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

Elasticsearch from Python Programming

In the last chapter, we introduced Java programming with Elasticsearch. A sample Spring Boot project is provided to demonstrate the programming technique for both the high-level and low-level REST clients. We also used Swagger UI to create an interface to test the REST API. To make a long story short, since the transport client will not be supported anytime soon, the REST client is the method you need to go with when you program with the Java language. In this chapter, we are going to introduce the Python Elasticsearch client. You will learn about two Elasticsearch client packages, elasticsearch-py and elasticsearch-dsl-py. The elasticsearch-py package is the official low-level client for Elasticsearch. The goal of the Python package is to provide common ground for all Elasticsearch-related code in Python. Elasticsearch DSL is a high-level...