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Data Lake for Enterprises

You're reading from   Data Lake for Enterprises Lambda Architecture for building enterprise data systems

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Product type Paperback
Published in May 2017
Publisher Packt
ISBN-13 9781787281349
Length 596 pages
Edition 1st Edition
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Authors (3):
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Pankaj Misra Pankaj Misra
Author Profile Icon Pankaj Misra
Pankaj Misra
Tomcy John Tomcy John
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Tomcy John
Vivek Mishra Vivek Mishra
Author Profile Icon Vivek Mishra
Vivek Mishra
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Toc

Table of Contents (13) Chapters Close

Preface 1. Introduction to Data FREE CHAPTER 2. Comprehensive Concepts of a Data Lake 3. Lambda Architecture as a Pattern for Data Lake 4. Applied Lambda for Data Lake 5. Data Acquisition of Batch Data using Apache Sqoop 6. Data Acquisition of Stream Data using Apache Flume 7. Messaging Layer using Apache Kafka 8. Data Processing using Apache Flink 9. Data Store Using Apache Hadoop 10. Indexed Data Store using Elasticsearch 11. Data Lake Components Working Together 12. Data Lake Use Case Suggestions

Kafka working example


We have briefly discussed a basic setup of Kafka as part of Flume examples. The basic setup of Kafka as listed there remains the same, hence the installation steps will remain the same, however we will also look additionally at usage examples of Kafka as a message broker.

The most natural programming language for Kafka is currently Scala or Java. Hence, to keep things simple, we will be using Java as our choice of language for examples.

Installation

  1. Download the Kafka binaries from the following link, using the command:
wget http://redrockdigimark.com/apachemirror/kafka/0.10.1.1/kafka_2.11-0.10.1.1.tgz
  1. Change the  directory to a user directory, where we will want to extract the contents of the Kafka tarball using the following command. Let us refer the extracted KAFKA directory as ${KAFKA_HOME}:
tar -xzvf ${DOWNLOAD_DIRECTORY}/kafka_2.11-0.10.1.1.tgz
  1. Set KAFKA_HOME as environment variable using the following commands and add the same into ~/.bashrc:
export KAFKA_HOME=<PATH...
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