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Create Indexes to Support Your Queries
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An index supports a query when the index contains all the fields scanned by the query. The query scans the index and not the collection. Creating indexes that support queries results in greatly increased query performance.
This document describes strategies for creating indexes that support queries.
Create a Single-Key Index if All Queries Use the Same, Single Key
If you only ever query on a single key in a given collection, then you need
to create just one single-key index for that collection. For example, you
might create an index on category in the product collection:
db.products.createIndex( { "category": 1 } )
Create Compound Indexes to Support Several Different Queries
If you sometimes query on only one key and at other times query on that
key combined with a second key, then creating a compound index is more
efficient than creating a single-key index. MongoDB will use the
compound index for both queries. For example, you might create an index
on both category and item.
db.products.createIndex( { "category": 1, "item": 1 } )
This allows you both options. You can query on just category, and
you also can query on category combined with item.
A single compound index on multiple fields
can support all the queries that search a "prefix" subset of those fields.
Example
The following index on a collection:
{ x: 1, y: 1, z: 1 }
Can support queries that the following indexes support:
{ x: 1 } { x: 1, y: 1 }
There are some situations where the prefix indexes may offer better
query performance: for example if z is a large array.
The { x: 1, y: 1, z: 1 } index can also support many of the same
queries as the following index:
{ x: 1, z: 1 }
Also, { x: 1, z: 1 } has an additional use. Given the following
query:
db.collection.find( { x: 5 } ).sort( { z: 1} )
The { x: 1, z: 1 } index supports both the query and the sort
operation, while the { x: 1, y: 1, z: 1 } index only supports
the query. For more information on sorting, see
Use Indexes to Sort Query Results.
Starting in version 2.6, MongoDB can use index intersection to fulfill queries. The choice between creating compound indexes that support your queries or relying on index intersection depends on the specifics of your system. See Index Intersection and Compound Indexes for more details.
Index Use and Collation
To use an index for string comparisons, an operation must also specify the same collation. That is, an index with a collation cannot support an operation that performs string comparisons on the indexed fields if the operation specifies a different collation.
For example, the collection myColl has an index on a string
field category with the collation locale "fr".
db.myColl.createIndex( { category: 1 }, { collation: { locale: "fr" } } )
The following query operation, which specifies the same collation as the index, can use the index:
db.myColl.find( { category: "cafe" } ).collation( { locale: "fr" } )
However, the following query operation, which by default uses the "simple" binary collator, cannot use the index:
db.myColl.find( { category: "cafe" } )
For a compound index where the index prefix keys are not strings, arrays, and embedded documents, an operation that specifies a different collation can still use the index to support comparisons on the index prefix keys.
For example, the collection myColl has a compound index on the
numeric fields score and price and the string field
category; the index is created with the collation locale
"fr" for string comparisons:
db.myColl.createIndex( { score: 1, price: 1, category: 1 }, { collation: { locale: "fr" } } )
The following operations, which use "simple" binary collation
for string comparisons, can use the index:
db.myColl.find( { score: 5 } ).sort( { price: 1 } ) db.myColl.find( { score: 5, price: { $gt: NumberDecimal( "10" ) } } ).sort( { price: 1 } )
The following operation, which uses "simple" binary collation
for string comparisons on the indexed category field, can use
the index to fulfill only the score: 5 portion of the query:
db.myColl.find( { score: 5, category: "cafe" } )