db.collection.update()

Replace Document Operations on a Sharded Collection替换分片集合上的文档操作

Starting in MongoDB 4.2, replace document operations attempt to target a single shard, first by using the query filter. 从MongoDB 4.2开始，替换文档操作尝试针对单个分片，首先使用查询筛选器。If the operation cannot target a single shard by the query filter, it then attempts to target by the replacement document.如果查询筛选器无法将操作定位于单个分片，则会尝试将替换文档作为目标。

In earlier versions, the operation attempts to target using the replacement document.在早期版本中，操作尝试使用替换文档作为目标。

upsert on a Sharded Collection分片系列的upsert

For a db.collection.update() operation that includes upsert: true and is on a sharded collection, you must include the full shard key in the filter:对于包含upsert:true并且位于分片集合上的db.collection.update()操作，必须在筛选器中包含完整的分片键：

• For an update operation.用于更新操作。
• For a replace document operation (starting in MongoDB 4.2).对于替换文档操作（从MongoDB 4.2开始）。

However, starting in version 4.4, documents in a sharded collection can be missing the shard key fields. 但是，从4.4版本开始，分片集合中的文档可能会缺少分片键字段。To target a document that is missing the shard key, you can use the null equality match in conjunction with another filter condition (such as on the _id field). 要针对缺少分片键的文档，可以将null相等匹配与另一个筛选条件结合使用（例如在_id字段上）。For example:例如：

{ _id: <value>, <shardkeyfield>: null } // _id of the document missing shard key

Shard Key Modification分片键修改

Starting in MongoDB 4.2, you can update a document's shard key value unless the shard key field is the immutable _id field. 从MongoDB 4.2开始，您可以更新文档的分片-key值，除非分片-key字段是不可变的_id字段。In MongoDB 4.2 and earlier, a document's shard key field value is immutable.在MongoDB 4.2及更早版本中，文档的分片键字段值是不可变的。

To modify the existing shard key value with db.collection.update():要使用db.collection.update()修改现有的分片键值，请执行以下操作：

• You must run on a mongos. 必须在mongos上运行。Do not issue the operation directly on the shard.不要直接在分片上发出操作。
• You must run either in a transaction or as a retryable write.您必须在事务中运行或作为可重试写入运行。
• You must specify multi: false.必须指定multi:false。
• You must include an equality query filter on the full shard key.必须在完整的分片键上包含一个相等查询筛选器。

See also upsert on a Sharded Collection.另请参阅分片集合上的upsert。

Missing Shard Key缺少分片键

Starting in version 4.4, documents in a sharded collection can be missing the shard key fields. 从4.4版本开始，分片集合中的文档可能会缺少分片键字段。To use db.collection.update() to set the document's missing shard key, you must run on a mongos. 要使用db.collection.update()设置文档缺少的分片键，必须在mongos上运行。Do not issue the operation directly on the shard.不要直接在分片上发出操作。

In addition, the following requirements also apply:此外，以下要求也适用：

See also:另请参阅：

• upsert on a Sharded Collection分片集合的upsert
• Missing Shard Key Fields缺少分片键字段

Upsert within Transactions事务中的Upsert

Starting in MongoDB 4.4, you can create collections and indexes inside a multi-document transaction if the transaction is not a cross-shard write transaction.从MongoDB 4.4开始，如果多文档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。

Specifically, in MongoDB 4.4 and greater, db.collection.update() with upsert: true can be run on an existing collection or a non-existing collection. 具体来说，在MongoDB 4.4及更高版本中，带有upsert:true的db.collection.update()可以在现有集合或不存在的集合上运行。If run on a non-existing collection, the operation creates the collection.如果在不存在的集合上运行，则该操作将创建该集合。

In MongoDB 4.2 and earlier, the operation must be run on an existing collection.在MongoDB 4.2及更早版本中，操作必须在现有集合上运行。

Write Concerns and Transactions撰写关注事项和事务

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，请不要显式设置操作的写入关注。要在事务中使用写入关注，请参阅事务和写入关注。

Upsert with Unique Index独特索引颠覆

When using the upsert: true option with the update() method, and not using a unique index on the query field(s), multiple instances of a update() operation with similar query field(s) could result in duplicate documents being inserted in certain circumstances.当在update()方法中使用upsert: true选项，并且不对查询字段使用唯一索引时，在某些情况下，具有相似查询字段的update()操作的多个实例可能会导致插入重复的文档。

Consider an example where no document with the name Andy exists and multiple clients issue the following command at roughly the same time:考虑一个示例，其中不存在名为Andy的文档，并且多个客户端大致同时发出以下命令：

db.people.update(
   { name: "Andy" },
   { $inc: { score: 1 } },
   {
     upsert: true,
     multi: true
   }
)

