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

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 Description

Building 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 for

This 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. 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

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