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Create a Text Index on Self-Managed Deployments

Note

MongoDB offers an improved full-text search solution, MongoDB Search, and vector search solution, MongoDB Vector Search. We recommend using MongoDB Search indexes or MongoDB Vector Search indexes instead of text indexes.

Text indexes support $text queries on fields containing string content. Text indexes improve performance when searching for specific words or multi-word strings within string content.

To create a text index, use the db.collection.createIndex() method. To index a field that contains a string or an array of string elements, specify the string "text" as the index key:

db.<collection>.createIndex(
   {
      <field1>: "text",
      <field2>: "text",
      ...
   }
)

About this Task

A collection can have at most one text index.
MongoDB Search (available in MongoDB) supports multiple full-text search indexes on a single collection. To learn more, see the MongoDB Search documentation.
You can index multiple fields in a single text index. A text index can contain up to 32 fields. To see an example, see Create a Compound Text Index.

Before You Begin

Create a blog collection with the following documents:

db.blog.insertMany( [
   {
     _id: 1,
     content: "This morning I had a cup of coffee.",
     about: "beverage",
     keywords: [ "coffee" ]
   },
   {
     _id: 2,
     content: "Who likes chocolate ice cream for dessert?",
     about: "food",
     keywords: [ "poll" ]
   },
   {
     _id: 3,
     content: "My favorite flavors are strawberry and coffee",
     about: "ice cream",
     keywords: [ "food", "dessert" ]
   }
] )

Procedures

The following examples show you how to:

Create a Single-Field Text Index
Create a Compound Text Index

Create a Single-Field Text Index

Create a text index on the content field:

db.blog.createIndex( { "content": "text" } )

The index supports $text queries on the content field. For example, the following query returns documents where the content field contains the string coffee:

db.blog.find(
   {
      $text: { $search: "coffee" }
   }
)

Output:

[
   {
     _id: 1,
     content: 'This morning I had a cup of coffee.',
     about: 'beverage',
     keywords: [ 'coffee' ]
   },
   {
     _id: 3,
     content: 'My favorite flavors are strawberry and coffee',
     about: 'ice cream',
     keywords: [ 'food', 'dessert' ]
   }
]

Matches on Non-Indexed Fields

The { "content": "text" } index only includes the content field, and does not return matches on non-indexed fields. For example, the following query searches the blog collection for the string food:

db.blog.find(
   {
      $text: { $search: "food" }
   }
)

The preceding query returns no documents. Although the string food appears in documents _id: 2 and _id: 3, it appears in the about and keywords fields respectively. The about and keywords fields are not included in the text index, and therefore do not affect $text query results.

Create a Compound Text Index

Note

Before you can create the index in this example, you must drop any existing text indexes on the blog collection.

Create a compound text index on the about and keywords fields in the blog collection:

db.blog.createIndex(
   {
      "about": "text",
      "keywords": "text"
   }
)

The index supports $text queries on the about and keywords fields. For example, the following query returns documents where the string food appears in either the about or keywords field:

db.blog.find(
   {
      $text: { $search: "food" }
   }
)

Output:

[
  {
    _id: 3,
    content: 'My favorite flavors are strawberry and coffee',
    about: 'ice cream',
    keywords: [ 'food', 'dessert' ]
  },
  {
    _id: 2,
    content: 'Who likes chocolate ice cream for dessert?',
    about: 'food',
    keywords: [ 'poll' ]
  }
]

Back

Text Indexes

Create a Wildcard Text Index