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Elasticsearch Essentials

You're reading from   Elasticsearch Essentials Harness the power of ElasticSearch to build and manage scalable search and analytics solutions with this fast-paced guide

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Product type Paperback
Published in Jan 2016
Publisher
ISBN-13 9781784391010
Length 240 pages
Edition 1st Edition
Languages
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Toc

Table of Contents (12) Chapters Close

Preface 1. Getting Started with Elasticsearch FREE CHAPTER 2. Understanding Document Analysis and Creating Mappings 3. Putting Elasticsearch into Action 4. Aggregations for Analytics 5. Data Looks Better on Maps: Master Geo-Spatiality 6. Document Relationships in NoSQL World 7. Different Methods of Search and Bulk Operations 8. Controlling Relevancy 9. Cluster Scaling in Production Deployments 10. Backups and Security Index

Considerations for using document relationships


Over the years, Elasticsearch has improved a lot in reducing memory pressure by introducing doc_values, which is a little slower than the in-memory data structure, fielddata, but still offer reasonable speed and performance. However, because of the way nested and parent-child documents are stored and searched, you should keep the pros and cons in mind before modeling your data. The following is a comparison of nested versus parent-child types, which is nicely outlined by Zachary Tong in one of his articles:

Nested

Parent-Child

Stored in the same Lucene block as each other, which helps in a faster read/query performance. Reading a nested doc is faster than the equivalent parent/child.

Children are stored separately from the parent, but are routed to the same shard. So parent/children performance is slightly less on read/query than nested.

Updating a single field in a nested document (parent or nested children) forces ES to re-index the entire...

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