db.collection.createIndex()

Collation and Index Use排序规则和索引的使用

If you have specified a collation at the collection level, then:如果已在集合级别指定排序规则，则：

• If you do not specify a collation when creating the index, MongoDB creates the index with the collection's default collation.如果在创建索引时未指定排序规则，MongoDB将使用集合的默认排序规则创建索引。
• If you do specify a collation when creating the index, MongoDB creates the index with the specified collation.如果在创建索引时指定了排序规则，MongoDB将使用指定的排序规则创建索引。

You can create multiple indexes on the same key(s) with different collations. 可以使用不同的排序规则在同一个键上创建多个索引。To create indexes with the same key pattern but different collations, you must supply unique index names.要创建具有相同键模式但排序规则不同的索引，必须提供唯一的索引名称。

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，如果具有排序规则的索引指定了不同的排序规则，则该索引无法支持对索引字段执行字符串比较的操作。

For example, the collection myColl has an index on a string field category with the collation locale "fr".例如，集合myColl在排序区域设置为"fr"的字符串字段category上有一个索引。

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

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

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:但是，以下查询操作（默认情况下使用“简单”二进制collator）无法使用索引：

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.对于索引前缀键不是字符串、数组和嵌入文档的复合索引，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 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:例如，集合myColl在数字字段score和price以及字符串字段category上有一个复合索引；索引是使用排序规则语言环境"fr"创建的，用于字符串比较：

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:以下操作使用"simple"二进制排序规则进行字符串比较，可以使用索引：

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:以下操作使用"simple"二进制排序规则对索引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.myColl.find( { score: 5, category: "cafe" } )

Non-Collation and Non-Hidden Options非排序规则和非隐藏选项

With the exception of the collation option, if you create an index with one set of index options and then try to recreate the same index but with different index options, MongoDB will not change the options nor recreate the index.除排序规则选项外，如果使用一组索引选项创建索引，然后尝试使用不同的索引选项重新创建相同的索引，MongoDB将不会更改选项，也不会重新创建索引。

The hidden option can be changed without dropping and recreating the index. 可以在不删除和重新创建索引的情况下更改隐藏选项。See Hidden Option.请参见隐藏选项。

To change the other index options, drop the existing index with db.collection.dropIndex() before running db.collection.createIndex() with the new options.要更改其他索引选项，请先使用db.collection.dropIndex()删除现有索引，然后使用新选项运行db.collection.createIndex()。

Collation Option排序规则选项

You can create multiple indexes on the same key(s) with different collations. 可以使用不同的排序规则在同一个键上创建多个索引。To create indexes with the same key pattern but different collations, you must supply unique index names.要创建具有相同键模式但排序规则不同的索引，必须提供唯一的索引名称。

Hidden Option隐藏选项

To hide or unhide existing indexes, you can use the following mongosh methods:要隐藏或取消隐藏现有索引，可以使用以下mongosh方法：

• db.collection.hideIndex()
• db.collection.unhideIndex()

For example,例如

• To change the hidden option for an index to true, use the db.collection.hideIndex() method:要将索引的hidden选项更改为true，请使用db.collection.hideIndex()方法：

  db.restaurants.hideIndex( { borough: 1, ratings: 1 } );

• To change the hidden option for an index to false, use the db.collection.unhideIndex() method:要将索引的hidden选项更改为false，请使用db.collection.unhideIndex()方法：

  db.restaurants.unhideIndex( { borough: 1, city: 1 } );

Create a Wildcard Index on a Single Field Path在单个字段路径上创建通配符索引

Consider a collection products_catalog where documents may contain a product_attributes field. 考虑一个集合products_catalog，其中的文档可能包含product_attributes字段。The product_attributes field can contain arbitrary nested fields, including embedded documents and arrays:product_attributes字段可以包含任意嵌套字段，包括嵌入的文档和数组：

