Database Manual / Reference / mongosh Methods / Collections

db.collection.updateMany() (mongosh method方法)

Definition定义

db.collection.updateMany(filter, update, options)
Updates all documents that match the specified filter for a collection.更新与集合的指定筛选器匹配的所有文档。

Compatibility兼容性

This method is available in deployments hosted in the following environments:此方法在以下环境中托管的部署中可用：

  • MongoDB Atlas: The fully managed service for MongoDB deployments in the cloud：云中MongoDB部署的完全托管服务

Note

This command is supported in all MongoDB Atlas clusters. 所有MongoDB Atlas集群都支持此命令。For information on Atlas support for all commands, see Unsupported Commands.有关Atlas支持所有命令的信息，请参阅不支持的命令。

  • MongoDB Enterprise: The subscription-based, self-managed version of MongoDB：MongoDB的基于订阅的自我管理版本
  • MongoDB Community: The source-available, free-to-use, and self-managed version of MongoDB：MongoDB的源代码可用、免费使用和自我管理版本

Syntax语法

The updateMany() method has the following form:updateMany()方法具有以下形式：

db.collection.updateMany(
   <filter>,
   <update>,
   {
     upsert: <boolean>,
     writeConcern: <document>,
     collation: <document>,
     arrayFilters: [ <filterdocument1>, ... ],
     hint:  <document|string>,
     let: <document>,
     maxTimeMS: <int>,
     bypassDocumentValidation: <boolean>
   }
)

Parameters参数

The updateMany() method takes the following parameters:updateMany()方法接受以下参数：

Parameter参数Type类型Description描述
filterdocument文档

The selection criteria for the update. The same query selectors as in the find() method are available.更新的选择标准。可以使用与find()方法中相同的查询选择器。

Specify an empty document { } to update all documents in the collection.指定一个空文档{ }以更新集合中的所有文档。

updatedocument or pipeline文件或管道

The modifications to apply. Can be one of the following:要应用的修改。可以是以下之一：

Update document更新文档

Contains only update operator expressions.仅包含更新运算符表达式。

For more information, see Update with an Update Operator Expressions Document有关详细信息，请参阅使用更新运算符表达式文档进行更新

Aggregation pipeline聚合管道

Contains only the following aggregation stages:仅包含以下聚合阶段：

For more information, see Update with an Aggregation Pipeline.有关更多信息，请参阅使用聚合管道更新。

To update with a replacement document, see db.collection.replaceOne().要使用替换文档进行更新，请参阅db.collection.replaceOne()。

upsertboolean布尔值

Optional. 可选。When true, updateMany() either:如果为true，updateMany()：

  • Creates a new document if no documents match the filter. For more details see upsert behavior.如果没有匹配filter的文档，则创建新文档。有关更多详细信息，请参阅upsert行为。
  • Updates documents that match the filter.更新与filter匹配的文档。

To avoid multiple upserts, ensure that the filter fields are uniquely indexed.为了避免多个异常，请确保filter字段具有唯一索引。

Defaults to false.默认为false。

writeConcerndocument文档

Optional. 可选。A document expressing the write concern. Omit to use the default write concern.表达写入关注的文件。省略使用默认写入关注。

Do not explicitly set the write concern for the operation if run in a transaction. 如果在事务中运行，则不要显式设置操作的写入关注。To use write concern with transactions, see Transactions and Write Concern.要对事务使用写关注，请参阅事务和写关注。

collationdocument文档

Optional.可选。

Specifies the collation to use for the operation.指定用于操作的排序规则。

Collation allows users to specify language-specific rules for string comparison, such as rules for lettercase and accent marks.排序规则允许用户为字符串比较指定特定于语言的规则，例如字母大小写和重音标记的规则。

The collation option has the following syntax:排序规则选项具有以下语法：

collation: {
   locale: <string>,
   caseLevel: <boolean>,
   caseFirst: <string>,
   strength: <int>,
   numericOrdering: <boolean>,
   alternate: <string>,
   maxVariable: <string>,
   backwards: <boolean>
}

When specifying collation, the locale field is mandatory; all other collation fields are optional. For descriptions of the fields, see Collation Document.指定排序规则时，locale段是必填的；所有其他排序字段都是可选的。有关字段的描述，请参阅排序规则文档。

If the collation is unspecified but the collection has a default collation (see db.createCollection()), the operation uses the collation specified for the collection.如果未指定排序规则，但集合具有默认排序规则（请参阅db.createCollection()），则操作将使用为集合指定的排序规则。

If no collation is specified for the collection or for the operations, MongoDB uses the simple binary comparison used in prior versions for string comparisons.如果没有为集合或操作指定排序规则，MongoDB将使用以前版本中用于字符串比较的简单二进制比较。

You cannot specify multiple collations for an operation. For example, you cannot specify different collations per field, or if performing a find with a sort, you cannot use one collation for the find and another for the sort.不能为操作指定多个排序规则。例如，您不能为每个字段指定不同的排序规则，或者如果使用排序执行查找，则不能对查找使用一个排序规则，对排序使用另一个。

arrayFiltersarray数组

Optional. 可选。An array of filter documents that determine which array elements to modify for an update operation on an array field.一组筛选文档，用于确定在数组字段上进行更新操作时要修改哪些数组元素。

