Elasticsearch Document Example: JSON Structure and Fields

This example showcases a sample Elasticsearch document in JSON format. It demonstrates how to represent data with various field types, including nested objects and arrays:

{
  'name': 'John Doe',
  'age': 30,
  'email': 'john.doe@example.com',
  'address': {
    'street': '123 Main St',
    'city': 'Anytown',
    'state': 'CA',
    'zip': '12345'
  },
  'phone_numbers': [
    {
      'type': 'home',
      'number': '555-1234'
    },
    {
      'type': 'work',
      'number': '555-5678'
    }
  ]
}

Key Concepts:

• Document: A single unit of data in Elasticsearch, represented as a JSON object.
• Fields: Key-value pairs within a document, defining different attributes of the data.
• Nested Objects: Objects that contain other fields within a document, allowing you to represent hierarchical data structures (e.g., the 'address' field).
• Arrays: Lists of values within a document, allowing you to represent collections of data (e.g., the 'phone_numbers' field).

Understanding the Example:

• name: A string field storing the person's name.
• age: An integer field representing the person's age.
• email: A string field holding the person's email address.
• address: A nested object representing the person's address with fields for 'street', 'city', 'state', and 'zip'.
• phone_numbers: An array of objects, each containing information about a phone number, including its 'type' and 'number'.

This example provides a foundation for understanding how to structure data within Elasticsearch documents. By exploring different field types and structures, you can effectively model your data and perform efficient searches and analysis using Elasticsearch's capabilities.