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Spark Cookbook

You're reading from   Spark Cookbook With over 60 recipes on Spark, covering Spark Core, Spark SQL, Spark Streaming, MLlib, and GraphX libraries this is the perfect Spark book to always have by your side

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Product type Paperback
Published in Jul 2015
Publisher
ISBN-13 9781783987061
Length 226 pages
Edition 1st Edition
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Author (1):
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Rishi Yadav Rishi Yadav
Author Profile Icon Rishi Yadav
Rishi Yadav
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Toc

Table of Contents (14) Chapters Close

Preface 1. Getting Started with Apache Spark 2. Developing Applications with Spark FREE CHAPTER 3. External Data Sources 4. Spark SQL 5. Spark Streaming 6. Getting Started with Machine Learning Using MLlib 7. Supervised Learning with MLlib – Regression 8. Supervised Learning with MLlib – Classification 9. Unsupervised Learning with MLlib 10. Recommender Systems 11. Graph Processing Using GraphX 12. Optimizations and Performance Tuning Index

Understanding the future of optimization – project Tungsten


Project Tungsten, starting with Spark Version 1.4, is the initiative to bring Spark closer to bare metal. The goal of this project is to substantially improve the memory and CPU efficiency of the Spark applications and push the limits of underlying hardware.

In distributed systems, conventional wisdom has been to always optimize network I/O as that has been the most scarce and bottlenecked resource. This trend has changed in the last few years. Network bandwidth, in the last 5 years, has changed from 1 gigabit per second to 10 gigabit per second.

On similar lines, the disk bandwidth has increased from 50 MB/s to 500 MB/s and SSDs are being deployed more and more. CPU clock speed, on the other hand, was ~3 GHz 5 years back and is still the same. This has unseated the network and made CPU the new bottleneck in distributed processing.

Note

Another trend that has put more load on CPU performance is the new compressed data formats such as...

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