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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

Nodes in Elasticsearch

As detailed earlier, a node in Elasticsearch is one of the servers forming the cluster. A node in a cluster can be configured to work as different node types as follows:

  • Master node
  • Data node
  • Client node

Elasticsearch - master node

Any node in a cluster is eligible to become the master node if the node.master property is set to true in the elasticsearch.yml file. Once the master node is elected automatically by the cluster, this node is entrusted with some key responsibilities, as follows:

  • Allocate of shards across various nodes within the cluster.
  • Create and delete indexes.
  • Broadcast the cluster state to all the nodes in the cluster and in turn receives confirmations from each of those nodes back.
  • Take necessary actions when a node joins...
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