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

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.

主要特點

• 使用易於遵循的食譜探索 Elasticsearch 8.x 的功能


• 擴展 Elasticsearch 的功能，並學習如何在 Elastic Cloud 上部署


• 部署和管理簡單的 Elasticsearch 节點以及複雜的集群拓撲

書籍描述

Elasticsearch 是基於 Lucene 的分佈式搜索引擎，是 Elastic Stack 的核心，允許您對 PB 級數據進行索引和搜索。通過這本更新的第五版，您將涵蓋與 Elasticsearch 8.x 相關的全面食譜，並了解如何創建和運行複雜的查詢和分析。

這些食譜將引導您進行索引映射、聚合、查詢和使用 Elasticsearch 的腳本。您將專注於執行常見和不常見任務的多種解決方案和快速技巧，例如部署 Elasticsearch 节點、使用摄取模塊、使用 X-Pack 和創建不同的可視化。隨著您的進一步學習，您將學習如何管理各種集群、恢復數據，並安裝 Kibana 監控集群並使用各種插件擴展它。此外，您還將了解如何將 Java、Scala、Python 和大數據應用（如 Apache Spark 和 Pig）與 Elasticsearch 集成，並創建由增強功能和自定義插件驅動的高效數據應用。

通過閱讀本 Elasticsearch 食譜，您將深入了解實施 Elasticsearch 架構的知識，並能夠使用 Elasticsearch 高效且有效地管理、搜索和存儲數據。

您將學到什麼

• 熟悉 X-Pack 的功能


• 通過執行分析聚合來優化搜索結果


• 掌握使用文本和數字查詢以及關係和地理查詢


• 安裝 Kibana 監控集群並為插件擴展它


• 通過管理索引和文檔來構建複雜的查詢


• 監控集群和節點的性能


• 設計高級映射以完全控制索引步驟


• 將 Elasticsearch 集成到 Java、Scala、Python 和大數據應用中

本書適合對象

如果您是軟件工程師、大數據基礎架構工程師或 Elasticsearch 開發人員，您會發現這本 Elasticsearch 書籍很有用。本書還將幫助在電子商務和快速消費品行業中使用 Elastic 進行指標評估和搜索分析以獲得更深入洞察並做出更好的業務決策的數據專業人士。有 Elasticsearch 的先前經驗將幫助您充分利用本書的內容。

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.

Alberto Paro是一位工程師、經理和軟體開發人員。他目前在義大利的Accenture Cloud First資料和人工智慧團隊擔任技術架構交付副總監。他喜歡研究新興的解決方案和應用，主要涉及雲端和大數據處理、NoSQL、自然語言處理（NLP）、軟體開發和機器學習。2000年，他從米蘭理工大學獲得計算機科學工程學位。之後，他與許多公司合作，主要使用Scala/Java和Python開發知識管理解決方案和先進的數據挖掘產品，使用最先進的大數據軟體。他花了很多時間教授如何有效使用大數據解決方案、NoSQL數據存儲和相關技術。

1. Getting Started
2. Managing Mapping
3. Basic Operations
4. Exploring Search Capabilities
5. Text and Numeric Queries
6. Relationships and Geo Queries
7. Aggregations
8. Scripting in Elasticsearch
9. Managing Clusters
10. Backups and Restoring Data
11. User Interfaces
12. Using the Ingest Module
13. Java Integration
14. Scala Integration
15. Python Integration
16. Plugin Development
17. Big Data Integration
18. X-Pack

- 入門指南
- 管理映射
- 基本操作
- 探索搜索功能
- 文本和數值查詢
- 關聯和地理查詢
- 聚合
- Elasticsearch 中的腳本
- 管理集群
- 備份和還原數據
- 使用者介面
- 使用 Ingest 模組
- Java 整合
- Scala 整合
- Python 整合
- 插件開發
- 大數據整合
- X-Pack