Book Image

Elasticsearch Indexing

By : Huseyin Akdogan
Book Image

Elasticsearch Indexing

By: Huseyin Akdogan

Overview of this book

Beginning with an overview of the way ElasticSearch stores data, you’ll begin to extend your knowledge to tackle indexing and mapping, and learn how to configure ElasticSearch to meet your users’ needs. You’ll then find out how to use analysis and analyzers for greater intelligence in how you organize and pull up search results – to guarantee that every search query is met with the relevant results! You’ll explore the anatomy of an ElasticSearch cluster, and learn how to set up configurations that give you optimum availability as well as scalability. Once you’ve learned how these elements work, you’ll find real-world solutions to help you improve indexing performance, as well as tips and guidance on safety so you can back up and restore data. Once you’ve learned each component outlined throughout, you will be confident that you can help to deliver an improved search experience – exactly what modern users demand and expect.
Table of Contents (15 chapters)
Elasticsearch Indexing
About the Author
About the Reviewer

Choosing the right amount of shards and replicas

If you have a limited dataset and the dataset grows by a small amount, you can use only a single primary shard with a replica. If your dataset is not limited and grows by a large amount, the optimal number of shards is dependent on the target number of nodes.

Actually, a single node can be sufficient for many simple use cases, but to reduce the fault tolerance when considering the nature of distributed architecture and to prevent data loss, you can use more than one node. So, we need to find the answer to the first question: How many nodes will work?

Even to answer this question, we need to find out the answers to a few questions. For example: Do we need to use the non-data node? If we don't need to use non-data nodes, considering the Elasticsearch shard allocation policy, we can say that a node requires at least one shard to be the data node - as well as a replica. In that case, we can follow the following formula:

Max number of data nodes ...