Text vs keyword field types in Elasticsearch

Introduction

We use text and keyword fields to store words differently so we can search and sort data easily.

When you want to search inside a sentence or paragraph, like searching words in a book.

When you want to filter or sort exact values, like filtering by country name or sorting by product code.

When you want to do full-text search with relevance scoring, like searching blog posts by keywords.

When you want to group data by exact matches, like grouping users by their exact email addresses.

Syntax

Elasticsearch

{
  "mappings": {
    "properties": {
      "field_name": {
        "type": "text" | "keyword"
      }
    }
  }
}

text fields are analyzed and broken into words for full-text search.

keyword fields are not analyzed and stored as exact values for filtering and sorting.

Examples

This defines a description field as text for full-text search.

Elasticsearch

{
  "mappings": {
    "properties": {
      "description": {
        "type": "text"
      }
    }
  }
}

This defines a country field as keyword for exact matching and sorting.

Elasticsearch

{
  "mappings": {
    "properties": {
      "country": {
        "type": "keyword"
      }
    }
  }
}

This example shows both text and keyword fields in one mapping.

Elasticsearch

{
  "mappings": {
    "properties": {
      "title": {
        "type": "text"
      },
      "status": {
        "type": "keyword"
      }
    }
  }
}

Sample Program

This mapping sets comment as text for searching words inside comments, and user_id as keyword for exact user ID filtering.

Elasticsearch

{
  "mappings": {
    "properties": {
      "comment": {
        "type": "text"
      },
      "user_id": {
        "type": "keyword"
      }
    }
  }
}

Important Notes

Use text fields when you want to search inside the content.

Use keyword fields when you want to filter, sort, or aggregate exact values.

Sometimes you can use both types on the same data by using multi-fields.

Summary

Text fields break content into words for searching.

Keyword fields store exact values for filtering and sorting.

Choose the field type based on how you want to use the data.

Practice

1. Which Elasticsearch field type should you use if you want to perform full-text search inside sentences?

easy

A. text

B. keyword

C. integer

D. date

Solution

1. Step 1: Understand the purpose of text fields

   Text fields are designed for full-text search, allowing analysis and tokenization of sentences.

2. Step 2: Compare with keyword fields

   Keyword fields are for exact matches and do not analyze the text, so they are not suitable for searching inside sentences.

3. Final Answer:

   text -> Option A

4. Quick Check:

   Full-text search = text [OK]

Hint: Full-text search needs analyzed text fields [OK]

Common Mistakes:

• Choosing keyword for full-text search
• Confusing integer or date types with text
• Thinking keyword fields tokenize text

2. Which of the following is the correct way to define a keyword field in an Elasticsearch mapping?

easy

A. "name": { "type": "text" }

B. "name": { "type": "keyword" }

C. "name": { "type": "string" }

D. "name": { "type": "fulltext" }

Solution

1. Step 1: Recall Elasticsearch field types

   Elasticsearch uses "keyword" as the type for exact match fields.

2. Step 2: Identify the correct syntax

   "keyword" is the correct type name; "text" is for analyzed fields, "string" and "fulltext" are invalid types.

3. Final Answer:

   "name": { "type": "keyword" } -> Option B

4. Quick Check:

   Keyword field syntax = "name": { "type": "keyword" } [OK]

Hint: Keyword type is exactly "keyword" in mapping [OK]

Common Mistakes:

• Using "string" instead of "keyword"
• Confusing "text" with "keyword"
• Using invalid type names like "fulltext"

3. Given this Elasticsearch mapping snippet:

{
  "properties": {
    "title": { "type": "text" },
    "category": { "type": "keyword" }
  }
}

Which query will correctly filter documents where category is exactly "books"?

medium

A. { "term": { "category": "books" } }

B. { "match": { "category": "books" } }

C. { "match": { "title": "books" } }

D. { "term": { "title": "books" } }

Solution

1. Step 1: Identify field types and query types

   "category" is a keyword field, so exact match queries use "term" query.

2. Step 2: Match query usage

   "match" queries are for full-text search on text fields, not exact matches on keyword fields.

3. Final Answer:

   { "term": { "category": "books" } } -> Option A

4. Quick Check:

   Exact filter on keyword = term query [OK]

Hint: Use term query for keyword fields exact match [OK]

Common Mistakes:

• Using match query on keyword fields
• Filtering text fields with term query expecting full-text search
• Confusing field names in queries

4. You have this mapping:

{
  "properties": {
    "username": { "type": "keyword" },
    "bio": { "type": "text" }
  }
}

A developer tries to filter users with username containing "john" using this query:

{ "match": { "username": "john" } }

Why does this query not work as expected?

medium

A. Because match query only works on numeric fields

B. Because username field should be of type text for exact matches

C. Because match query does not work on keyword fields for partial matches

D. Because bio field should be used instead of username

Solution

1. Step 1: Understand keyword field behavior

   Keyword fields are not analyzed and do not support partial matching with match query.

2. Step 2: Understand match query limitations

   Match query analyzes input and is meant for text fields, not keyword fields which require term or wildcard queries for partial matches.

3. Final Answer:

   Because match query does not work on keyword fields for partial matches -> Option C

4. Quick Check:

   Match query + keyword field = no partial match [OK]

Hint: Match query needs text fields, not keyword [OK]

Common Mistakes:

• Thinking keyword fields support partial match with match query
• Confusing field types for filtering
• Using match query on numeric or date fields

5. You want to store user tags in Elasticsearch so you can both filter by exact tag and search inside tag text. Which mapping setup is best?

hard

A. "tags": { "type": "text" }

B. "tags": { "type": "keyword" }

C. "tags": { "type": "keyword", "fields": { "analyzed": { "type": "text" } } }

D. "tags": { "type": "text", "fields": { "raw": { "type": "keyword" } } }

Solution

1. Step 1: Understand the need for both full-text search and exact filtering

   Full-text search requires text type; exact filtering requires keyword type.

2. Step 2: Use multi-fields to support both

   Mapping with "text" type and a subfield "raw" as "keyword" allows searching inside tags and filtering/sorting by exact tag.

3. Final Answer:

   "tags": { "type": "text", "fields": { "raw": { "type": "keyword" } } } -> Option D

4. Quick Check:

   Multi-fields = text + keyword for search and filter [OK]

Hint: Use multi-fields for both text search and exact filter [OK]

Common Mistakes:

• Using only text type and expecting exact filters
• Using only keyword type and expecting full-text search
• Not defining subfields for multi-purpose queries