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

Working with Elasticsearch SQL

In the last chapter, we touched upon the major components of the Elastic Stack. We went through the entire range of data processes, starting with Filebeat, Logstash, and Elasticsearch, before finally viewing it in Kibana. Although we only gave a simple example, you can still see that once the details can be handled, the feasibility and extensibility are great. That is why the Beats are so popular and extend to different areas to collect data. In this chapter, we will introduce Elasticsearch SQL. With Elasticsearch SQL, you can access full-text search and easily extend the functionality with a familiar query syntax. You can even see your results in the tabular views. Elasticsearch provides a variety of approaches, such as the REST API interface, the command-line interface, the JDBC (Java Database Connectivity) driver, and the ODBC (Open Database Connectivity...