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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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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

Introduction

Streaming is the process of dividing continuously flowing input data into discreet units so that it can be processed easily. Familiar examples in real life are streaming video and audio content (though a user can download the full movie before he/she can watch it, a faster solution is to stream data in small chunks that start playing for the user while the rest of the data is being downloaded in the background).

Real-world examples of streaming, besides multimedia, are the processing of market feeds, weather data, electronic stock trading data, and so on. All of these applications produce large volumes of data at very fast rates and require special handling of the data so that insights can be derived from data in real time.

Streaming has a few basic concepts, which are better to understand before we focus on Spark Streaming. The rate at which a streaming application receives data is called data rate and is expressed in the form of kilobytes per second (kbps) or megabytes per...

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