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Perform a Text Search (Self-Managed Deployments)


This page describes text query capabilities for self-managed (non-Atlas) deployments. For data hosted on MongoDB Atlas, MongoDB offers an improved full-text query solution, Atlas Search.

To run text search queries on self-managed deployments, you must have a text index on your collection. MongoDB provides text indexes to support text search queries on string content. Text indexes can include any field whose value is a string or an array of string elements. A collection can only have one text search index, but that index can cover multiple fields.

See the Text Indexes section for a full reference on text indexes, including behavior, tokenization, and properties.

This example demonstrates how to build a text index and use it to find coffee shops, given only text fields.

Create a collection stores with the following documents:

{ _id: 1, name: "Java Hut", description: "Coffee and cakes" },
{ _id: 2, name: "Burger Buns", description: "Gourmet hamburgers" },
{ _id: 3, name: "Coffee Shop", description: "Just coffee" },
{ _id: 4, name: "Clothes Clothes Clothes", description: "Discount clothing" },
{ _id: 5, name: "Java Shopping", description: "Indonesian goods" }

Run the following in mongosh to allow text search over the name and description fields:

db.stores.createIndex( { name: "text", description: "text" } )

You can also search for exact phrases by wrapping them in double-quotes. If the $search string includes a phrase and individual terms, text search will only match documents that include the phrase.

For example, the following will find all documents containing "coffee shop":

db.stores.find( { $text: { $search: "\"coffee shop\"" } } )

For more information, see Phrases.

To exclude a word, you can prepend a "-" character. For example, to find all stores containing "java" or "shop" but not "coffee", use the following:

db.stores.find( { $text: { $search: "java shop -coffee" } } )

MongoDB returns its results in unsorted order by default. However, $text queries compute a relevance score for each document that specifies how well a document matches the query.

To sort the results in order of relevance score, you must explicitly project the $meta textScore field and sort on it:

{ $text: { $search: "java coffee shop" } },
{ score: { $meta: "textScore" } }
).sort( { score: { $meta: "textScore" } } )

$text is also available in the aggregation pipeline.


Self-Managed Search