If all update() operations finish the query phase before any client successfully inserts data, and there is no unique index on the name field, each update() operation may result in an insert, creating multiple documents with name: Andy.如果所有的update()操作都在任何客户端成功插入数据之前完成了查询阶段，并且name字段上没有唯一索引，则每个update()运算都可能导致插入，从而创建多个name: Andy的文档。

To ensure that only one such document is created, and the other update() operations update this new document instead, create a unique index on the name field. 为了确保只创建一个这样的文档，而其他update()操作会更新这个新文档，请在name字段上创建一个唯一索引。This guarantees that only one document with name: Andy is permitted in the collection.这保证了集合中只允许一个name: Andy的文档。

With this unique index in place, the multiple c operations now exhibit the following behavior:有了这个唯一的索引，多个update()操作现在表现出以下行为：

• Exactly one update() operation will successfully insert a new document.只需执行一次update()操作即可成功插入新文档。
• All other update() operations will update the newly-inserted document, incrementing the score value.所有其他的update()操作都会更新新插入的文档，从而增加score值。

Modify a Field Using the Values of the Other Fields in the Document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commentsSomester2字段分开，而是想将它们聚集到一个新的comments字段中。以下更新操作使用聚合管道：

• 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commentsSomester2字段。

db.members.update(
   { },
   [
      { $set: { comments: [ "$commentsSemester1", "$commentsSemester2" ], lastUpdate: "$$NOW" } },
      { $unset: [ "commentsSemester1", "commentsSemester2" ] }
   ],
   { multi: true }
)

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commentsSomester2字段的当前内容
• 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 $$ and enclose in quotes.要访问聚合变量，请在变量前面加上双美元符号$$并用引号括起来。

Second Stage第二阶段

The $unset stage removes the commentsSemester1 and commentsSemester2 fields.$unset阶段删除commentsSemester1和commentsSemoster2字段。

After the command, the collection contains the following documents:命令之后，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" ] }

Perform Conditional Updates Based on Current Field Values根据当前字段值执行条件更新

Create a students3 collection with the following documents: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，可以使用计算出的平均成绩和字母成绩更新文档。

db.students3.update(
   { },
   [
     { $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"
     } } } }
   ],
   { multi: true }
)

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. See $avg for more information on the $avg aggregation operator and $trunc for more information on the $trunc truncate aggregation operator.基于tests字段的average来计算新的字段average。有关$avg聚合运算符的详细信息，请参阅$avg；有关$trunc截断聚合运算符的更多信息，请参阅$trunc。
• sets the field lastUpdate to the value of the aggregation variable NOW. The aggregation variable NOW resolves to the current datetime value and remains the same throughout the pipeline. 将字段lastUpdate设置为聚合变量NOW的值。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 $$ and enclose in quotes.要访问聚合变量，请在变量前面加上双美元符号$$并用引号括起来。

Second Stage第二阶段

The $set stage calculates a new field grade based on the average field calculated in the previous stage. See $switch for more information on the $switch aggregation operator.$set阶段根据上一阶段中计算的average字段来计算新的字段grade。有关$switch聚合运算符的详细信息，请参阅$switch。

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

{ "_id" : 1, "tests" : [ 95, 92, 90 ], "lastUpdate" : ISODate("2020-01-24T17:29:35.340Z"), "average" : 92, "grade" : "A" }
{ "_id" : 2, "tests" : [ 94, 88, 90 ], "lastUpdate" : ISODate("2020-01-24T17:29:35.340Z"), "average" : 90, "grade" : "A" }
{ "_id" : 3, "tests" : [ 70, 75, 82 ], "lastUpdate" : ISODate("2020-01-24T17:29:35.340Z"), "average" : 75, "grade" : "C" }

Update Elements Match arrayFilters Criteria更新匹配arrayFilters条件的元素

To update all array elements which match a specified criteria, use the arrayFilters parameter.要更新与指定条件匹配的所有数组元素，请使用arrayFilters参数。

In mongosh, create a students collection with the following documents:在mongosh中，使用以下文档创建一个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 $[<identifier>] with the arrayFilters option:要更新grades数组中大于或等于100的所有元素，请将已筛选的位置运算符$[<identifier>]配合arrayFilters选项一起使用：

db.students.update(
   { grades: { $gte: 100 } },
   { $set: { "grades.$[element]" : 100 } },
   {
     multi: true,
     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

You can also use the arrayFilters parameter to update specific document fields within an array of documents.还可以使用arrayFilters参数更新文档数组中的特定文档字段。

In mongosh, create a students2 collection with the following documents:在mongosh中，使用以下文档创建students2集合：

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 $[<identifier>] with the arrayFilters:要修改grades数组中grade大于或等于85的所有元素的mean字段值，请将筛选后的位置运算符$[<identifier>]与arrayFilters一起使用：

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

After the operation, the collection has the following documents:操作后，集合具有以下文档：

{
   "_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 }
   ]
}