Indexes索引

Index Names索引名称

The default name for an index is the concatenation of the indexed keys and each key's direction in the index ( i.e. 1 or -1) using underscores as a separator. 索引的默认名称是索引键和索引中每个键的方向（即-1或-1）的串联，使用下划线作为分隔符。For example, an index created on { item : 1, quantity: -1 } has the name item_1_quantity_-1.例如，在{ item : 1, quantity: -1 }上创建的索引的名称为item_1_quantity_-1。

You can create indexes with a custom name, such as one that is more human-readable than the default. 您可以使用自定义名称创建索引，例如比默认名称更易于阅读的索引。For example, consider an application that frequently queries the products collection to populate data on existing inventory. 例如，考虑一个经常查询products集合以填充现有库存数据的应用程序。The following createIndex() method creates an index on item and quantity named query for inventory:下面的createIndex()方法在item和quantity上创建索引，名为query for inventory：

db.products.createIndex(
  { item: 1, quantity: -1 } ,
  { name: "query for inventory" }
)

You can view index names using the db.collection.getIndexes() method. 可以使用db.collection.getIndexes()方法查看索引名称。You cannot rename an index once created. Instead, you must drop and re-create the index with a new name.索引一旦创建，就不能重命名。相反，您必须删除索引并使用新名称重新创建索引。

Single Field单个字段

In addition to the MongoDB-defined _id index, MongoDB supports the creation of user-defined ascending/descending indexes on a single field of a document.除了MongoDB定义的_id索引外，MongoDB还支持在文档的单个字段上创建用户定义的升序/降序索引。

For a single-field index and sort operations, the sort order (i.e. ascending or descending) of the index key does not matter because MongoDB can traverse the index in either direction.对于单个字段的索引和排序操作，索引键的排序顺序（即升序或降序）并不重要，因为MongoDB可以在任意方向遍历索引。

See Single Field Indexes and Sort with a Single Field Index for more information on single-field indexes.有关单字段索引的详细信息，请参阅单字段索引和使用单字段索引排序。

Compound Index复合指数

MongoDB also supports user-defined indexes on multiple fields, i.e. compound indexes.MongoDB还支持多个字段上的用户定义索引，即复合索引。

The order of fields listed in a compound index has significance. 在复合索引中列出的字段的顺序具有重要意义。For instance, if a compound index consists of { userid: 1, score: -1 }, the index sorts first by userid and then, within each userid value, sorts by score.例如，如果复合索引由{ userid: 1, score: -1 }组成，则该索引首先按userid排序，然后在每个userid值内按score排序。

For compound indexes and sort operations, the sort order (i.e. ascending or descending) of the index keys can determine whether the index can support a sort operation. 对于复合索引和排序操作，索引键的排序顺序（即升序或降序）可以决定索引是否支持排序操作。See Sort Order for more information on the impact of index order on results in compound indexes.有关索引顺序对复合索引中结果的影响的详细信息，请参阅排序顺序。

See also:另请参阅：

• Compound Indexes,复合索引，

• Sort on Multiple Fields按多个字段排序, and和

• The ESR (Equality, Sort, Range) RuleESR（相等、排序、范围）规则

Multikey Index多键索引

MongoDB uses multikey indexes to index the content stored in arrays. MongoDB使用多键索引对存储在数组中的内容进行索引。If you index a field that holds an array value, MongoDB creates separate index entries for every element of the array. 如果对包含数组值的字段进行索引，MongoDB会为数组的每个元素创建单独的索引条目。These multikey indexes allow queries to select documents that contain arrays by matching on element or elements of the arrays. 这些多键索引允许查询通过匹配数组的一个或多个元素来选择包含数组的文档。MongoDB automatically determines whether to create a multikey index if the indexed field contains an array value; you do not need to explicitly specify the multikey type.如果索引字段包含数组值，MongoDB会自动确定是否创建多键索引；您不需要显式指定多密钥类型。

See Multikey Indexes and Multikey Index Bounds for more information on multikey indexes.有关多键索引的详细信息，请参阅多键索引和多键索引边界。

Geospatial Index地理空间索引

To support efficient queries of geospatial coordinate data, MongoDB provides two special indexes: 2d indexes that uses planar geometry when returning results and 2dsphere indexes that use spherical geometry to return results.为了支持高效查询地理空间坐标数据，MongoDB提供了两个特殊的索引：在返回结果时使用平面几何体的2d索引和使用球面几何体返回结果的2dsphere索引。

This index is a sparse index. 此索引是稀疏索引。If you want to use a sparse index to create a compound index, first review the special considerations of using sparse compound indexes.如果要使用稀疏索引创建复合索引，请首先查看使用稀疏复合索引的特殊注意事项。

See Geospatial Indexes for a high level introduction to geospatial indexes.有关地理空间索引的高级介绍，请参阅地理空间索引。

Text Search Indexes文本搜索索引

For data hosted on MongoDB Atlas, you can support full-text search with Atlas Search indexes. 对于MongoDB Atlas上托管的数据，您可以使用Atlas search索引支持全文搜索。To learn more, see Create an Atlas Search Index.要了解更多信息，请参阅创建Atlas搜索索引。

