Core concepts

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...