Before we start writing our first queries to interact with Elasticsearch, we should familiarize ourselves with a very important tool: Kibana Console. This is important because Elasticsearch has a very rich REST API, allowing you to do all possible operations with Elasticsearch. Kibana Console has an editor which is very capable and aware of the REST API. It allows for auto-completion, and for the formatting of queries as you write them.

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...

In this section we will look at how to perform basic CRUD operations, which are the most fundamental operations required by any data store. Elasticsearch has a very well designed REST API, and the CRUD operations are targeted at documents. 

To understand how to perform CRUD operations, we will cover the following APIs. These APIs fall under the category of Document APIs that deal with documents:

• Index API
• Get API
• Update API
• Delete API

In Elasticsearch terminology, adding (or creating) a document into a type within an index of Elasticsearch is called an indexing operation. Essentially, it involves adding the document to the index by parsing all fields within the document...

In the previous section, we learnt how to perform CRUD operations with Elasticsearch. In the process, we saw how indexing the first document to an index which doesn't yet exist results in the creation of the new index and the mapping of the type.

Usually, you wouldn't want to let things happen automatically, as you would want to control how indices are created and also how mapping is created. We will see how you can take control of this process in this section and look at the following:

• Creating an index
• Create a mapping
• Updating a mapping

You can create an index and specify the number of shards and replicas to create:

PUT /catalog
{
  "settings...

We just looked at how to perform basic CRUD operations. Elasticsearch supports a wide variety of operation types. Some operations deal with documents, that is, creating, reading, updating, deleting, and so on. Some operations provide search and aggregations, while other operations are for providing cluster related operations, such as monitoring health. Broadly, the APIs that deal with Elasticsearch are categorized into the following types of APIs:

• Document APIs
• Search APIs
• Aggregations APIs
• Indices APIs
• Cluster APIs
• cat APIs

The Elasticsearch reference documentation has documented these APIs very nicely. In this book, we will not go into the APIs down to the last detail. We will conceptually understand, with examples, how the APIs can be leveraged to get the best out of Elasticsearch and other components of Elastic Stack.

We will look at the search and...