In the update document, use the $[<identifier>] filtered positional operator to define an identifier, which you then reference in the array filter documents. 在更新文档中，使用$[<identifier>]筛选位置运算符定义一个标识符，然后在数组筛选文档中引用该标识符。You cannot have an array filter document for an identifier if the identifier is not included in the update document.如果标识符未包含在更新文档中，则无法为标识符创建数组筛选器文档。

The <identifier> must begin with a lowercase letter and contain only alphanumeric characters.<identifier>必须以小写字母开头，并且只能包含字母数字字符。

You can include the same identifier multiple times in the update document; however, for each distinct identifier ($[identifier]) in the update document, you must specify exactly one corresponding array filter document. 您可以在更新文档中多次包含相同的标识符；但是，对于更新文档中的每个不同标识符（$[identifier]），您必须指定一个相应的数组筛选器文档。That is, you cannot specify multiple array filter documents for the same identifier. For example, if the update statement includes the identifier x (possibly multiple times), you cannot specify the following for arrayFilters that includes 2 separate filter documents for x:也就是说，不能为同一标识符指定多个数组筛选器文档。例如，如果update语句包含标识符x（可能多次），则不能为包含2个单独的x筛选文档的arrayFilters指定以下内容：

// INVALID

[
  { "x.a": { $gt: 85 } },
  { "x.b": { $gt: 80 } }
]

However, you can specify compound conditions on the same identifier in a single filter document, such as in the following examples:但是，您可以在单个筛选器文档中为同一标识符指定复合条件，例如以下示例：

// Example 1
[
  { $or: [{"x.a": {$gt: 85}}, {"x.b": {$gt: 80}}] }
]
// Example 2
[
  { $and: [{"x.a": {$gt: 85}}, {"x.b": {$gt: 80}}] }
]
// Example 3
[
  { "x.a": { $gt: 85 }, "x.b": { $gt: 80 } }
]

For examples, see Specify arrayFilters for an Array Update Operations.有关示例，请参阅为数组更新操作指定arrayFilters。

hintDocument or string文档或字符串

Optional. 可选。A document or string that specifies the index to use to support the query predicate.指定用于支持查询谓词的索引的文档或字符串。

The option can take an index specification document or the index name string.该选项可以采用索引规范文档或索引名称字符串。

If you specify an index that does not exist, the operation errors.如果指定的索引不存在，则操作会出错。

For an example, see Specify hint for Update Operations.例如，请参阅指定更新操作的hint。

letDocument文档

Optional.可选。

Specifies a document with a list of variables. This allows you to improve command readability by separating the variables from the query text.指定一个包含变量列表的文档。这允许您通过将变量与查询文本分离来提高命令的可读性。

The document syntax is:文档语法为：

{
  <variable_name_1>: <expression_1>,
  ...,
  <variable_name_n>: <expression_n>
}

The variable is set to the value returned by the expression, and cannot be changed afterwards.变量设置为表达式返回的值，之后不能更改。

To access the value of a variable in the command, use the double dollar sign prefix ($$) together with your variable name in the form $$<variable_name>. For example: $$targetTotal.要在命令中访问变量的值，请使用双美元符号前缀（$$）和变量名，格式为$$<variable_name>。例如：$$targetTotal。

To use a variable to filter results, you must access the variable within the $expr operator.要使用变量筛选结果，您必须在$expr运算符中访问该变量。

For a complete example using let and variables, see Update with let Variables.有关使用let和变量的完整示例，请参阅使用let变量更新。

maxTimeMSinteger整数

Optional. 可选。Specifies the time limit in milliseconds for the update operation to run before timing out.指定在超时之前运行更新操作的时间限制（以毫秒为单位）。

bypassDocumentValidationboolean布尔值

Optional. 可选。Enables insert to bypass schema validation during the operation. 启用插入以在操作期间绕过架构验证。This lets you insert documents that do not meet the validation requirements.这允许您插入不符合验证要求的文档。

Returns值

The method returns a document that contains:该方法返回一个文档，其中包含：

  • A boolean acknowledged as true if the operation ran with write concern or false if write concern was disabled如果操作在写入关注下运行，则布尔值acknowledged为true，如果写入关注被禁用，则确认为false
  • matchedCount containing the number of matched documents包含匹配文档的数量
  • modifiedCount containing the number of modified documents包含已修改文档的数量
  • upsertedId containing the _id for the upserted document包含已更新文档的_id
  • upsertedCount containing the number of upserted documents包含被打乱的文档数量

Access Control访问控制

On deployments running with authorization, the user must have access that includes the following privileges:在authorization运行的部署中，用户必须具有包括以下权限的访问权限：

  • update action on the specified collection(s).对指定集合执行更新操作。
  • find action on the specified collection(s).指定集合上的find操作。
  • insert action on the specified collection(s) if the operation results in an upsert.如果操作导致upsert，请在指定的集合上insert操作。

The built-in role readWrite provides the required privileges.内置角色readWrite提供了所需的权限。

Behavior行为

updateMany() finds all documents in the collection that match the filter and applies modifications specified by the update parameter.查找集合中与filter匹配的所有文档，并应用update参数指定的修改。

updateMany() modifies each document individually. Each document write is an atomic operation, but updateMany() as a whole is not atomic. updateMany()分别修改每个文档。每次文档写入都是一个原子操作，但updateMany()作为一个整体不是原子操作。If your use case requires atomicity of writes to multiple documents, use Transactions.如果用例要求对多个文档的写入具有原子性，请使用事务。

