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 SQL REST API

The SQL REST API accepts a SQL statement in JSON format, executes it, and returns a response. The endpoint of the SQL REST API is shown in the following code block. You should use a parameter query with a SQL statement in the request body:

POST /_sql?format=response_format
{
"query": "....",
"parameter_x": parameter_x_value
}

Now, let's use the Kibana console to practice some examples outlined under the Query DSL section of Chapter 6, Search APIs:

  1. To use the Kibana console from dev_tools, click on the button with the wrench icon on the left-hand sidebar, as shown in the following screenshot:
  1. Then, type the SQL statement to retrieve all the records from the cf_etf index, as described in the following code block, in the left-hand panel and click on the green arrow button in the top-right corner of the panel:
POST...