Advanced Elasticsearch 7.0 : A practical guide to designing, indexing, and querying advanced distributed search engines

個数:

Advanced Elasticsearch 7.0 : A practical guide to designing, indexing, and querying advanced distributed search engines

  • オンデマンド(OD/POD)版です。キャンセルは承れません。
  • 【入荷遅延について】
    世界情勢の影響により、海外からお取り寄せとなる洋書・洋古書の入荷が、表示している標準的な納期よりも遅延する場合がございます。
    おそれいりますが、あらかじめご了承くださいますようお願い申し上げます。
  • ◆画像の表紙や帯等は実物とは異なる場合があります。
  • ◆ウェブストアでの洋書販売価格は、弊社店舗等での販売価格とは異なります。
    また、洋書販売価格は、ご注文確定時点での日本円価格となります。
    ご注文確定後に、同じ洋書の販売価格が変動しても、それは反映されません。
  • 製本 Paperback:紙装版/ペーパーバック版/ページ数 560 p.
  • 言語 ENG
  • 商品コード 9781789957754
  • DDC分類 025.04252

Full Description

Master the intricacies of Elasticsearch 7.0 and use it to create flexible and scalable search solutions

Key Features

Master the latest distributed search and analytics capabilities of Elasticsearch 7.0
Perform searching, indexing, and aggregation of your data at scale
Discover tips and techniques for speeding up your search query performance

Book DescriptionBuilding enterprise-grade distributed applications and executing systematic search operations call for a strong understanding of Elasticsearch and expertise in using its core APIs and latest features. This book will help you master the advanced functionalities of Elasticsearch and understand how you can develop a sophisticated, real-time search engine confidently. In addition to this, you'll also learn to run machine learning jobs in Elasticsearch to speed up routine tasks.

You'll get started by learning to use Elasticsearch features on Hadoop and Spark and make search results faster, thereby improving the speed of query results and enhancing the customer experience. You'll then get up to speed with performing analytics by building a metrics pipeline, defining queries, and using Kibana for intuitive visualizations that help provide decision-makers with better insights. The book will later guide you through using Logstash with examples to collect, parse, and enrich logs before indexing them in Elasticsearch.

By the end of this book, you will have comprehensive knowledge of advanced topics such as Apache Spark support, machine learning using Elasticsearch and scikit-learn, and real-time analytics, along with the expertise you need to increase business productivity, perform analytics, and get the very best out of Elasticsearch.

What you will learn

Pre-process documents before indexing in ingest pipelines
Learn how to model your data in the real world
Get to grips with using Elasticsearch for exploratory data analysis
Understand how to build analytics and RESTful services
Use Kibana, Logstash, and Beats for dashboard applications
Get up to speed with Spark and Elasticsearch for real-time analytics
Explore the basics of Spring Data Elasticsearch, and understand how to index, search, and query in a Spring application

Who this book is forThis book is for Elasticsearch developers and data engineers who want to take their basic knowledge of Elasticsearch to the next level and use it to build enterprise-grade distributed search applications. Prior experience of working with Elasticsearch will be useful to get the most out of this book.

Contents

Table of Contents

Overview of Elasticsearch 7
Index APIs
Document APIs
Mapping APIs
Anatomy of an Analyzer
Search APIs
Modeling Your Data in the Real World
Aggregations Frameworks
Preprocessing Documents in Ingest Pipelines
Using ElasticSearch for Exploratory Data Analysis
Elasticsearch from Java Programming
Elasticsearch from Python Programming
Using Kibana, Logstash and Beats
Working with Elasticsearch SQL
Working with Elasticsearch Analysis Plugins
Machine Learning with Elasticsearch
Spark and Elasticsearch for Real-Time Analytics
Building Analytics RESTful Services

最近チェックした商品