If a single document update fails, all document updates written before the failure are retained, but any remaining matching documents are not updated. 如果单个文档更新失败，则保留失败前写入的所有文档更新，但不更新任何剩余的匹配文档。For details on this behavior, see Multi-Update Failures.有关此行为的详细信息，请参阅多次更新失败。

Tip

Sharded Collections for more information about updateMany() behavior in sharded collections.分片集合了解有关分片集合中updateMany()行为的更多信息。

Limitations局限性

  • updateMany() should only be used for idempotent operations.updateMany()只应用于幂等运算。

Upsert

If upsert: true and no documents match the filter, db.collection.updateMany() creates a new document based on the filter and update parameters.如果upsert: true且没有文档与filter匹配，db.collection.updateMany()将根据筛选器和更新参数创建一个新文档。

If you specify upsert: true on a sharded collection, you must include the full shard key in the filter. 如果在分片集合上指定upsert: true，则必须在filter中包含完整的分片键。For additional db.collection.updateMany() behavior, see Sharded Collections.有关db.collection.updateMany()的其他行为，请参阅分片集合。

See Update Multiple Documents with Upsert.请参阅使用Upsert更新多个文档。

Update with an Update Operator Expressions Document使用更新运算符表达式文档进行更新

For the modification specification, the db.collection.updateMany() method can accept a document that only contains update operator expressions to perform.对于修改规范，db.collection.updateMany()方法可以接受只包含要执行的更新运算符表达式的文档。

For example:例如：

db.collection.updateMany(
   <query>,
   { $set: { status: "D" }, $inc: { quantity: 2 } },
   ...
)

Update with an Aggregation Pipeline使用聚合管道进行更新

The db.collection.updateMany() method can accept an aggregation pipeline [ <stage1>, <stage2>, ... ] that specifies the modifications to perform. db.collection.updateMany()方法可以接受指定要执行的修改的聚合管道[ <stage1>, <stage2>, ... ]。The pipeline can consist of the following stages:管道可包括以下阶段：

Using the aggregation pipeline allows for a more expressive update statement, such as expressing conditional updates based on current field values or updating one field using the value of another field(s).使用聚合管道允许更具表现力的更新语句，例如基于当前字段值表示条件更新，或使用另一个字段的值更新一个字段。

For example:例如：

db.collection.updateMany(
   <query>,
   [
      { $set: { status: "Modified", comments: [ "$misc1", "$misc2" ] } },
      { $unset: [ "misc1", "misc2" ] }
   ]
   ...
)

Note

In this pipeline, $set and $unset are aggregation stages, as opposed to update operators. 在这个管道中，$set和$unset是聚合阶段，而不是更新运算符。The aggregation stages $set and $unset add new fields to documents and do not modify existing field values.聚合阶段$set和$unset向文档添加新字段，而不修改现有字段值。

For more information on the update operators, see $set and $unset.有关更新运算符的更多信息，请参阅$set和$unset。

For examples, see Update with Aggregation Pipeline.有关示例，请参阅使用聚合管道进行更新。

Capped Collections封顶集合

If an update operation changes the document size, the operation will fail.如果更新操作更改了文档大小，则操作将失败。

Time Series Collections时间序列集合

The updateMany() method is available for time series collections starting in MongoDB 5.1.updateMany()方法可用于MongoDB 5.1中开始的时间序列集合。

Update commands must meet the following requirements:更新命令必须满足以下要求：

  • You can only match on the metaField field value.您只能匹配metaField字段值。
  • You can only modify the metaField field value.您只能修改metaField字段值。
  • Your update document can only contain update operator expressions.更新文档只能包含更新运算符表达式。
  • Your update command must not limit the number of documents to be updated. 更新命令不得限制要更新的文档数量。Set multi: true or use the updateMany() method.设置multi:true或使用updateMany()方法。
  • Your update command must not set upsert: true.更新命令不得设置upsert:true。

Sharded Collections分片化集合

updateMany() exhibits the following behaviors when used with sharded collections:当与分片集合一起使用时，表现出以下行为：

  • updateMany() operations that include upsert: true must include the full shard key in the filter.包含upsert: true的updateMany()操作必须在筛选器中包含完整的分片键。
  • If you attempt to run updateMany() during a Range Migration or a shard key value update, the operation can miss documents in some scenarios. 如果你试图在范围迁移或分片键值更新期间运行updateMany()，在某些情况下，该操作可能会错过文档。To ensure all documents are updated, use idempotent updates and rerun the command until no further updates are applied. 为确保所有文档都已更新，请使用幂等更新并重新运行该命令，直到不再应用任何更新。For more information on idempotent updates with updateMany(), see Idempotent Updates.有关使用updateMany()进行幂等更新的更多信息，请参阅幂等更新。
  • If updateMany() is run outside a transaction, operations that target more than one shard broadcast the operation to all shards in the cluster.如果updateMany()在事务外部运行，则针对多个分片的操作会将操作广播到集群中的所有分片。
  • If updateMany() is run inside a transaction, operations that target more than one shard only target the relevant shards.如果updateMany()在事务中运行，则针对多个分片的操作只针对相关分片。

Explainability可解释性

updateMany() is not compatible with db.collection.explain().与db.collection.explain()不兼容。

Transactions事务

db.collection.updateMany() can be used inside distributed transactions.可以在分布式事务中使用。

