Elasticsearch 8.x Cookbook - Fifth Edition: Over 180 recipes to perform fast, scalable, and reliable searches for your enterprise

Elasticsearch 8.x Cookbook - Fifth Edition: Over 180 recipes to perform fast, scalable, and reliable searches for your enterprise

作者: Paro Alberto
出版社: Packt Publishing
出版在: 2022-05-27
ISBN-13: 9781801079815
ISBN-10: 1801079811
裝訂格式: Quality Paper - also called trade paper
總頁數: 750 頁





內容描述


Key Features

Explore the capabilities of Elasticsearch 8.x with easy-to-follow recipes
Extend the Elasticsearch functionalities and learn how to deploy on Elastic Cloud
Deploy and manage simple Elasticsearch nodes as well as complex cluster topologies

Book Description
Elasticsearch is a Lucene-based distributed search engine at the heart of the Elastic Stack that allows you to index and search unstructured content with petabytes of data. With this updated fifth edition, you'll cover comprehensive recipes relating to what's new in Elasticsearch 8.x and see how to create and run complex queries and analytics.
The recipes will guide you through performing index mapping, aggregation, working with queries, and scripting using Elasticsearch. You'll focus on numerous solutions and quick techniques for performing both common and uncommon tasks such as deploying Elasticsearch nodes, using the ingest module, working with X-Pack, and creating different visualizations. As you advance, you'll learn how to manage various clusters, restore data, and install Kibana to monitor a cluster and extend it using a variety of plugins. Furthermore, you'll understand how to 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 Elasticsearch cookbook, you'll have gained in-depth knowledge of implementing the Elasticsearch architecture and be able to manage, search, and store data efficiently and effectively using Elasticsearch.
What you will learn

Become well-versed with the capabilities of X-Pack
Optimize search results by executing analytics aggregations
Get to grips with using text and numeric queries as well as relationship and geo queries
Install Kibana to monitor clusters and extend it for plugins
Build complex queries by managing indices and documents
Monitor the performance of your cluster and nodes
Design advanced mapping to take full control of index steps
Integrate Elasticsearch in Java, Scala, Python, and big data applications

Who this book is for
If you're a software engineer, big data infrastructure engineer, or Elasticsearch developer, you'll find this Elasticsearch book useful. The book will also help data professionals working in e-commerce and FMCG industries who use Elastic for metrics evaluation and search analytics to gain deeper insights and make better business decisions. Prior experience with Elasticsearch will help you get the most out of this book.


目錄大綱


Getting Started
Managing Mapping
Basic Operations
Exploring Search Capabilities
Text and Numeric Queries
Relationships and Geo Queries
Aggregations
Scripting in Elasticsearch
Managing Clusters
Backups and Restoring Data
User Interfaces
Using the Ingest Module
Java Integration
Scala Integration
Python Integration
Plugin Development
Big Data Integration
X-Pack


作者介紹


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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