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Compound Indexes

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  • Overview
  • Sample Data
  • Create a Compound Index
  • Collation

Compound indexes hold references to multiple fields within a collection's documents, improving query and sort performance.

The examples in this guide use the sample_mflix.movies collection from the Atlas sample datasets. To learn how to create a free MongoDB Atlas cluster and load the sample datasets, see the Get Started with PyMongo.

The following example creates a compound index on the type and genre fields:

movies.create_index([("type", pymongo.ASCENDING), ("genre", pymongo.ASCENDING)])

The following is an example of a query that uses the index created in the preceding code example:

query = { "type": "movie", "genre": "Drama" }
sort = [("type", pymongo.ASCENDING), ("genre", pymongo.ASCENDING)]
cursor = movies.find(query).sort(sort)

For more information, see Compound Indexes in the MongoDB Server manual.

When you create an index, you can specify a default collation for all operations you perform on fields that are included in the index.

A collation is a set of language-specific rules for string comparison, such as for letter case and accent marks.

To specify a collation, create an instance of the Collation class or a Python dictionary. For a list of options to pass to the Collation constructor or include as keys in the dictionary, see Collation in the MongoDB Server manual.

Tip

Import Collation

To create an instance of the Collation class, you must import it from pymongo.collation.

To use an index with a specified collation, your operation must meet the following criteria:

  • The operation uses the same collation as the one specified in the index.

  • The operation is covered by the index that contains the collation.

The following example creates the same index as the previous example, but with a default collation of fr_CA:

from pymongo.collation import Collation
movies.create_index([("type", pymongo.ASCENDING), ("genre", pymongo.ASCENDING)],
collation=Collation(locale='fr_CA'))

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