Book Image

Learning Elastic Stack 6.0

By : Pranav Shukla, Sharath Kumar M N
Book Image

Learning Elastic Stack 6.0

By: Pranav Shukla, Sharath Kumar M N

Overview of this book

The Elastic Stack is a powerful combination of tools for distributed search, analytics, logging, and visualization of data from medium to massive data sets. The newly released Elastic Stack 6.0 brings new features and capabilities that empower users to find unique, actionable insights through these techniques. This book will give you a fundamental understanding of what the stack is all about, and how to use it efficiently to build powerful real-time data processing applications. After a quick overview of the newly introduced features in Elastic Stack 6.0, you’ll learn how to set up the stack by installing the tools, and see their basic configurations. Then it shows you how to use Elasticsearch for distributed searching and analytics, along with Logstash for logging, and Kibana for data visualization. It also demonstrates the creation of custom plugins using Kibana and Beats. You’ll find out about Elastic X-Pack, a useful extension for effective security and monitoring. We also provide useful tips on how to use the Elastic Cloud and deploy the Elastic Stack in production environments. On completing this book, you’ll have a solid foundational knowledge of the basic Elastic Stack functionalities. You’ll also have a good understanding of the role of each component in the stack to solve different data processing problems.
Table of Contents (19 chapters)
Title Page
Credits
Disclaimer
About the Authors
About the Reviewer
www.PacktPub.com
Customer Feedback
Preface

Writing compound queries


This class of queries can be used to combine one or more queries to come up with a more complex query. Some compound queries convert scoring queries into non-scoring queries, and combine multiple scoring and non-scoring queries. We will look at the following compound queries:

  • Constant score query
  • Bool query

Constant score query

Elasticsearch supports querying both structured data and full text. While full-text queries need scoring mechanisms to find the best matching documents, structured searches don't need scoring. The constant score query allows us to convert a scoring query which normally runs in query context to a non-scoring filter contextThe constant score query is a very important tool in your toolbox.

For example, the term query is normally run in a query context. That means when Elasticsearch executes a term query, it not only filters the documents but also scores all of them:

GET /amazon_products/products/_search
{
  "query": {
    "term": {
      "manufacturer...