: Streaming Live Data with Spark Chapter 6: Visualizing Insights and Trends