Important

In most cases, a distributed transaction incurs a greater performance cost over single document writes, and the availability of distributed transactions should not be a replacement for effective schema design. 在大多数情况下，分布式事务比单文档写入产生更大的性能成本，分布式事务的可用性不应取代有效的模式设计。For many scenarios, the denormalized data model (embedded documents and arrays) will continue to be optimal for your data and use cases. That is, for many scenarios, modeling your data appropriately will minimize the need for distributed transactions.对于许多场景，非规范化数据模型（嵌入式文档和数组）将继续是数据和用例的最佳选择。也就是说，对于许多场景，适当地对数据进行建模将最大限度地减少对分布式事务的需求。

For additional transactions usage considerations (such as runtime limit and oplog size limit), see also Production Considerations.有关其他事务使用注意事项（如运行时限制和oplog大小限制），另请参阅生产注意事项。

Upsert within Transactions事务中的失误

You can create collections and indexes inside a distributed transaction if the transaction is not a cross-shard write transaction.如果分布式事务不是跨分片写入事务，则可以在该事务内创建集合和索引。

db.collection.updateMany() with upsert: true can be run on an existing collection or a non-existing collection. If run on a non-existing collection, the operation creates the collection.db.collection.updateMany()和upsert: true可以在现有集合或不存在的集合上运行。如果在不存在的集合上运行，则该操作将创建该集合。

Tip

Create Collections and Indexes in a Transaction在事务中创建集合和索引

Write Concerns and Transactions撰写入关注和事务

Do not explicitly set the write concern for the operation if run in a transaction. To use write concern with transactions, see Transactions and Write Concern.如果在事务中运行，则不要显式设置操作的写入关注。要对事务使用写关注，请参阅事务和写关注。

Oplog Entries操作日志条目

updateMany() adds an entry to the oplog (operations log) for each successfully updated document. updateMany()为每个成功更新的文档在oplog（操作日志）中添加一个条目。If no documents are updated, updateMany() does not add entries to the oplog.如果没有更新文档，updateMany()不会向oplog添加条目。

Examples示例

Idempotent Updates幂等更新

The following example demonstrates an idempotent update with updateMany():以下示例演示了使用updateMany()进行幂等更新：

A company is giving a $1,000 raise to all employees earning less than $100,000.一家公司为所有收入低于10万美元的员工加薪1000美元。

Consider an employees collection with the following documents:考虑一个包含以下文档的employees集合：

db.employees.insertMany( [
   { _id: 1, name: "Rob", salary: 37000 },
   { _id: 2, name: "Trish", salary: 65000 },
   { _id: 3, name: "Zeke", salary: 99999 },
   { _id: 4, name: "Mary", salary: 200000 }
] )

The following command matches all employees who earn less than $100,000 and have not received a raise, increments those salaries by $1,000, and sets raiseApplied to true:以下命令匹配所有收入低于100000美元且未加薪的员工，将这些工资增加1000美元，并将raiseApplied设置为true：

db.employees.updateMany(
   { salary: { $lt: 100000 }, raiseApplied: { $ne: true } },
   { $inc: { salary: 1000 }, $set: { raiseApplied: true } }
)

updateMany() modifies the matching employee documents individually. 单独修改匹配的员工文档。The individual document updates are atomic operations, but the updateMany() operation as a whole is not atomic.单个文档更新是原子操作，但updateMany()操作作为一个整体不是原子操作。

If the operation fails to update all matched documents, you can safely rerun an idempotent command until no additional documents match the specified filter. In this case, each document's salary field is only updated one time regardless of how many times it is retried because the command is idempotent.如果操作未能更新所有匹配的文档，则可以安全地重新运行幂等命令，直到没有其他文档与指定的筛选器匹配为止。在这种情况下，无论重试多少次，每个文档的salary字段都只更新一次，因为该命令是幂等的。

After all eligible employees have received their raises, you can remove the raiseApplied field with the following command:在所有符合条件的员工都收到加薪后，您可以使用以下命令删除raiseApplied字段：

db.employees.updateMany(
   { },
   { $unset: { raiseApplied: 1 } }
)

Update Multiple Documents更新多个文档

The restaurant collection contains the following documents:restaurant集合包含以下文件：

db.restaurant.insertMany( [
   { _id: 1, name: "Central Perk Cafe", violations: 3 },
   { _id: 2, name: "Rock A Feller Bar and Grill", violations: 2 },
   { _id: 3, name: "Empire State Sub", violations: 5 },
   { _id: 4, name: "Pizza Rat's Pizzaria", violations: 8 },
] )

The following operation updates all documents where violations are greater than 4 and $set a flag for review:以下操作将更新所有violations（违规行为）大于4并设置Review（审查）标志的文档：

try {
   db.restaurant.updateMany(
      { violations: { $gt: 4 } },
      { $set: { "Review" : true } }
   );
} catch (e) {
   print(e);
}

The operation returns:操作返回：

{ "acknowledged" : true, "matchedCount" : 2, "modifiedCount" : 2 }

The collection now contains the following documents:该集合现在包含以下文档：

{ _id: 1, name: "Central Perk Cafe", violations: 3 }
{ _id: 2, name: "Rock A Feller Bar and Grill", violations: 2 }
{ _id: 3, name: "Empire State Sub", violations: 5, Review: true }
{ _id: 4, name: "Pizza Rat's Pizzaria", violations: 8, Review: true }

If no matches were found, the operation instead returns:如果没有找到匹配项，则操作将返回：

{ "acknowledged" : true, "matchedCount" : 0, "modifiedCount" : 0 }

Setting upsert: true would insert a document if no match was found.设置upsert: true将在未找到匹配项时插入文档。

