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Elasticsearch 5.x Cookbook. Distributed Search and Analytics - Third Edition Alberto Paro

(ebook) (audiobook) (audiobook) Książka w języku angielskim
Elasticsearch 5.x Cookbook. Distributed Search and Analytics - Third Edition Alberto Paro - okladka książki

Elasticsearch 5.x Cookbook. Distributed Search and Analytics - Third Edition Alberto Paro - okladka książki

Elasticsearch 5.x Cookbook. Distributed Search and Analytics - Third Edition Alberto Paro - audiobook MP3

Elasticsearch 5.x Cookbook. Distributed Search and Analytics - Third Edition Alberto Paro - audiobook CD

Autor:
Alberto Paro
Ocena:
Bądź pierwszym, który oceni tę książkę
Stron:
696
Dostępne formaty:
     PDF
     ePub
     Mobi
Elasticsearch is a Lucene-based distributed search server that allows users to index and search unstructured content with petabytes of data. This book is your one-stop guide to master the complete Elasticsearch ecosystem.
We’ll guide you through comprehensive recipes on what’s new in Elasticsearch 5.x, showing you how to create complex queries and analytics, and perform index mapping, aggregation, and scripting. Further on, you will explore the modules of Cluster and Node monitoring and see ways to back up and restore a snapshot of an index.
You will understand how to install Kibana to monitor a cluster and also to extend Kibana for plugins. Finally, you will also see how you can integrate your Java, Scala, Python, and Big Data applications such as Apache Spark and Pig with Elasticsearch, and add enhanced functionalities with custom plugins.
By the end of this book, you will have an in-depth knowledge of the implementation of the Elasticsearch architecture and will be able to manage data efficiently and effectively with Elasticsearch.

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O autorze książki

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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