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

Pipeline aggregations


Pipeline aggregations, as their name suggests, allow you to aggregate over the result of another aggregation. They let you pipe the result of an aggregation as an input to another aggregation. Pipeline aggregations are a relatively new feature and they are still experimental. At a high level, there are two types of pipeline aggregation:

  • Parent pipeline aggregations have the pipeline aggregation nested inside other aggregations
  • Sibling pipeline aggregations have the pipeline aggregation as the sibling of the original aggregation from which pipelining is done

Let us understand how the pipeline aggregations work by taking one example of cumulative sum aggregation, which is a parent of pipeline aggregation.

Calculating the cumulative sum of usage over time

While understanding the Date Histogram aggregation and in the section Focusing on a specific day and changing intervalswe looked at the aggregation, to compute hourly bandwidth usage for one particular day. After completing...