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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
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Vivek Mishra
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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

Other Kafka components


In addition to these components, there are some important components in a Kafka deployment without which the Kafka won't work as intended. These are a couple of the important components that could be used:

  • Zookeeper
  • MirrorMaker

Zookeeper

Zookeeper is one of the very important hidden component, needed (mandatory) for Kafka to function properly. It is entrusted to do the following jobs:

  • Taking care of bringing each broker into the cluster membership.
  • Electing the Kafka controller which does some very important functions within the cluster such as managing the state of partitions and their replicas.
  • Complete topic configurations like number of partitions, leader partitions election, partition replication location and so on.
  • Access control list maintenance and various quotas within each broker.

MirrorMaker

As the name suggests, it helps mirror data cross Kafka clusters. This component can be used to mirror an entire cluster from one data center to another, as shown in the next figure...

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