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You're reading from  Elasticsearch 7.0 Cookbook. - Fourth Edition

Product typeBook
Published inApr 2019
Reading LevelBeginner
PublisherPackt
ISBN-139781789956504
Edition4th Edition
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Author (1)
Alberto Paro
Alberto Paro
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Alberto Paro

Alberto Paro is an engineer, manager, and software developer. He currently works as technology architecture delivery associate director of the Accenture Cloud First data and AI team in Italy. He loves to study emerging solutions and applications, mainly related to cloud and big data processing, NoSQL, Natural language processing (NLP), software development, and machine learning. In 2000, he graduated in computer science engineering from Politecnico di Milano. Then, he worked with many companies, mainly using Scala/Java and Python on knowledge management solutions and advanced data mining products, using state-of-the-art big data software. A lot of his time is spent teaching how to effectively use big data solutions, NoSQL data stores, and related technologies.
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Mapping base types

Using explicit mapping makes it possible to be faster in starting to ingest the data using a schema-less approach without being concerned about field types. Thus, to achieve better results and performance in indexing, it's required to manually define a mapping.

Fine-tuning mapping brings some advantages, such as the following:

  • Reducing the index size on the disk (disabling functionalities for custom fields)
  • Indexing only interesting fields (general speed up)
  • Precooking data for fast search or real-time analytics (such as facets)
  • Correctly defining whether a field must be analyzed in multiple tokens or considered as a single token

Elasticsearch allows you to use base fields with a wide range of configurations.

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Elasticsearch 7.0 Cookbook. - Fourth Edition
Published in: Apr 2019Publisher: PacktISBN-13: 9781789956504

Author (1)

author image
Alberto Paro

Alberto Paro is an engineer, manager, and software developer. He currently works as technology architecture delivery associate director of the Accenture Cloud First data and AI team in Italy. He loves to study emerging solutions and applications, mainly related to cloud and big data processing, NoSQL, Natural language processing (NLP), software development, and machine learning. In 2000, he graduated in computer science engineering from Politecnico di Milano. Then, he worked with many companies, mainly using Scala/Java and Python on knowledge management solutions and advanced data mining products, using state-of-the-art big data software. A lot of his time is spent teaching how to effectively use big data solutions, NoSQL data stores, and related technologies.
Read more about Alberto Paro