Relational databases have concepts such as rows, columns, tables, and schema. Elasticsearch and other document-oriented stores are based on different abstractions. Elasticsearch is a document-oriented store. JSON documents are first class citizens in Elasticsearch. These JSON documents are organized within different types and indexes. We will look at the following core abstractions of Elasticsearch:
- Index
- Type
- Document
- Cluster
- Node
- Shards and replicas
- Mappings and types
- Inverted index
Let us start learning these with an example:
PUT /catalog/product/1 { "sku": "SP000001", "title": "Elasticsearch for Hadoop", "description": "Elasticsearch for Hadoop", "author": "Vishal Shukla", "ISBN": "1785288997", "price": 26.99 }
Copy and paste this example into the editor of your Kibana Console UI and execute it. This will index a document which represents a product in the product catalog of a system. All examples written for the Kibana Console UI can be very easily converted...