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

Correctly configuring the cluster

While understanding the distribution of shards is essential, understanding the distribution of documents is also critical. Elasticsearch works to evenly spread the documents at shards. This is an appropriate behavior. Having a shard with the majority of the data cannot be wise.

Let's start two Elasticsearch nodes and create an index by running the following command:

curl -XPUT localhost:9200/my_index -d '{
  settings: {
    number_of_shards: 2,
    number_of_replicas: 0

We've created an index without replicas that are built of two shards. Now we add a document to index:

curl -XPOST localhost:9200/my_index/document -d '{
  "title": "The first document"

We will get the current shard level stats of the my_index by using the following command:
curl -XGET 'localhost:9200/my_index/_stats?level=shards&pretty'
"shards": {