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Mastering Hadoop 3

You're reading from  Mastering Hadoop 3

Product type Book
Published in Feb 2019
Publisher Packt
ISBN-13 9781788620444
Pages 544 pages
Edition 1st Edition
Languages
Authors (2):
Chanchal Singh Chanchal Singh
Profile icon Chanchal Singh
Manish Kumar Manish Kumar
Profile icon Manish Kumar
View More author details

Table of Contents (23) Chapters

Title Page
Dedication
About Packt
Foreword
Contributors
Preface
Journey to Hadoop 3 Deep Dive into the Hadoop Distributed File System YARN Resource Management in Hadoop Internals of MapReduce SQL on Hadoop Real-Time Processing Engines Widely Used Hadoop Ecosystem Components Designing Applications in Hadoop Real-Time Stream Processing in Hadoop Machine Learning in Hadoop Hadoop in the Cloud Hadoop Cluster Profiling Who Can Do What in Hadoop Network and Data Security Monitoring Hadoop Other Books You May Enjoy Index

Real-time processing case study


In this section, for the IP fraud detection case mentioned in the preceding section, we will use Apache Storm for the same log processing. Apache Storm is used for very sensitive applications in which even a 1 second delay could cause enormous losses. There are many enterprises that use Storm to detect fraud, develop recommendation engines, trigger suspicious activity, and so on. It uses Zookeeper for coordination purposes and maintains significant metadata information. Apache Storm is stateless. It is a distributed real-time processing framework that can handle one event at a time with the processing of millions of records per second per node. Streaming data can be limited or unlimited; Storm can reliably process it in both situations. The Maven app is as follows: 

<?xml version="1.0" encoding="UTF-8"?>
<project xmlns="http://maven.apache.org/POM/4.0.0"
         xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"
         xsi:schemaLocation="http...
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