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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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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

Elasticsearch and relational database

We did cover Elasticsearch terminologies in detail in the section. However, Elasticsearch and its terminologies are not that different from a database, which is known common to many in the industry now as well. So let's see a comparison, so that whenever these terminologies are used in Elasticsearch, you could relate these to more RDBMS terminologies:

Elasticsearch Terminology RDBMS Terminology
Node DB Instance
Cluster DB Cluster
Index Database
Type Table
Mapping Schema
Shard Physical Partition
Route Logical Partition
Document Row
Field Column
Elasticsearch DSL (Query DSL) SQL
Table 02: Elasticsearch and RDBMS terminologies
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