Why mappings define document structure in Elasticsearch - See It in Action

Understanding Mappings in Elasticsearch

📖 Scenario: You are setting up a search system for a small online bookstore. You want to organize the book information so Elasticsearch knows how to store and search it properly.

🎯 Goal: Build an Elasticsearch index with a mapping that defines the structure of book documents, specifying fields and their types.

📋 What You'll Learn

Create an index called books with a mapping

Define fields title as text, author as keyword, and year as integer

Add a summary field as text with analyzer set to english

Ensure the mapping clearly shows the document structure

💡 Why This Matters

🌍 Real World

Elasticsearch mappings are used in real-world search engines to organize and optimize how data is stored and searched.

💼 Career

Understanding mappings is essential for roles like search engineers, backend developers, and data engineers working with Elasticsearch.

1

Create the index with basic mapping

Create an Elasticsearch index called books with a mapping that defines the fields title as text, author as keyword, and year as integer.

Elasticsearch

{
  "mappings": {
    "properties": {
      // Your code here
    }
  }
}

Need a hint?

Use the mappings key with properties to define each field and its type.

2

Add a summary field with analyzer

Add a new field called summary to the properties in the mapping. Set its type to text and add an analyzer property with the value english.

Elasticsearch

{
  "mappings": {
    "properties": {
      "title": { "type": "text" },
      "author": { "type": "keyword" },
      "year": { "type": "integer" },
      // Your code here
    }
  }
}

Need a hint?

The analyzer helps Elasticsearch understand the text better for searching.

3

Explain why mappings define document structure

Add a comment inside the mapping JSON explaining that mappings tell Elasticsearch how to store and search each field in the documents.

Elasticsearch

{
  "mappings": {
    "properties": {
      "title": { "type": "text" },
      "author": { "type": "keyword" },
      "year": { "type": "integer" },
      "summary": { "type": "text", "analyzer": "english" }
    }
  }
  // Your code here
}

Need a hint?

Use a comment to explain the purpose of mappings in the JSON.

4

Complete the index creation with mapping

Wrap the mapping inside a full index creation request JSON with the index name books as the key, including the mappings you defined.

Elasticsearch

{
  "books": {
    // Your code here
  }
}

Need a hint?

Put the mapping inside the index name key to complete the index creation JSON.