Create Indexes to Support Your Queries创建索引以支持您的查询

Create a Single-Key Index创建单键索引

If your application only queries on a single key in a given collection, then you need to create a single-key index for that collection. For example, you can create an index on category in the product collection:如果您的应用程序只查询给定集合中的单个键，那么您需要为该集合创建一个单键索引。例如，您可以在product（产品）集合中创建category（类别）索引：

db.products.createIndex( { category: 1 } )

The preceding index supports this query:前面的索引支持此查询：

db.products.find( { category: "electronics" } )

Create a Compound Index创建复合索引

If your application performs queries on both a single key and multiple keys, a compound index is more efficient than a single-key index. For example, you can create an index on the category, item, and location fields:如果应用程序对单键和多键都执行查询，则复合索引比单键索引更有效。例如，您可以在category、item和location字段上创建索引：

db.products.createIndex( { category: 1, item: 1, location: 1 } )

db.products.find( { category: "electronics" } )
db.products.find( { category: "electronics", item: "television" } )

Create Indexes to Support Text Search创建索引以支持文本搜索

For data hosted on MongoDB, you can support full-text search with MongoDB Search indexes. To learn more, see Create a MongoDB Search Index.对于托管在MongoDB上的数据，您可以使用MongoDB搜索索引支持全文搜索。要了解更多信息，请参阅创建MongoDB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. To learn more about self-managed text indexes, see Text Indexes on Self-Managed Deployments.对于自我管理（非Atlas）部署，MongoDB提供了一种text索引类型，支持在集合中搜索字符串内容。要了解有关自我管理文本索引的更多信息，请参阅自我管理部署上的文本索引。

Create Vector Search Indexes创建矢量搜索索引

Vector Search Indexes support queries on vector embeddings. To create Vector Search Indexes, see Index Fields for Vector Search.矢量搜索索引支持对矢量嵌入的查询。要创建矢量搜索索引，请参阅矢量搜索的索引字段。

Index Use and Collation索引使用和排序

To use an index for string comparisons, an operation must also specify the same collation. 要使用索引进行字符串比较，操作还必须指定相同的排序规则。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.也就是说，如果操作指定了不同的排序规则，则具有排序规则的索引无法支持对索引字段执行字符串比较的操作。

A restaurants collection has the following documents:restaurants（餐厅）集合有以下文件：

db.restaurants.insertMany( [
   { _id: 1, category: "café", status: "Open" },
   { _id: 2, category: "cafe", status: "open" },
   { _id: 3, category: "cafE", status: "open" }
] )

The restaurants collection has an index on a string field category with the collation locale "fr".restaurants集合在排序规则为"fr"的字符串字段category上有一个索引。

db.restaurants.createIndex( { category: 1 }, { collation: { locale: "fr" } } )

The following query, which specifies the same collation as the index, can use the index:以下查询指定了与索引相同的排序规则，可以使用索引：

db.restaurants.find( { category: "cafe" } ).collation( { locale: "fr" } )

However, the following query operation, which by default uses the "simple" binary collator, cannot use the index:但是，以下查询操作（默认情况下使用“简单”二进制排序器）不能使用索引：

db.restaurants.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.对于索引前缀键不是字符串、数组和嵌入式文档的复合索引，指定不同排序规则的操作仍然可以使用索引来支持对索引前缀键的比较。

For example, the collection restaurants has a compound index on the numeric fields score and score and the string field category; the index is created with the collation locale "fr" for string comparisons:例如，集合restaurants在数字字段score和score以及字符串字段类别上有一个复合索引；索引是使用排序规则区域设置“fr”创建的，用于字符串比较：

db.restaurants.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:以下使用"simple"二进制排序规则进行字符串比较的操作可以使用索引：

db.restaurants.find( { score: 5 } ).sort( { price: 1 } )
db.restaurants.find( { score: 5, price: { $gt: Decimal128( "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:以下操作使用"simple"二进制排序规则对索引化的category字段进行字符串比较，可以使用索引仅完成查询的score: 5部分：

db.restaurants.find( { score: 5, category: "cafe" } )

To confirm whether a query used an index, run the query with the explain() option.要确认查询是否使用了索引，请使用explain()选项运行查询。