Update with Aggregation Pipeline使用聚合管道进行更新

The db.collection.updateMany() can use an aggregation pipeline for the update. The pipeline can consist of the following stages:db.collection.updateMany()可以使用聚合管道进行更新。管道可包括以下阶段：

Using the aggregation pipeline allows for a more expressive update statement, such as expressing conditional updates based on current field values or updating one field using the value of another field(s).使用聚合管道允许更具表现力的更新语句，例如基于当前字段值表示条件更新，或使用另一个字段的值更新一个字段。

Example 1: Update with Aggregation Pipeline Using Existing Fields示例1：使用现有字段使用聚合管道进行更新

The following examples uses the aggregation pipeline to modify a field using the values of the other fields in the document.以下示例使用聚合管道使用文档中其他字段的值修改字段。

Create a students collection with the following documents:使用以下文档创建students集合：

db.students.insertMany( [
   { _id: 1, student: "Skye", points: 75, commentsSemester1: "great at math", commentsSemester2: "loses temper", lastUpdate: ISODate("2019-01-01T00:00:00Z") },
   { _id: 2, students: "Elizabeth", points: 60, commentsSemester1: "well behaved", commentsSemester2: "needs improvement", lastUpdate: ISODate("2019-01-01T00:00:00Z") }
] )

Assume that instead of separate commentsSemester1 and commentsSemester2 fields, you want to gather these into a new comments field. The following update operation uses an aggregation pipeline to:假设您不想将commentsSemester1和commentsSemester2字段分开，而是想将它们集合到一个新的comments字段中。以下更新操作使用聚合管道来：

  • add the new comments field and set the lastUpdate field.添加新的comments字段并设置lastUpdate字段。
  • remove the commentsSemester1 and commentsSemester2 fields for all documents in the collection.删除集合中所有文档的commentsSemester1和commentsSemester2字段。
db.students.updateMany(
   { },
   [
      { $set: { comments: [ "$commentsSemester1", "$commentsSemester2" ], lastUpdate: "$$NOW" } },
      { $unset: [ "commentsSemester1", "commentsSemester2" ] }
   ]
)

Note

In this pipeline, $set and $unset are aggregation stages, as opposed to update operators. 在这个管道中，$set和$unset是聚合阶段，而不是更新运算符。The aggregation stages $set and $unset add new fields to documents and do not modify existing field values.聚合阶段$set和$unset向文档添加新字段，而不修改现有字段值。

For more information on the update operators, see $set and $unset.有关更新运算符的更多信息，请参阅$set和$unset。

First Stage第一阶段

The $set stage:$set阶段：

  • creates a new array field comments whose elements are the current content of the commentsSemester1 and commentsSemester2 fields and创建一个新的数组字段comments，其元素是commentsSemester1和commentsSemester2字段的当前内容，以及
  • sets the field lastUpdate to the value of the aggregation variable NOW. 将字段lastUpdate设置为聚合变量NOW的值。The aggregation variable NOW resolves to the current datetime value and remains the same throughout the pipeline. 聚合变量NOW解析为当前日期时间值，并在整个管道中保持不变。To access aggregation variables, prefix the variable with double dollar signs $$ and enclose in quotes.要访问聚合变量，请在变量前添加双美元符号$$并括在引号中。
Second Stage第二阶段
The $unset stage removes the commentsSemester1 and commentsSemester2 fields.$unset阶段删除commentsSemester1和commentsSemester2字段。

After the command, the collection contains the following documents:命令后，集合包含以下文档：

{ _id: 1, student: "Skye", status: "Modified", points: 75, lastUpdate: ISODate("2020-01-23T05:11:45.784Z"), comments: [ "great at math", "loses temper" ] }
{ _id: 2, student: "Elizabeth", status: "Modified", points: 60, lastUpdate: ISODate("2020-01-23T05:11:45.784Z"), comments: [ "well behaved", "needs improvement" ] }

Example 2: Update with Aggregation Pipeline Using Existing Fields Conditionally示例2：有条件地使用现有字段更新聚合管道

The aggregation pipeline allows the update to perform conditional updates based on the current field values as well as use current field values to calculate a separate field value.聚合管道允许更新基于当前字段值执行条件更新，并使用当前字段值计算单独的字段值。

For example, create a students3 collection with the following documents:例如，使用以下文档创建students3集合：

db.students3.insertMany( [
   { _id: 1, tests: [ 95, 92, 90 ], lastUpdate: ISODate("2019-01-01T00:00:00Z") },
   { _id: 2, tests: [ 94, 88, 90 ], lastUpdate: ISODate("2019-01-01T00:00:00Z") },
   { _id: 3, tests: [ 70, 75, 82 ], lastUpdate: ISODate("2019-01-01T00:00:00Z") }
] )

Using an aggregation pipeline, you can update the documents with the calculated grade average and letter grade.使用聚合管道，您可以使用计算出的平均成绩和字母成绩更新文档。

db.students3.updateMany(
   { },
   [
     { $set: { average : { $trunc: [ { $avg: "$tests" }, 0 ] } , lastUpdate: "$$NOW" } },
     { $set: { grade: { $switch: {
                           branches: [
                               { case: { $gte: [ "$average", 90 ] }, then: "A" },
                               { case: { $gte: [ "$average", 80 ] }, then: "B" },
                               { case: { $gte: [ "$average", 70 ] }, then: "C" },
                               { case: { $gte: [ "$average", 60 ] }, then: "D" }
                           ],
                           default: "F"
     } } } }
   ]
)

