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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

Bucket aggregations


Similar to metric aggregations, bucket aggregations are also categorized into two forms: Single buckets that contain only a single bucket in the response, and multi buckets that contain more than one bucket in the response.

The following are the most important aggregations that are used to create buckets:

  • Multi bucket aggregations

    • Terms aggregation

    • Range aggregation

    • Date range aggregation

    • Histogram aggregation

    • Date histogram aggregation

  • Single bucket aggregation

    • Filter-based aggregation

    Note

    We will cover a few more aggregations such as nested and geo aggregations in subsequent chapters.

Buckets aggregation response formats are different from the response formats of metric aggregations. The response of a bucket aggregation usually comes in the following format:

"aggregations": {

      "aggregation_name": {
         "buckets": [
            {
               "key": value,
               "doc_count": value
            },
            ......
         ]
      }
   }

Note

All the bucket...

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