Home | Amazing | Today | Tags | Publishers | Years | Account | Search 
Spark for Python Developers

Buy
Spark for Python Developers, 9781784399696 (1784399698), Packt Publishing, 2015

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.

What you will learn

  • Create a Python development environment powered by Spark (PySpark), Blaze, and Bookeh
  • Build a real-time trend tracker data intensive app
  • Visualize the trends and insights gained from data using Bookeh
  • Generate insights from data using machine learning through Spark MLLIB
  • Juggle with data using Blaze
  • Create training data sets and train the Machine Learning models
  • Test the machine learning models on test datasets
  • Deploy the machine learning algorithms and models and scale it for real-time events

About the Author

Amit Nandi studied physics at the Free University of Brussels in Belgium, where he did his research on computer generated holograms. Computer generated holograms are the key components of an optical computer, which is powered by photons running at the speed of light. He then worked with the university Cray supercomputer, sending batch jobs of programs written in Fortran. This gave him a taste for computing, which kept growing. He has worked extensively on large business reengineering initiatives, using SAP as the main enabler. He focused for the last 15 years on start-ups in the data space, pioneering new areas of the information technology landscape. He is currently focusing on large-scale data-intensive applications as an enterprise architect, data engineer, and software developer. He understands and speaks seven human languages. Although Python is his computer language of choice, he aims to be able to write fluently in seven computer languages too.

Table of Contents

  1. Setting Up a Spark Virtual Environment
  2. Building Batch and Streaming Apps with Spark
  3. Juggling Data with Spark
  4. Learning from Data Using Spark
  5. Streaming Live Data with Spark
  6. Visualizing Insights and Trends
(HTML tags aren't allowed.)

Introduction to Probability and Statistics Using R
Introduction to Probability and Statistics Using R
This is a textbook for an undergraduate course in probability and statistics. The approximate prerequisites are two or three... More > semesters of calculus and some linear algebra. Students attending the class include mathematics, engineering, and computer science majors....
Ethernet Networks: Design, Implementation, Operation,& Management
Ethernet Networks: Design, Implementation, Operation,& Management
Ethernet Networks, Fourth Edition, provides everything you need to know to plan, implement, manage and upgrade Ethernet networks.
  • Improve your skills in employing Ethernet hubs, switches, and routers.

  • Learn how to set up and operate a wireless Local Area Network (LAN).

    ...
Teach Yourself Algebra for Electronic Circuits
Teach Yourself Algebra for Electronic Circuits

The way to go for problem-solving skills and applications, TEACH YOURSELF ALGEBRA FOR ELECTRIC CIRCUITS is the self-tutoring guide that's just right for electronics.

* Math that goes beyond elementary algebra, without the burden of heavy-duty calculus you don't need
* All the tools for solving any problem in a single place--no
...


Mastering Nginx
Mastering Nginx

Written for experienced systems administrators and engineers, this book teaches you from scratch how to configure Nginx for any situation. Step-by-step instructions and real-world code snippets clarify even the most complex areas.

Overview

  • An in-depth configuration guide to help you understand how to best...
Practical Data Science Cookbook - Second Edition
Practical Data Science Cookbook - Second Edition

Over 85 recipes to help you complete real-world data science projects in R and Python

About This Book

  • Tackle every step in the data science pipeline and use it to acquire, clean, analyze, and visualize your data
  • Get beyond the theory and implement real-world projects in data science using...
Practical Statistics for Data Scientists: 50 Essential Concepts
Practical Statistics for Data Scientists: 50 Essential Concepts

Statistical methods are a key part of of data science, yet very few data scientists have any formal statistics training. Courses and books on basic statistics rarely cover the topic from a data science perspective. This practical guide explains how to apply various statistical methods to data science, tells you how to avoid their...

©2019 LearnIT (support@pdfchm.net) - Privacy Policy