Query Optimization查询优化

Create Indexes to Support Queries创建索引以支持查询

Indexes store values from individual fields or sets of fields from a collection in a separate data structure. In read operations, they allow MongoDB to search in the index to identify relevant documents instead of the entire collection. In write operations, MongoDB must both write the change to the collection and update the index.索引将单个字段或集合中的字段集的值存储在单独的数据结构中。在读取操作中，它们允许MongoDB在索引中搜索以识别相关文档，而不是整个集合。在写操作中，MongoDB必须将更改写入集合并更新索引。

Create indexes for commonly issued queries. If a query searches multiple fields, create a compound index.为常见查询创建索引。如果查询搜索多个字段，请创建复合索引。

For example, consider the following query on the type field in the inventory collection:例如，考虑对inventory集合中的type字段进行以下查询：

let typeValue = <someUserInput>;
db.inventory.find( { type: typeValue } );

To improve performance for this query, add an index to the inventory collection on the type field. 为了提高此查询的性能，请在inventory集合中的type字段添加索引。[1] In mongosh, create indexes using the db.collection.createIndex() method:在mongosh中，使用db.collection.createIndex()方法创建索引：

db.inventory.createIndex( { type: 1 } )

To analyze query performance, see Interpret Explain Plan Results.要分析查询性能，请参阅解释计划结果。

Create Selective Queries创建选择性查询

Query selectivity refers to how well the query predicate filters out documents in a collection. Query selectivity determines whether queries can use indexes effectively.查询选择性是指查询谓词筛选集合中文档的能力。查询选择性决定了查询是否可以有效地使用索引。

More selective queries match a smaller percentage of documents. For instance, an equality match on the unique _id field is highly selective as it can match at most one document.更具选择性的查询匹配的文档比例较小。例如，唯一_id字段上的相等匹配具有高度选择性，因为它最多只能匹配一个文档。

Less selective queries match a larger percentage of documents and cannot use indexes effectively.选择性较低的查询会匹配更大比例的文档，并且无法有效地使用索引。

For instance, the inequality operators $nin and $ne are not very selective since they often match a large portion of the index. 例如，不等式运算符$nin和$ne不是很有选择性，因为它们通常与指数的很大一部分相匹配。As a result, in many cases, a $nin or $ne query with an index may perform no better than a $nin or $ne query that must scan all documents in a collection.因此，在许多情况下，带有索引的$nin或$ne查询的性能可能不如必须扫描集合中所有文档的$nin和$ne查询。

The selectivity of regular expressions depends on the expressions themselves. For details, see regular expression and index use.正则表达式的选择性取决于表达式本身。有关详细信息，请参阅正则表达式和索引使用。

Project Only Necessary Data仅项目所需数据

When you need a subset of fields from documents, you can improve performance by returning only the fields you need. Projections reduce network traffic and processing time.当您需要文档中的字段子集时，可以通过仅返回所需的字段来提高性能。预测减少了网络流量和处理时间。

For example, if your query to the posts collection needs only the timestamp, title, author, and abstract fields, specify those fields in the projection:例如，如果您对posts集合的查询只需要timestamp、title、author和abstract字段，请在投影中指定这些字段：

db.posts.find(
   {},
   { timestamp : 1, title : 1, author : 1, abstract : 1}
).sort( { timestamp : -1 } )

When you use a $project aggregation stage it should typically be the last stage in your pipeline, used to specify which fields to return to the client.当您使用$project聚合阶段时，它通常应该是管道中的最后一个阶段，用于指定要返回给客户端的字段。

Using a $project stage at the beginning or middle of a pipeline to reduce the number of fields passed to subsequent pipeline stages is unlikely to improve performance, because the database performs this optimization automatically.在管道的开始或中间使用$project阶段来减少传递给后续管道阶段的字段数量不太可能提高性能，因为数据库会自动执行此优化。

For more information on using projections, see Project Fields to Return from Query.有关使用投影的更多信息，请参阅从查询返回的项目字段。

db.inventory.createIndex( { type: 1, _id: 1, price: 1, item: 1, expiryDate: 1} )

db.inventory.aggregate([
  { $match: {type: "food", expiryDate: { $gt: ISODate("2025-07-10T00:00:00Z") }}},
  { $sort: { item: 1 }},
  { $project: { _id: 1, price: 1} }
])

Limit Query Results限制查询结果

MongoDB cursors return results in batches. If you know the number of results you want, specify that value in the limit() method. Limiting results reduces the demand on network resources.MongoDB游标分批返回结果。如果你知道你想要的结果数量，在limit()方法中指定该值。限制结果减少了对网络资源的需求。

Generally, limiting results is most useful when results are sorted so you know which documents will be returned. For example, if you need only 10 results from your query to the posts collection, run the following query:通常，当对结果进行排序时，限制结果是最有用的，这样您就知道将返回哪些文档。例如，如果您对posts集合的查询只需要10个结果，请运行以下查询：

db.posts.find().sort( { timestamp : -1 } ).limit(10)

For more information on limiting results, see limit().有关限制结果的更多信息，请参阅limit()。

Use Index Hints使用索引提示

The query optimizer typically selects the optimal index for a specific operation. However, you can force MongoDB to use a specific index using the hint() method. 查询优化器通常为特定操作选择最佳索引。但是，您可以使用hint()方法强制MongoDB使用特定的索引。Use hint() to support performance testing or when you are querying a field that appears in several indexes to guarantee that MongoDB uses the correct index.使用hint()支持性能测试，或者当您查询出现在多个索引中的字段时，以确保MongoDB使用正确的索引。

Use Server-Side Operations使用服务器端操作

Use MongoDB's $inc operator to increment or decrement values in documents. 使用MongoDB的$inc运算符来增加或减少文档中的值。The operator increments the value of the field on the server side, as an alternative to selecting a document, making simple modifications in the client, and then writing the entire document to the server. 运算符在服务器端递增字段的值，作为选择文档、在客户端进行简单修改，然后将整个文档写入服务器的替代方法。The $inc operator can also help avoid race conditions that occur when two application instances query for a document, manually increment a field, and save the entire document back at the same time.$inc运算符还可以帮助避免两个应用程序实例查询文档、手动增加字段并同时将整个文档保存回时出现的竞争条件。

Run Covered Queries运行覆盖查询

A covered query is a query that can be satisfied entirely using an index and does not have to examine any documents. An index covers a query when all of the following apply:覆盖查询是一种可以完全使用索引满足的查询，不必检查任何文档。当以下所有条件都适用时，索引会覆盖查询：

• All the fields in the query (both as specified by the application and as needed internally such as for sharding purposes) are part of an index.查询中的所有字段（包括应用程序指定的字段和内部需要的字段，例如用于分片的字段）都是索引的一部分。
• All the fields returned in the results are in the same index.结果中返回的所有字段都在同一索引中。

• No fields in the query are equal to null. For example, the following query predicates cannot result in covered queries:查询中没有字段等于null。例如，以下查询谓词不能导致覆盖查询：

  • { "field": null }
  • { "field": { $eq: null } }

db.inventory.createIndex( { type: 1, item: 1 } )

db.inventory.find(
   { type: "food", item:/^c/ },
   { item: 1, _id: 0 }
)

db.userdata.insertOne(
   { _id: 1, user: { login: "tester" } }
)

db.userdata.createIndex(
   { "user.login": 1 }
)

db.userdata.find(
   { "user.login": "tester" },
   { "user.login": 1, _id: 0 }
)