Query Optimization查询优化

Create an Index to Support Read Operations创建索引以支持读取操作

If your application queries a collection on a particular field or set of fields, then an index on the queried field or a compound index on the set of fields can prevent the query from scanning the whole collection to find and return the query results. 如果应用程序查询某个特定字段或字段集的集合，则查询字段上的索引或字段集上的复合索引会阻止查询扫描整个集合以查找并返回查询结果。For more information about indexes, see the complete documentation of indexes in MongoDB.有关索引的更多信息，请参阅MongoDB中索引的完整文档。

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

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

To analyze the performance of the query with an index, see Analyze Query Performance.要使用索引分析查询的性能，请参阅分析查询性能。

In addition to optimizing read operations, indexes can support sort operations and allow for a more efficient storage utilization. 除了优化读取操作外，索引还可以支持排序操作，并允许更高效的存储利用率。See db.collection.createIndex() and Indexes for more information about index creation.有关索引创建的详细信息，请参阅db.collection.createIndex()和索引。

Query Selectivity查询选择性

Query selectivity refers to how well the query predicate excludes or filters out documents in a collection. 查询选择性是指查询谓词排除或筛选集合中文档的程度。Query selectivity can determine whether or not queries can use indexes effectively or even use indexes at all.查询选择性可以确定查询是否可以有效地使用索引，甚至可以完全使用索引。

More selective queries match a smaller percentage of documents. 更有选择性的查询与较小百分比的文档匹配。For instance, an equality match on the unique _id field is highly selective as it can match at most one document.例如，唯一性_id字段上的相等匹配是高度选择性的，因为它最多可以匹配一个文档。

Less selective queries match a larger percentage of documents. 选择性较低的查询与较大百分比的文档匹配。Less selective queries cannot use indexes effectively or even at all.选择性较低的查询无法有效使用索引，甚至根本无法使用索引。

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 $ne query that must scan all documents in a collection.因此，在许多情况下，带索引的$nin或$ne查询的性能可能并不比必须扫描集合中所有文档的$nin或$ne搜索好。

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

Covered Query涵盖的查询

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:覆盖查询是指可以完全使用索引来满足的查询，并且不必检查任何文档。当以下所有条件都适用时，索引将覆盖查询：

• all the fields in the query are part of an index, and查询中的所有字段都是索引的一部分，并且
• 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 (i.e. {"field" : null} or {"field" : {$eq : null}} ).查询中没有字段等于null（即{"field" : null}或{"field" : {$eq : null}}）。

For example, a collection inventory has the following index on the type and item fields:例如，集合inventory在type字段和item字段上具有以下索引：

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

This index will cover the following operation which queries on the type and item fields and returns only the item field:此索引将涵盖以下查询type和item字段并仅返回item字段的操作：

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

For the specified index to cover the query, the projection document must explicitly specify _id: 0 to exclude the _id field from the result since the index does not include the _id field.对于覆盖查询的指定索引，投影文档必须显式指定_id:0以从结果中排除_id字段，因为索引不包括_id字段。

{ _id: 1, user: { login: "tester" } }

{ "user.login": 1 }

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