{
  "_id" : ObjectId("5c1d358bf383fbee028aea0b"),
  "product_name" : "Blaster Gauntlet",
  "product_attributes" : {
     "price" : {
       "cost" : 299.99
       "currency" : USD
     }
     ...
  }
},
{
  "_id" : ObjectId("5c1d358bf383fbee028aea0c"),
  "product_name" : "Super Suit",
  "product_attributes" : {
     "superFlight" : true,
     "resistance" : [ "Bludgeoning", "Piercing", "Slashing" ]
     ...
  },
}

The following operation creates a wildcard index on the product_attributes field:以下操作将在product_attributes字段上创建通配符索引：

use inventory
db.products_catalog.createIndex( { "product_attributes.$**" : 1 } )

With this wildcard index, MongoDB indexes all scalar values of product_attributes. 使用此通配符索引，MongoDB将为product_attributes的所有标量值建立索引。If the field is a nested document or array, the wildcard index recurses into the document/array and indexes all scalar fields in the document/array.如果字段是嵌套文档或数组，通配符索引将递归到文档/数组，并为文档/数组中的所有标量字段编制索引。

The wildcard index can support arbitrary single-field queries on product_attributes or one of its nested fields:通配符索引可以支持对product_attributes或其中一个嵌套字段的任意单字段查询：

db.products_catalog.find( { "product_attributes.superFlight" : true } )
db.products_catalog.find( { "product_attributes.maxSpeed" : { $gt : 20 } } )
db.products_catalog.find( { "product_attributes.elements" : { $eq: "water" } } )

Create a Wildcard Index on All Field Paths在所有字段路径上创建通配符索引

Consider a collection products_catalog where documents may contain a product_attributes field. 考虑一个集合products_catalog，其中的文档可能包含product_attributes字段。The product_attributes field can contain arbitrary nested fields, including embedded documents and arrays:product_attributes字段可以包含任意嵌套字段，包括嵌入的文档和数组：

{
  "_id" : ObjectId("5c1d358bf383fbee028aea0b"),
  "product_name" : "Blaster Gauntlet",
  "product_attributes" : {
     "price" : {
       "cost" : 299.99
       "currency" : USD
     }
     ...
  }
},
{
  "_id" : ObjectId("5c1d358bf383fbee028aea0c"),
  "product_name" : "Super Suit",
  "product_attributes" : {
     "superFlight" : true,
     "resistance" : [ "Bludgeoning", "Piercing", "Slashing" ]
     ...
  },
}

The following operation creates a wildcard index on all scalar fields (excluding the _id field):以下操作将在所有标量字段（不包括_id字段）上创建通配符索引：

use inventory
db.products_catalog.createIndex( { "$**" : 1 } )

With this wildcard index, MongoDB indexes all scalar fields for each document in the collection. 使用此通配符索引，MongoDB为集合中每个文档的所有标量字段建立索引。If a given field is a nested document or array, the wildcard index recurses into the document/array and indexes all scalar fields in the document/array.如果给定字段是嵌套文档或数组，通配符索引将递归到文档/数组中，并为文档/数组的所有标量字段编制索引。

The created index can support queries on any arbitrary field within documents in the collection:创建的索引可以支持查询集合中文档中的任意字段：

db.products_catalog.find( { "product_price" : { $lt : 25 } } )
db.products_catalog.find( { "product_attributes.elements" : { $eq: "water" } } )

Include Specific Fields in Wildcard Index Coverage在通配符索引覆盖范围中包括特定字段

Consider a collection products_catalog where documents may contain a product_attributes field. 考虑一个集合products_catalog，其中的文档可能包含product_attributes字段。The product_attributes field can contain arbitrary nested fields, including embedded documents and arrays:product_attributes字段可以包含任意嵌套字段，包括嵌入的文档和数组：

{
  "_id" : ObjectId("5c1d358bf383fbee028aea0b"),
  "product_name" : "Blaster Gauntlet",
  "product_attributes" : {
     "price" : {
       "cost" : 299.99
       "currency" : USD
     }
     ...
  }
},
{
  "_id" : ObjectId("5c1d358bf383fbee028aea0c"),
  "product_name" : "Super Suit",
  "product_attributes" : {
     "superFlight" : true,
     "resistance" : [ "Bludgeoning", "Piercing", "Slashing" ]
     ...
  },
}

