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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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Using the search_after functionality

Elasticsearch standard pagination using from and size perform very poorly on large datasets because, for every query, you need to compute and discard all the results before the from value. Scrolling doesn't have this problem, but it consumes a lot due to memory search contexts, so it cannot be used for frequent user queries.

To bypass these problems, Elasticsearch 5.x and above provides the search_after functionality, which provides a fast skipping for scrolling results.

Getting ready

You need an up-and-running Elasticsearch installation, as we described in the Downloading and installing Elasticsearch recipe in Chapter 1, Getting Started.

To execute these commands, any HTTP client...

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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