Spark Cookbook: Over 60 recipes on Spark, covering Spark Core, Spark SQL, Spark Streaming, MLlib, and GraphX libraries - Couverture souple

Rishi Yadav

 
9781783987061: Spark Cookbook: Over 60 recipes on Spark, covering Spark Core, Spark SQL, Spark Streaming, MLlib, and GraphX libraries

Synopsis

If you are a data engineer, application developer, or data scientist who would like to leverage the power of Apache Spark to get better insights from big data, this is the book for you.

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Présentation de l'éditeur

Over 60 recipes on Spark, covering Spark Core, Spark SQL, Spark Streaming, MLlib, and GraphX libraries

About This Book

  • Become an expert at graph processing using GraphX
  • Use Apache Spark as your single big data compute platform and master its libraries
  • Learn with recipes that can be run on a single machine as well as on a production cluster of thousands of machines

Who This Book Is For

If you are a data engineer, an application developer, or a data scientist who would like to leverage the power of Apache Spark to get better insights from big data, then this is the book for you.

What You Will Learn

  • Install and configure Apache Spark with various cluster managers
  • Set up development environments
  • Perform interactive queries using Spark SQL
  • Get to grips with real-time streaming analytics using Spark Streaming
  • Master supervised learning and unsupervised learning using MLlib
  • Build a recommendation engine using MLlib
  • Develop a set of common applications or project types, and solutions that solve complex big data problems
  • Use Apache Spark as your single big data compute platform and master its libraries

In Detail

By introducing in-memory persistent storage, Apache Spark eliminates the need to store intermediate data in filesystems, thereby increasing processing speed by up to 100 times.

This book will focus on how to analyze large and complex sets of data. Starting with installing and configuring Apache Spark with various cluster managers, you will cover setting up development environments. You will then cover various recipes to perform interactive queries using Spark SQL and real-time streaming with various sources such as Twitter Stream and Apache Kafka. You will then focus on machine learning, including supervised learning, unsupervised learning, and recommendation engine algorithms. After mastering graph processing using GraphX, you will cover various recipes for cluster optimization and troubleshooting.

Biographie de l'auteur

Rishi Yadav

Rishi Yadav has 17 years of experience in designing and developing enterprise applications. He is an open source software expert and advises American companies on big data trends. Rishi was honored as one of Silicon Valley's 40 under 40 in 2014. He finished his bachelor's degree at the prestigious Indian Institute of Technology (IIT) Delhi in 1998. About 10 years ago, Rishi started InfoObjects, a company that helps data-driven businesses gain new insights into data. InfoObjects combines the power of open source and big data to solve business challenges for its clients and has a special focus on Apache Spark. The company has been on the Inc. 5000 list of the fastest growing companies for 4 years in a row. InfoObjects has also been awarded with the #1 best place to work in the Bay Area in 2014 and 2015. Rishi is an open source contributor and active blogger.

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