The following operation creates a wildcard index and uses the wildcardProjection option to include only scalar values of the product_attributes.elements and product_attributes.resistance fields in the index.以下操作创建通配符索引，并使用wildcardProjection选项在索引中仅包含product_attributes.elements和product_attributes.resistance字段的标量值。

use inventory
db.products_catalog.createIndex(
  { "$**" : 1 },
  {
    "wildcardProjection" : {
      "product_attributes.elements" : 1,
      "product_attributes.resistance" : 1
    }
  }
)

While the key pattern "$**" covers all fields in the document, the wildcardProjection field limits the index to only the included fields. 虽然键模式"$**"涵盖文档中的所有字段，但wildcardProjection字段将索引限制为仅包含的字段。For complete documentation on wildcardProjection, see Options for wildcard indexes.有关wildcardProjection的完整文档，请参阅wildcard索引选项。

If a field is a nested document or array, the wildcard index recurses into the document/array and indexes all scalar fields in the document/array.如果字段是嵌套文档或数组，通配符索引将递归到文档/数组，并为文档/数组中的所有标量字段编制索引。

The created index can support queries on any scalar field included in the wildcardProjection:创建的索引可以支持对wildcardProjection中包含的任何标量字段的查询：

db.products_catalog.find( { "product_attributes.elements" : { $eq: "Water" } } )
db.products_catalog.find( { "product_attributes.resistance" : "Bludgeoning" } )

Omit Specific Fields from Wildcard Index Coverage从通配符索引覆盖范围中省略特定字段

Consider a collection products_catalog where documents may contain a product_attributes field. 考虑一个集合products_catalog，其中的文档可能包含product_attributes字段。The product_attributes field can contain arbitrary nested fields, including embedded documents and arrays:product_attributes字段可以包含任意嵌套字段，包括嵌入的文档和数组：

{
  "_id" : ObjectId("5c1d358bf383fbee028aea0b"),
  "product_name" : "Blaster Gauntlet",
  "product_attributes" : {
     "price" : {
       "cost" : 299.99
       "currency" : USD
     }
     ...
  }
},
{
  "_id" : ObjectId("5c1d358bf383fbee028aea0c"),
  "product_name" : "Super Suit",
  "product_attributes" : {
     "superFlight" : true,
     "resistance" : [ "Bludgeoning", "Piercing", "Slashing" ]
     ...
  },
}

The following operation creates a wildcard index and uses the wildcardProjection document to index all scalar fields for each document in the collection, excluding the product_attributes.elements and product_attributes.resistance fields:以下操作创建通配符索引，并使用wildcardProjection文档为集合中每个文档的所有标量字段编制索引，不包括product_attributes.elements和product_attributes.resistance字段：

use inventory
db.products_catalog.createIndex(
  { "$**" : 1 },
  {
    "wildcardProjection" : {
      "product_attributes.elements" : 0,
      "product_attributes.resistance" : 0
    }
  }
)

While the key pattern "$**" covers all fields in the document, the wildcardProjection field excludes the specified fields from the index. 虽然键模式"$**"涵盖了文档中的所有字段，但wildcardProjection字段从索引中排除了指定的字段。For complete documentation on wildcardProjection, see Options for wildcard indexes.有关wildcardProjection的完整文档，请参阅wildcard索引选项。

If a field is a nested document or array, the wildcard index recurses into the document/array and indexes all scalar fields in the document/array.如果字段是嵌套文档或数组，通配符索引将递归到文档/数组，并为文档/数组中的所有标量字段编制索引。

The created index can support queries on any scalar field exceptthose excluded by wildcardProjection:创建的索引可以支持对任何标量字段的查询，wildcardProjection排除的字段除外：

db.products_catalog.find( { "product_attributes.maxSpeed" : { $gt: 25 } } )
db.products_catalog.find( { "product_attributes.superStrength" : true } )