ElasticSearch Cookbook

· Packt Publishing Ltd
4.0
2 reviews
Ebook
422
Pages

About this ebook

Written in an engaging, easy-to-follow style, the recipes will help you to extend the capabilities of ElasticSearch to manage your data effectively. If you are a developer who implements ElasticSearch in your web applications, manage data, or have decided to start using ElasticSearch, this book is ideal for you. This book assumes that you’ve got working knowledge of JSON and Java

Ratings and reviews

4.0
2 reviews

About the author

Alberto Paro is an engineer, a project manager, and a software developer. He currently works as a CTO at The Net Planet Europe and as a Freelance Consultant of software engineering on Big Data and NoSQL solutions. He loves studying emerging solutions and applications mainly related to Big Data processing, NoSQL, Natural Language Processing, and neural networks. He started programming in Basic on a Sinclair Spectrum when he was eight years old and in his life he has gained a lot of experience using different operative systems, applications, and programming. In 2000, he completed Computer Science engineering from Politecnico di Milano with a thesis on designing multi-users and multidevices web applications. He worked as a professor helper at the university for about one year. Then, after coming in contact with The Net Planet company and loving their innovation ideas, he started working on knowledge management solutions and advanced data-mining products. In his spare time, when he is not playing with his children, he likes working on open source projects. When he was in high school, he started contributing to projects related to the Gnome environment (GTKMM). One of his preferred programming languages was Python and he wrote one of the first NoSQL backend for Django for MongoDB (django-mongodb-engine). In 2010, he started using ElasticSearch to provide search capabilities for some Django e-commerce sites and developed PyES (a pythonic client for ElasticSearch) and the initial part of ElasticSearch MongoDB River.

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