For self-managed (non-Atlas) deployments, MongoDB provides a text index type that supports searching for string content in a collection. 对于自管理（非Atlas）部署，MongoDB提供了一种text索引类型，支持搜索集合中的字符串内容。To learn more about self-managed text indexes, see Text Indexes.要了解有关自管理文本索引的更多信息，请参阅文本索引。

This index is a sparse index. 此索引是稀疏索引。If you want to use a sparse index to create a compound index, first review the special considerations of using sparse compound indexes.如果要使用稀疏索引创建复合索引，请首先查看使用稀疏复合索引的特殊注意事项。

Hashed Indexes哈希索引

To support hash based sharding, MongoDB provides a hashed index type, which indexes the hash of the value of a field. 为了支持基于哈希的分片，MongoDB提供了一种哈希索引类型，它对字段值的哈希进行索引。These indexes have a more random distribution of values along their range, but only support equality matches and cannot support range-based queries.这些索引的值在其范围内的分布更加随机，但只支持相等匹配，不能支持基于范围的查询。

Clustered Indexes群集索引

Starting in MongoDB 5.3, you can create a collection with a clustered index. 从MongoDB 5.3开始，您可以创建一个具有聚集索引的集合。Collections created with a clustered index are called clustered collections.使用聚集索引创建的集合称为聚集集合。

See Clustered Collections.请参见聚集集合。

Wildcard Indexes通配符索引

Starting in MongoDB 4.2, you can use wildcard indexes to support queries against multiple, arbitrary, or unknown fields. 从MongoDB 4.2开始，您可以使用通配符索引来支持针对多个、任意或未知字段的查询。When you create a wildcard index, you specify $** to represent all fields or all values, allowing you to index any of the following with a single command:创建通配符索引时，您可以指定$**来表示所有字段或所有值，从而可以使用单个命令对以下任何项进行索引：

• All values of a field字段的所有值

• All fields in a document文档中的所有字段

• All fields in a document except specific field paths文档中除特定字段路径之外的所有字段

• Multiple specific fields in a document文档中的多个特定字段

To learn more, see Wildcard Indexes.要了解更多信息，请参阅通配符索引。

Unique Indexes唯一索引

The unique property for an index causes MongoDB to reject duplicate values for the indexed field. 索引的unique属性导致MongoDB拒绝索引字段的重复值。Other than the unique constraint, unique indexes are functionally interchangeable with other MongoDB indexes.除了唯一约束之外，唯一索引在功能上可以与其他MongoDB索引互换。

Partial Indexes部分索引

Partial indexes only index the documents in a collection that meet a specified filter expression. 分部索引仅对集合中符合指定筛选表达式的文档进行索引。By indexing a subset of the documents in a collection, partial indexes have lower storage requirements and reduced performance costs for index creation and maintenance.通过对集合中的文档子集进行索引，部分索引可以降低存储需求，并降低索引创建和维护的性能成本。

Partial indexes offer a superset of the functionality of sparse indexes and should be preferred over sparse indexes.部分索引提供了稀疏索引功能的超集，应该优先于稀疏索引。

Sparse Indexes稀疏索引

The sparse property of an index ensures that the index only contains entries for documents that have the indexed field. The index skips documents that do not have the indexed field.索引的sparse属性确保索引只包含具有索引字段的文档的条目。索引会跳过没有索引字段的文档。

You can combine the sparse index option with the unique index option to prevent inserting documents that have duplicate values for the indexed field(s) and skip indexing documents that lack the indexed field(s).您可以将sparse索引选项与unique索引选项结合使用，以防止插入索引字段值重复的文档，并跳过对缺少索引字段的文档进行索引。

TTL IndexesTTL索引

TTL indexes automatically remove documents from a collection after a certain amount of time. TTL索引会在一定时间后自动从集合中删除文档。This is ideal for certain types of information like machine generated event data, logs, and session information that only need to persist in a database for a finite amount of time.这非常适合某些类型的信息，如机器生成的事件数据、日志和会话信息，这些信息只需要在数据库中保留有限的时间。

See: Expire Data from Collections by Setting TTL for implementation instructions.有关实现说明，请参阅：通过设置TTL使集合中的数据过期。

Hidden Indexes隐藏索引

Hidden indexes are not visible to the query planner and cannot be used to support a query.隐藏索引对查询计划器不可见，不能用于支持查询。

By hiding an index from the planner, users can evaluate the potential impact of dropping an index without actually dropping the index. 通过向计划器隐藏索引，用户可以在不实际删除索引的情况下评估删除索引的潜在影响。If the impact is negative, the user can unhide the index instead of having to recreate a dropped index. 如果影响是负面的，用户可以取消隐藏索引，而不必重新创建已删除的索引。And because indexes are fully maintained while hidden, the indexes are immediately available for use once unhidden.由于索引在隐藏时是完全维护的，因此一旦取消隐藏，索引就可以立即使用。

Except for the _id index, you can hide any indexes.除了_id索引之外，您可以隐藏任何索引。