Spark: Big Data Cluster Computing in Production

Book Description

Production-targeted Spark guidance with real-world use cases

Spark: Big Data Cluster Computing in Production goes beyond general Spark overviews to provide targeted guidance toward using lightning-fast big-data clustering in production. Written by an expert team well-known in the big data community, this book walks you through the challenges in moving from proof-of-concept or demo Spark applications to live Spark in production. Real use cases provide deep insight into common problems, limitations, challenges, and opportunities, while expert tips and tricks help you get the most out of Spark performance. Coverage includes Spark , Tachyon, Kerberos, ML Lib, YARN, and Mesos, with clear, actionable guidance on resource scheduling, db connectors, streaming, , and much more.

Spark has become the tool of choice for many Big Data problems, with more active contributors than any other Software project. General introductory books abound, but this book is the first to provide deep insight and real-world advice on using Spark in production. Specific guidance, expert tips, and invaluable foresight make this guide an incredibly useful resource for real production settings.

  • Review Spark requirements and estimate cluster size
  • Gain insight from real-world production use cases
  • Tighten security, schedule resources, and fine-tune performance
  • Overcome common problems encountered using Spark in production

Spark works with other big data tools including MapReduce and , and uses languages you already know like Java, Scala, Python, and R. Lightning speed makes Spark too good to pass up, but understanding limitations and challenges in advance goes a long way toward easing actual production implementation. Spark: Big Data Cluster Computing in Production tells you everything you need to know, with real-world production insight and expert guidance, tips, and tricks.

Table of Contents

Chapter 1 Finishing Your Spark Job
Chapter 2 Cluster
Chapter 3 Performance Tuning
Chapter 4 Security
Chapter 5 Fault Tolerance or Job Execution
Chapter 6 Beyond Spark

Book Details

  • Title: Spark: Big Data Cluster Computing in Production
  • Author: , , ,
  • Length: 216 pages
  • Edition: 1
  • Language: English
  • Publisher:
  • Publication Date: 2016-03-21
  • ISBN-10: 1119254019
  • ISBN-13: 9781119254010
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