Book Image

Advanced Elasticsearch 7.0

By : Wai Tak Wong
Book Image

Advanced Elasticsearch 7.0

By: Wai Tak Wong

Overview of this book

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.
Table of Contents (25 chapters)
Free Chapter
1
Section 1: Fundamentals and Core APIs
8
Section 2: Data Modeling, Aggregations Framework, Pipeline, and Data Analytics
13
Section 3: Programming with the Elasticsearch Client
16
Section 4: Elastic Stack
20
Section 5: Advanced Features

Summary

Cheers! We have completed a basic study of Java programming with Elasticsearch. We should now be able to understand and access the different Elasticsearch clients in Java. We also learned how to incorporate Elasticsearch into Java applications, especially Spring Boot applications. We also outlined the basic programming concept of Spring Data Elasticsearch. We pointed out the issue that Spring Data needs to revise significantly, due to the fact that the transport client is deprecated in version 7.0 and will be removed fully in version 8.0.

In the following Chapter 12, Elasticsearch from Python Programming, we will introduce Python programming with Elasticsearch. The elasticsearch-py package is the official low-level client for Elasticsearch. The goal of the Python package is to provide commonality to all Elasticsearch-related codes in Python. We will also review Elasticsearch...