Text Indexes¶

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Create Text Index
Storage Requirements and Performance Costs
Text Search

New in version 2.4.

MongoDB provides text indexes to support text search of string content in documents of a collection. text indexes are case-insensitive and can include any field whose value is a string or an array of string elements. You can only access the text index with the text command.

Important

Before you can create a text index or run the text command, you need to manually enable the text search. See Enable Text Search for information on how to enable the text search feature.
A collection can have at most one text index.

Create Text Index¶

To create a text index, use the db.collection.ensureIndex() method. To index a field that contains a string or an array of string elements, include the field and specify the string literal "text" in the index document, as in the following example:

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db.reviews.ensureIndex( { comments: "text" } )

For examples of creating text indexes on multiple fields, see Create a text Index.

text indexes drop language-specific stop words (e.g. in English, “the,” “an,” “a,” “and,” etc.) and uses simple language-specific suffix stemming. See Text Search Languages for the supported languages and Specify a Language for Text Index for details on specifying languages with text indexes.

text indexes can satisfy the filter component of a text search. For details, see Create text Index to Satisfy the filter Component of Text Search.

Storage Requirements and Performance Costs¶

text indexes have the following storage requirements and performance costs:

text indexes change the space allocation method for all future record allocations in a collection to usePowerOf2Sizes.
text indexes can be large. They contain one index entry for each unique post-stemmed word in each indexed field for each document inserted.
Building a text index is very similar to building a large multi-key index and will take longer than building a simple ordered (scalar) index on the same data.
When building a large text index on an existing collection, ensure that you have a sufficiently high limit on open file descriptors. See the recommended settings.
text indexes will impact insertion throughput because MongoDB must add an index entry for each unique post-stemmed word in each indexed field of each new source document.
Additionally, text indexes do not store phrases or information about the proximity of words in the documents. As a result, phrase queries will run much more effectively when the entire collection fits in RAM.

Text Search¶

Text search supports the search of string content in documents of a collection. MongoDB provides the text command to perform the text search. The text command accesses the text index.

The text search process:

tokenizes and stems the search term(s) during both the index creation and the text command execution.
assigns a score to each document that contains the search term in the indexed fields. The score determines the relevance of a document to a given search query.

By default, the text command returns at most the top 100 matching documents as determined by the scores. The command can search for words and phrases. The command matches on the complete stemmed words. For example, if a document field contains the word blueberry, a search on the term blue will not match the document. However, a search on either blueberry or blueberries will match.

For information and examples on various text search patterns, see Search String Content for Text.

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