Note

In this pipeline, $set and $unset are aggregation stages, as opposed to update operators. 在这个管道中，$set和$unset是聚合阶段，而不是更新运算符。The aggregation stages $set and $unset add new fields to documents and do not modify existing field values.聚合阶段$set和$unset向文档添加新字段，而不修改现有字段值。

For more information on the update operators, see $set and $unset.有关更新运算符的更多信息，请参阅$set和$unset。

First Stage第一阶段

The $set stage:$set阶段：

  • calculates a new field average based on the average of the tests field. 基于tests字段的平均值计算新的字段average。See $avg for more information on the $avg aggregation operator and $trunc for more information on the $trunc truncate aggregation operator.有关$avg聚合运算符的更多信息，请参阅$avg；有关$trunc截断聚合运算符的详细信息，请参阅$trunc。
  • sets the field lastUpdate to the value of the aggregation variable NOW. 将字段lastUpdate设置为聚合变量NOW的值。The aggregation variable NOW resolves to the current datetime value and remains the same throughout the pipeline. 聚合变量NOW解析为当前日期时间值，并在整个管道中保持不变。To access aggregation variables, prefix the variable with double dollar signs $$ and enclose in quotes.要访问聚合变量，请在变量前添加双美元符号$$并括在引号中。
Second Stage第二阶段
The $set stage calculates a new field grade based on the average field calculated in the previous stage. $set阶段根据前一阶段计算的average字段计算新的字段grade。See $switch for more information on the $switch aggregation operator.有关$switch聚合运算符的更多信息，请参阅$switch。

After the command, the collection contains the following documents:命令后，集合包含以下文档：

{ _id: 1, tests: [ 95, 92, 90 ], lastUpdate: ISODate("2020-01-24T17:31:01.670Z"), average: 92, grade: "A" }
{ _id: 2, tests: [ 94, 88, 90 ], lastUpdate: ISODate("2020-01-24T17:31:01.670Z"), average: 90, grade: "A" }
{ _id: 3, tests: [ 70, 75, 82 ], lastUpdate: ISODate("2020-01-24T17:31:01.670Z"), average: 75, grade: "C" }

Tip

Updates with Aggregation Pipeline聚合管道的更新

Update Multiple Documents with Upsert使用Upert更新多个文档

The inspectors collection contains the following documents:inspectors集合的文件包括以下内容：

db.inspectors.insertMany( [
   { _id: 92412, inspector: "F. Drebin", Sector: 1, Patrolling: true },
   { _id: 92413, inspector: "J. Clouseau", Sector: 2, Patrolling: false },
   { _id: 92414, inspector: "J. Clouseau", Sector: 3, Patrolling: true },
   { _id: 92415, inspector: "R. Coltrane", Sector: 3, Patrolling: false }
] )

The following operation updates all documents with Sector greater than 4 and inspector equal to "R. Coltrane":以下操作将更新Sector（扇区）大于4且inspector等于"R. Coltrane"的所有文件：

try {
   db.inspectors.updateMany(
      { "Sector" : { $gt : 4 }, "inspector" : "R. Coltrane" },
      { $set: { "Patrolling" : false } },
      { upsert: true }
   );
} catch (e) {
   print(e);
}

The operation returns:操作返回：

{
   "acknowledged" : true,
   "matchedCount" : 0,
   "modifiedCount" : 0,
   "upsertedId" : ObjectId("56fc5dcb39ee682bdc609b02"),
   "upsertedCount": 1
}

The collection now contains the following documents:该集合现在包含以下文档：

{ _id: 92412, inspector: "F. Drebin", Sector: 1, Patrolling: true },
{ _id: 92413, inspector: "J. Clouseau", Sector: 2, Patrolling: false },
{ _id: 92414, inspector: "J. Clouseau", Sector: 3, Patrolling: true },
{ _id: 92415, inspector: "R. Coltrane", Sector: 3, Patrolling: false },
{ _id: ObjectId("56fc5dcb39ee682bdc609b02"), inspector: "R. Coltrane", Patrolling: false }

Since no documents matched the filter, and upsert was true, updateMany() inserted the document with a generated _id, the equality conditions from the filter, and the update modifiers.由于没有文档与filter匹配，并且upsert为true，updateMany()插入了具有生成的_id、filter的相等条件和更新修饰符的文档。

Update with Write Concern写入关注更新

Given a three member replica set, the following operation specifies a w of majority and wtimeout of 100:给定一个由三个成员组成的副本集，以下操作指定w为majority，wtimeout为100：

try {
   db.restaurant.updateMany(
       { "name" : "Pizza Rat's Pizzaria" },
       { $inc: { "violations" : 3}, $set: { "Closed" : true } },
       { w: "majority", wtimeout: 100 }
   );
} catch (e) {
   print(e);
}

If the acknowledgment takes longer than the wtimeout limit, the following exception is thrown:如果确认时间超过wtimeout限制，则抛出以下异常：

WriteConcernError({
   "code" : 64,
   "errmsg" : "waiting for replication timed out",
   "errInfo" : {
     "wtimeout" : true,
     "writeConcern" : {
       "w" : "majority",
       "wtimeout" : 100,
       "provenance" : "getLastErrorDefaults"
     }
   }
})

The following table explains the possible values of errInfo.writeConcern.provenance:下表解释了errInfo.writeConcern.provenance的可能值：

