Use Indexes to Sort Query Results
Since indexes contain ordered records, MongoDB can obtain the results of a sort from an index that includes the sort fields. MongoDB may use multiple indexes to support a sort operation if the sort uses the same indexes as the query predicate.
If MongoDB cannot use an index or indexes to obtain the sort order, MongoDB must perform a blocking sort operation on the data. A blocking sort indicates that MongoDB must consume and process all input documents to the sort before returning results. Blocking sorts do not block concurrent operations on the collection or database.
If MongoDB needs more than 100 megabytes of system memory for
the blocking sort operation, MongoDB returns an error unless the query
specifies cursor.allowDiskUse() (New in MongoDB 4.4).
allowDiskUse() allows MongoDB to use temporary files
on disk to store data exceeding the 100 megabyte system memory limit
while processing a blocking sort operation.
Sort operations that use an index often have better performance than blocking sorts.
Note
As a result of changes to sorting behavior on array fields in MongoDB 4.4, when you sort on an array indexed with a multikey index, the query plan includes a blocking sort stage, unless:
The index boundaries for all sort fields are
[MinKey, MaxKey], andNo boundaries for any multikey-indexed field have the same path prefix as the sort pattern.
Sort with a Single Field Index
If an ascending or a descending index is on a single field, the sort operation on the field can be in either direction.
For example, create an ascending index on the field a for a
collection records:
db.records.createIndex( { a: 1 } )
This index can support an ascending sort on a:
db.records.find().sort( { a: 1 } )
The index can also support the following descending sort on a by
traversing the index in reverse order:
db.records.find().sort( { a: -1 } )
Sort on Multiple Fields
Create a compound index to support sorting on multiple fields.
You can specify a sort on all the keys of the index or on a subset;
however, the sort keys must be listed in the same order as they
appear in the index. For example, an index key pattern { a: 1, b: 1
} can support a sort on { a: 1, b: 1 } but not on { b: 1, a:
1 }.
For a query to use a compound index for a sort, the specified sort direction
for all keys in the cursor.sort() document must match the index
key pattern or match the inverse of the index key pattern.
For example, an index key pattern { a: 1, b: -1 } can
support a sort on { a: 1, b: -1 } and { a: -1, b: 1 } but not
on { a: -1, b: -1 } or {a: 1, b: 1}.
Sort and Index Prefix
If the sort keys correspond to the index keys or an index prefix, MongoDB can use the index to sort the query results. A prefix of a compound index is a subset that consists of one or more keys at the start of the index key pattern.
For example, create a compound index on the data collection:
db.data.createIndex( { a:1, b: 1, c: 1, d: 1 } )
Then, the following are prefixes for that index:
{ a: 1 } { a: 1, b: 1 } { a: 1, b: 1, c: 1 }
The following query and sort operations use the index prefixes to sort the results. These operations do not need to sort the result set in memory.
Example | Index Prefix |
|---|---|
db.data.find().sort( { a: 1 } ) | { a: 1 } |
db.data.find().sort( { a: -1 } ) | { a: 1 } |
db.data.find().sort( { a: 1, b: 1 } ) | { a: 1, b: 1 } |
db.data.find().sort( { a: -1, b: -1 } ) | { a: 1, b: 1 } |
db.data.find().sort( { a: 1, b: 1, c: 1 } ) | { a: 1, b: 1, c: 1 } |
db.data.find( { a: { $gt: 4 } } ).sort( { a: 1, b: 1 } ) | { a: 1, b: 1 } |
Consider the following example in which the prefix keys of the index appear in both the query predicate and the sort:
db.data.find( { a: { $gt: 4 } } ).sort( { a: 1, b: 1 } )
In such cases, MongoDB can use the index to retrieve the documents in order specified by the sort. As the example shows, the index prefix in the query predicate can be different from the prefix in the sort.
Sort and Non-prefix Subset of an Index
An index can support sort operations on a non-prefix subset of the index key pattern. To do so, the query must include equality conditions on all the prefix keys that precede the sort keys.
For example, the collection data has the following index:
{ a: 1, b: 1, c: 1, d: 1 }
The following operations can use the index to get the sort order:
Example | Index Prefix |
|---|---|
db.data.find( { a: 5 } ).sort( { b: 1, c: 1 } ) | { a: 1 , b: 1, c: 1 } |
db.data.find( { b: 3, a: 4 } ).sort( { c: 1 } ) | { a: 1, b: 1, c: 1 } |
db.data.find( { a: 5, b: { $lt: 3} } ).sort( { b: 1 } ) | { a: 1, b: 1 } |
As the last operation shows, only the index fields preceding the sort subset must have the equality conditions in the query document; the other index fields may specify other conditions.
If the query does not specify an equality condition on an index
prefix that precedes or overlaps with the sort specification, the
operation will not efficiently use the index. For example, the
following operations specify a sort document of { c: 1 }, but the
query documents do not contain equality matches on the preceding index
fields a and b:
db.data.find( { a: { $gt: 2 } } ).sort( { c: 1 } ) db.data.find( { c: 5 } ).sort( { c: 1 } )
These operations will not efficiently use the index { a: 1, b: 1,
c: 1, d: 1 } and may not even use the index to retrieve the documents.
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.
Warning
Because indexes that are configured with collation use ICU collation keys to achieve sort order, collation-aware index keys may be larger than index keys for indexes without 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" } )
Important
Matches against document keys, including embedded document keys, use simple binary comparison. This means that a query for a key like "foo.bár" will not match the key "foo.bar", regardless of the value you set for the strength parameter.