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Building Data Streaming Applications with Apache Kafka

You're reading from   Building Data Streaming Applications with Apache Kafka Design, develop and streamline applications using Apache Kafka, Storm, Heron and Spark

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Product type Paperback
Published in Aug 2017
Publisher Packt
ISBN-13 9781787283985
Length 278 pages
Edition 1st Edition
Tools
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Authors (2):
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Chanchal Singh Chanchal Singh
Author Profile Icon Chanchal Singh
Chanchal Singh
Manish Kumar Manish Kumar
Author Profile Icon Manish Kumar
Manish Kumar
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Table of Contents (14) Chapters Close

Preface 1. Introduction to Messaging Systems FREE CHAPTER 2. Introducing Kafka the Distributed Messaging Platform 3. Deep Dive into Kafka Producers 4. Deep Dive into Kafka Consumers 5. Building Spark Streaming Applications with Kafka 6. Building Storm Applications with Kafka 7. Using Kafka with Confluent Platform 8. Building ETL Pipelines Using Kafka 9. Building Streaming Applications Using Kafka Streams 10. Kafka Cluster Deployment 11. Using Kafka in Big Data Applications 12. Securing Kafka 13. Streaming Application Design Considerations

Producer 

You can use IntelliJ or Eclipse to build a producer application. This producer reads a log file taken from an Apache project which contains detailed records like:

64.242.88.10 - - [08/Mar/2004:07:54:30 -0800] "GET /twiki/bin/edit/Main/Unknown_local_recipient_reject_code?topicparent=Main.ConfigurationVariables HTTP/1.1" 401 12846

You can have just one record in the test file and the producer will produce records by generating random IPs and replace it with existing. So, we will have millions of distinct records with unique IP addresses.

Record columns are separated by space delimiters, which we change to commas in producer. The first column represents the IP address or the domain name which will be used to detect whether the request was from a fraud client. The following is the Java Kafka producer which remembers logs.

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