Provenance来源Description描述
clientSuppliedThe write concern was specified in the application.应用程序中指定了写入关注。
customDefaultThe write concern originated from a custom defined default value. 写入关注源于自定义的默认值。See setDefaultRWConcern.请参阅setDefaultRWConcern。
getLastErrorDefaultsThe write concern originated from the replica set's settings.getLastErrorDefaults field.写入关注源于副本集的settings.getLastErrorDefaults字段。
implicitDefaultThe write concern originated from the server in absence of all other write concern specifications.在没有所有其他写入关注规范的情况下，写入关注源自服务器。

Specify Collation指定排序规则

Collation allows users to specify language-specific rules for string comparison, such as rules for lettercase and accent marks.排序规则允许用户为字符串比较指定特定于语言的规则，例如字母大小写和重音标记的规则。

A collection myColl has the following documents:myColl集合有以下文件：

db.myColl.insertMany( [
   { _id: 1, category: "café", status: "A" },
   { _id: 2, category: "cafe", status: "a" },
   { _id: 3, category: "cafE", status: "a" }
] )

The following operation includes the collation option:以下操作包括排序规则选项：

db.myColl.updateMany(
   { category: "cafe" },
   { $set: { status: "Updated" } },
   { collation: { locale: "fr", strength: 1 } }
);

Specify arrayFilters for an Array Update Operations为数组更新操作指定arrayFilters

When updating an array field, you can specify arrayFilters that determine which array elements to update.更新数组字段时，可以指定arrayFilters来确定要更新的数组元素。

Update Elements Match arrayFilters Criteria更新元素匹配arrayFilters条件

Create a collection students with the following documents:使用以下文档创建students集合：

db.students.insertMany( [
   { _id: 1, grades: [ 95, 92, 90 ] },
   { _id: 2, grades: [ 98, 100, 102 ] },
   { _id: 3, grades: [ 95, 110, 100 ] }
] )

To update all elements that are greater than or equal to 100 in the grades array, use the filtered positional operator $[<identifier>] with the arrayFilters option:要更新grades数组中大于或等于100的所有元素，请使用带arrayFilters选项的筛选位置运算符$[<identifier>]：

db.students.updateMany(
   { grades: { $gte: 100 } },
   { $set: { "grades.$[element]" : 100 } },
   { arrayFilters: [ { "element": { $gte: 100 } } ] }
)

After the operation, the collection contains the following documents:操作后，集合包含以下文档：

{ _id: 1, grades: [ 95, 92, 90 ] }
{ _id: 2, grades: [ 98, 100, 100 ] }
{ _id: 3, grades: [ 95, 100, 100 ] }

Update Specific Elements of an Array of Documents更新文档数组的特定元素

Create a collection students2 with the following documents:使用以下文档创建集合students2：

db.students2.insertMany( [
   {
      _id: 1,
      grades: [
         { grade: 80, mean: 75, std: 6 },
         { grade: 85, mean: 90, std: 4 },
         { grade: 85, mean: 85, std: 6 }
      ]
   },
   {
      _id: 2,
      grades: [
         { grade: 90, mean: 75, std: 6 },
         { grade: 87, mean: 90, std: 3 },
         { grade: 85, mean: 85, std: 4 }
      ]
   }
] )

To modify the value of the mean field for all elements in the grades array where the grade is greater than or equal to 85, use the filtered positional operator $[<identifier>] with the arrayFilters:要修改grades数组中等级大于或等于85的所有元素的mean字段的值，请将筛选后的位置运算符$[<identifier>]与arrayFilters一起使用：

db.students2.updateMany(
   { },
   { $set: { "grades.$[elem].mean" : 100 } },
   { arrayFilters: [ { "elem.grade": { $gte: 85 } } ] }
)

After the operation, the collection has the following documents:操作后，集合有以下文件：

{
   _id: 1,
   grades: [
      { grade: 80, mean: 75, std: 6 },
      { grade: 85, mean: 100, std: 4 },
      { grade: 85, mean: 100, std: 6 }
   ]
}
{
   _id: 2,
   grades: [
      { grade: 90, mean: 100, std: 6 },
      { grade: 87, mean: 100, std: 3 },
      { grade: 85, mean: 100, std: 4 }
   ]
}

Specify hint for Update Operations指定更新操作的hint

Create a sample students collection with the following documents:使用以下文档创建示例students集合：

db.students.insertMany( [
   { _id: 1, student: "Richard", grade: "F", points:  0,  comments1: null, comments2: null },
   { _id: 2, student: "Jane", grade: "A", points: 60,  comments1: "well behaved", comments2: "fantastic student" },
   { _id: 3, student: "Ronan", grade: "F", points:  0,  comments1: null, comments2: null },
   { _id: 4, student: "Noah", grade: "D", points: 20,  comments1: "needs improvement", comments2: null },
   { _id: 5, student: "Adam", grade: "F", points:  0,  comments1: null, comments2: null },
   { _id: 6, student: "Henry", grade: "A", points: 86,  comments1: "fantastic student", comments2: "well behaved" }
] )

Create the following indexes on the collection:在集合上创建以下索引：

db.students.createIndex( { grade: 1 } )

The following update operation explicitly hints to use the index { grade: 1 }:以下更新操作明确提示使用索引{ grade: 1 }：

Note

If you specify an index that does not exist, the operation errors.如果指定的索引不存在，则操作会出错。

db.students.updateMany(
   { "points": { $lte: 20 }, "grade": "F" },
   { $set: { "comments1": "failed class" } },
   { hint: { grade: 1 } }
)

