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Elasticsearch 7.0 Cookbook. Over 100 recipes for fast, scalable, and reliable search for your enterprise - Fourth Edition Alberto Paro

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Elasticsearch 7.0 Cookbook. Over 100 recipes for fast, scalable, and reliable search for your enterprise - Fourth Edition Alberto Paro - okladka książki

Elasticsearch 7.0 Cookbook. Over 100 recipes for fast, scalable, and reliable search for your enterprise - Fourth Edition Alberto Paro - okladka książki

Autor:
Alberto Paro
Ocena:
Bądź pierwszym, który oceni tę książkę
Stron:
724
Dostępne formaty:
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     Mobi

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Elasticsearch is a Lucene-based distributed search server that allows users to index and search unstructured content with petabytes of data. With this book, you'll be guided through comprehensive recipes on what's new in Elasticsearch 7, and see how to create and run complex queries and analytics.

Packed with recipes on performing index mapping, aggregation, and scripting using Elasticsearch, this fourth edition of Elasticsearch Cookbook will get you acquainted with numerous solutions and quick techniques for performing both every day and uncommon tasks such as deploying Elasticsearch nodes, integrating other tools to Elasticsearch, and creating different visualizations. You will install Kibana to monitor a cluster and also extend it using a variety of plugins. Finally, you will integrate your Java, Scala, Python, and big data applications such as Apache Spark and Pig with Elasticsearch, and create efficient data applications powered by enhanced functionalities and custom plugins.

By the end of this book, you will have gained in-depth knowledge of implementing Elasticsearch architecture, and you'll be able to manage, search, and store data efficiently and effectively using 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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