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Elasticsearch Essentials

Elasticsearch Essentials

By : Bharvi Dixit
4.3 (6)
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Elasticsearch Essentials

Elasticsearch Essentials

4.3 (6)
By: Bharvi Dixit

Overview of this book

With constantly evolving and growing datasets, organizations have the need to find actionable insights for their business. ElasticSearch, which is the world's most advanced search and analytics engine, brings the ability to make massive amounts of data usable in a matter of milliseconds. It not only gives you the power to build blazing fast search solutions over a massive amount of data, but can also serve as a NoSQL data store. This guide will take you on a tour to become a competent developer quickly with a solid knowledge level and understanding of the ElasticSearch core concepts. Starting from the beginning, this book will cover these core concepts, setting up ElasticSearch and various plugins, working with analyzers, and creating mappings. This book provides complete coverage of working with ElasticSearch using Python and performing CRUD operations and aggregation-based analytics, handling document relationships in the NoSQL world, working with geospatial data, and taking data backups. Finally, we’ll show you how to set up and scale ElasticSearch clusters in production environments as well as providing some best practices.
Table of Contents (12 chapters)
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11
Index

Chapter 4. Aggregations for Analytics

Elasticsearch is a search engine at the core but what makes it more usable is its ability to make complex data analytics in an easy and simple way. The volume of data is growing rapidly and companies want to perform analysis on data in real time. Whether it is log, real-time streaming of data, or static data, Elasticsearch works wonderfully in getting a summarization of data through its aggregation capabilities.

In this chapter, we will cover the following topics:

  • Introducing the aggregation framework
  • Metric and bucket aggregations
  • Combining search, buckets, and metrics
  • Memory pressure and implications
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