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Modern Big Data Processing with Hadoop

You're reading from  Modern Big Data Processing with Hadoop

Product type Book
Published in Mar 2018
Publisher Packt
ISBN-13 9781787122765
Pages 394 pages
Edition 1st Edition
Languages
Concepts
Authors (3):
V Naresh Kumar V Naresh Kumar
Profile icon V Naresh Kumar
Manoj R Patil Manoj R Patil
Profile icon Manoj R Patil
Prashant Shindgikar Prashant Shindgikar
Profile icon Prashant Shindgikar
View More author details

Table of Contents (12) Chapters

Preface 1. Enterprise Data Architecture Principles 2. Hadoop Life Cycle Management 3. Hadoop Design Consideration 4. Data Movement Techniques 5. Data Modeling in Hadoop 6. Designing Real-Time Streaming Data Pipelines 7. Large-Scale Data Processing Frameworks 8. Building Enterprise Search Platform 9. Designing Data Visualization Solutions 10. Developing Applications Using the Cloud 11. Production Hadoop Cluster Deployment

Elasticsearch-supported data types

The following spreadsheet summarizes the available data types in Elasticsearch:

Common

Complex

Geo

Specialized

String

Array

Geo_Point

ip

Keyword

Object (single Json)

Geo_Shape

completion

Date

Nested (Json array)

token_count

Long

join

Short

percolator

Byte

murmur3

Double

Float

Boolean

Binary

Integer_range

Float_range

Long_range

Double_range

Date_range

Most of the data types need no explanation. But the following are a few explanations for specific data types:

  • Geo-Point: You can define latitude and longitude points here
  • Geo-Shape: This is for defining shapes
  • Completion: This data type is for defining auto completion of words.
  • Join: To define parent/child relationships
  • Percolator: This is for query-dsl
  • Murmur3: During...
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