When sorting data on more than one field in an Access query which field is the major sort key?

You can sort on a maximum of 32 keys.

Changed in version 4.4.

MongoDB does not store documents in a collection in a particular order. When sorting on a field which contains duplicate values, documents containing those values may be returned in any order.

If consistent sort order is desired, include at least one field in your sort that contains unique values. The easiest way to guarantee this is to include the _id field in your sort query.

Consider the following restaurant collection:

db.restaurants.insertMany( [
   { "_id" : 1, "name" : "Central Park Cafe", "borough" : "Manhattan"},
   { "_id" : 2, "name" : "Rock A Feller Bar and Grill", "borough" : "Queens"},
   { "_id" : 3, "name" : "Empire State Pub", "borough" : "Brooklyn"},
   { "_id" : 4, "name" : "Stan's Pizzaria", "borough" : "Manhattan"},
   { "_id" : 5, "name" : "Jane's Deli", "borough" : "Brooklyn"},
] );

The following command uses the sort() method to sort on the borough field:

db.restaurants.find().sort( { "borough": 1 } )

In this example, sort order may be inconsistent, since the borough field contains duplicate values for both Manhattan and Brooklyn. Documents are returned in alphabetical order by borough, but the order of those documents with duplicate values for borough might not be the same across multiple executions of the same sort. For example, here are the results from two different executions of the above command:

{ "_id" : 3, "name" : "Empire State Pub", "borough" : "Brooklyn" }
{ "_id" : 5, "name" : "Jane's Deli", "borough" : "Brooklyn" }
{ "_id" : 1, "name" : "Central Park Cafe", "borough" : "Manhattan" }
{ "_id" : 4, "name" : "Stan's Pizzaria", "borough" : "Manhattan" }
{ "_id" : 2, "name" : "Rock A Feller Bar and Grill", "borough" : "Queens" }
{ "_id" : 5, "name" : "Jane's Deli", "borough" : "Brooklyn" }
{ "_id" : 3, "name" : "Empire State Pub", "borough" : "Brooklyn" }
{ "_id" : 4, "name" : "Stan's Pizzaria", "borough" : "Manhattan" }
{ "_id" : 1, "name" : "Central Park Cafe", "borough" : "Manhattan" }
{ "_id" : 2, "name" : "Rock A Feller Bar and Grill", "borough" : "Queens" }

While the values for borough are still sorted in alphabetical order, the order of the documents containing duplicate values for borough (i.e. Manhattan and Brooklyn) is not the same.

To achieve a consistent sort, add a field which contains exclusively unique values to the sort. The following command uses the sort() method to sort on both the borough field and the _id field:

db.restaurants.find().sort( { "borough": 1, "_id": 1 } )

Since the _id field is always guaranteed to contain exclusively unique values, the returned sort order will always be the same across multiple executions of the same sort.

Specify in the sort parameter the field or fields to sort by and a value of 1 or -1 to specify an ascending or descending sort respectively.

The following operation sorts the documents first by the age field in descending order and then by the posts field in ascending order:

db.users.find({ }).sort( { age : -1, posts: 1 } )

When comparing values of different BSON types, MongoDB uses the following comparison order, from lowest to highest:

1. MinKey (internal type)

2. Null

3. Numbers (ints, longs, doubles, decimals)

4. Symbol, String

5. Object

6. Array

7. BinData

8. ObjectId

9. Boolean

10. Date

11. Timestamp

12. Regular Expression

13. MaxKey (internal type)

For details on the comparison/sort order for specific types, see Comparison/Sort Order.

For a $text search, you can sort by descending relevance score using the { $meta: "textScore" } expression.

The following sample document specifies a descending sort by the "textScore" metadata:

db.users.find(
   { $text: { $search: "operating" } },
   { score: { $meta: "textScore" }}        // Optional starting in MongoDB 4.4
).sort({ score: { $meta: "textScore" } })

The "textScore" metadata sorts in descending order.

For more information, see $meta for details.

MongoDB can obtain the results of a sort operation from an index which 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.

Sort operations that use an index often have better performance than blocking sorts. For more information on creating indexes to support sort operations, see Use Indexes to Sort Query Results.

If MongoDB requires using 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.

To check if MongoDB must perform a blocking sort, append cursor.explain() to the query and check the explain results. If the query plan contains a SORT stage, then MongoDB must perform a blocking sort operation subject to the 100 megabyte memory limit.

To prevent blocking sorts from consuming too much memory:

• Create an index to support the sort operation. See Use Indexes to Sort Query Results for more information and examples.

• Limit the amount of data to sort by using cursor.limit() with cursor.sort(). See Limit Results for more information and examples.

Tip

See also:

You can use sort() in conjunction with limit() to return the first (in terms of the sort order) k documents, where k is the specified limit.

If MongoDB cannot obtain the sort order via an index scan, then MongoDB uses a top-k sort algorithm. This algorithm buffers the first k results (or last, depending on the sort order) seen so far by the underlying index or collection access. If at any point the memory footprint of these k results exceeds 100 megabytes, the query will fail unless the query specifies cursor.allowDiskUse() (New in MongoDB 4.4).

Tip

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When a set of results are both sorted and projected, the MongoDB query engine will always apply the sorting first.

Queries that include a sort by $natural order do not use indexes to fulfill the query predicate with the following exception: If the query predicate is an equality condition on the _id field { _id: <value> }, then the query with the sort by $natural order can use the _id index.

Tip

See also: