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Elasticsearch & Full Text Search Systems · Lesson

Customizing Field Mappings

Deep dive into defining explicit mappings for various field types, including text, keyword, numeric, date, and boolean fields.

Why Customize Mappings?

Elasticsearch is smart! It often guesses your data types when you index a document (this is called dynamic mapping). But sometimes, you need more precise control.

Explicit mappings let you define exactly how each field in your documents should be stored and indexed. This is crucial for optimal search behavior, efficient storage, and accurate aggregations.

Defining Your Index's Blueprint

A mapping acts like a schema for your index. You typically define it when you create a new index. It lives within the "mappings" object in your index creation request.

Here's the basic structure:

PUT /my_new_index
{
  "mappings": {
    "properties": {
      "your_field_name": {
        "type": "field_type_here"
      }
    }
  }
}

The "properties" object holds all your field definitions.

All lessons in this course

  1. Customizing Field Mappings
  2. Dynamic vs. Explicit Mappings
  3. Index Templates and Aliases
  4. Nested and Object Field Types
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