The update command returns the following:更新命令返回以下内容：

{ "acknowledged" : true, "matchedCount" : 3, "modifiedCount" : 3 }

To see if the hinted index is used, run the $indexStats pipeline:要查看是否使用了提示的索引，请运行$indexStats管道：

db.students.aggregate( [ { $indexStats: { } }, { $sort: { name: 1 } }, { $match: {key: { grade: 1 } } } ] )

Write Concern Errors in Sharded Clusters分片集群中的写入关注错误

Changed in version 8.1.2.在版本8.1.2中的更改。

When db.collection.updateMany() executes on mongos in a sharded cluster, a writeConcernError is always reported in the response, even when one or more other errors occur. 当db.collection.updateMany()在分片集群中的mongos上执行时，即使出现一个或多个其他错误，也总是在响应中报告writeConcernError。In previous releases, other errors sometimes caused db.collection.updateMany() to not report write concern errors.在以前的版本中，其他错误有时会导致db.collection.updateMany()不报告写入关注错误。

For example, if a document fails validation, triggering a DocumentValidationFailed error, and a write concern error also occurs, both the DocumentValidationFailed error and the writeConcernError are returned in the top-level field of the response.例如，如果文档验证失败，触发DocumentValidationFailed错误，并且还发生写入关注错误，则DocumentValidationFailure错误和writeConcernError都会在响应的顶级字段中返回。

User Roles and Document Updates用户角色和文档更新

Starting in MongoDB 7.0, you can use the new USER_ROLES system variable to return user roles.从MongoDB 7.0开始，您可以使用新的USER_ROLES系统变量返回用户角色。

The example in this section shows updates to fields in a collection containing medical information. The example reads the current user roles from the USER_ROLES system variable and only performs the updates if the user has a specific role.本节中的示例显示了包含医疗信息的集合中字段的更新。该示例从USER_ROLES系统变量读取当前用户角色，并且仅在用户具有特定角色时执行更新。

To use a system variable, add $$ to the start of the variable name. Specify the USER_ROLES system variable as $$USER_ROLES.要使用系统变量，请在变量名的开头添加$$。将USER_ROLES系统变量指定为$$USER_ROLES。

The example creates these users:该示例创建了以下用户：

  • James with a Billing role.具有Billing角色。
  • Michelle with a Provider role.具有Provider角色。

Perform the following steps to create the roles, users, and collection:执行以下步骤以创建角色、用户和集合：

1

Create the roles创建角色

Create roles named Billing and Provider with the required privileges and resources.创建具有所需权限和资源的名为Billing和Provider的角色。

Run:运行：

db.createRole( { role: "Billing", privileges: [ { resource: { db: "test",
   collection: "medicalView" }, actions: [ "find" ] } ], roles: [ ] } )
db.createRole( { role: "Provider", privileges: [ { resource: { db: "test",
   collection: "medicalView" }, actions: [ "find" ] } ], roles: [ ] } )
2

Create the users创建用户

Create users named James and Michelle with the required roles.创建具有所需角色的名为James和Michelle的用户。

db.createUser( {
   user: "James",
   pwd: "js008",
   roles: [
      { role: "Billing", db: "test" }
   ]
} )

db.createUser( {
   user: "Michelle",
   pwd: "me009",
   roles: [
      { role: "Provider", db: "test" }
   ]
} )
3

Create the collection创建集合

Run:运行：

db.medical.insertMany( [
   {
      _id: 0,
      patientName: "Jack Jones",
      diagnosisCode: "CAS 17",
      creditCard: "1234-5678-9012-3456"
   },
   {
      _id: 1,
      patientName: "Mary Smith",
      diagnosisCode: "ACH 01",
      creditCard: "6541-7534-9637-3456"
   }
] )

Log in as as Michelle, who has the Provider role, and perform an update:以Michelle（具有Provider角色）的身份登录，并执行更新：

1

Log in as Michelle以Michelle的身份登录

Run:运行：

db.auth( "Michelle", "me009" )
2

Perform update执行更新

Run:运行：

// Attempt to update many documents
db.medical.updateMany(
   // User must have the Provider role to perform the update
   { $expr: { $ne: [ {
      $setIntersection: [ [ "Provider" ], "$$USER_ROLES.role" ] }, []
   ] } },
   // Update diagnosisCode
   { $set: { diagnosisCode: "ACH 02"} }
)

The previous example uses $setIntersection to return documents where the intersection between the "Provider" string and the user roles from $$USER_ROLES.role is not empty. Michelle has the Provider role, so the update is performed.前面的示例使用$setIntersection返回文档，其中"Provider"字符串与$$user_ROLESrole中的用户角色之间的交集不为空。Michelle具有提供者角色，因此执行更新。

Next, log in as as James, who does not have the Provider role, and attempt to perform the same update:接下来，以没有Provider角色的James身份登录，并尝试执行相同的更新：

1

Log in as James以James的身份登录

Run:运行：

db.auth( "James", "js008" )
2

Attempt to perform update尝试执行更新

Run:运行：

// Attempt to update many documents
db.medical.updateMany(
   // User must have the Provider role to perform the update
   { $expr: { $ne: [ {
      $setIntersection: [ [ "Provider" ], "$$USER_ROLES.role" ] }, []
   ] } },
   // Update diagnosisCode
   { $set: { diagnosisCode: "ACH 02"} }
)

The previous example does not update any documents.前面的示例不会更新任何文档。