定义
$unwind：将文档中的某一个数组类型字段拆分成多条，每条包含数组中的一个值。
语法
您可以传递字段路径操作数或文档操作数来展开数组字段。
字段路径
您可以将数组字段路径传递给 $unwind。使用此语法时，如果字段值为 null、缺失或空数组，则 $unwind 不会输出文档。
{ $unwind: <field path> }
指定字段路径时，在字段名称前加上美元符号 $ 并用引号引起来。
带选项的文档
您可以将文档传递给 $unwind 以指定各种行为选项。
{
$unwind:
{
path: <field path>,
includeArrayIndex: <string>,
preserveNullAndEmptyArrays: <boolean>
}
}
| 字段 | 类型 | 描述 |
|---|---|---|
| path | string | 数组字段的字段路径。要指定字段路径，请在字段名称前加上美元符号 $ 并用引号括起来。 |
| includeArrayIndex | string | 可选的。保存元素数组索引的新字段的名称。名称不能以美元符号 $ 开头。 |
| preserveNullAndEmptyArrays | boolen | 可选的。 如果为 true，如果路径为空、缺失或空数组，则 $unwind 输出文档。 如果为 false，如果 path 为空、缺失或空数组，则 $unwind 不会输出文档。 默认值为false。 |
例子
展开数组
插入数据
db.inventory.insertOne({ "_id" : 1, "item" : "ABC1", sizes: [ "S", "M", "L"] })
使用$unwind展开
db.inventory.aggregate( [ { $unwind : "$sizes" } ] )
该操作返回以下结果：
{ "_id" : 1, "item" : "ABC1", "sizes" : "S" }
{ "_id" : 1, "item" : "ABC1", "sizes" : "M" }
{ "_id" : 1, "item" : "ABC1", "sizes" : "L" }
使用includeArrayIndex和preserveNullAndEmptyArrays
示例数据
db.inventory2.insertMany([
{ "_id" : 1, "item" : "ABC", price: NumberDecimal("80"), "sizes": [ "S", "M", "L"] },
{ "_id" : 2, "item" : "EFG", price: NumberDecimal("120"), "sizes" : [ ] },
{ "_id" : 3, "item" : "IJK", price: NumberDecimal("160"), "sizes": "M" },
{ "_id" : 4, "item" : "LMN" , price: NumberDecimal("10") },
{ "_id" : 5, "item" : "XYZ", price: NumberDecimal("5.75"), "sizes" : null }
])
以下$unwind操作是等效的，并为sizes字段中的每个元素返回一个文档。如果sizes 字段未解析为数组但不丢失、为空或空数组，$unwind则将非数组操作数视为单元素数组。
db.inventory2.aggregate( [ { $unwind: "$sizes" } ] )
db.inventory2.aggregate( [ { $unwind: { path: "$sizes" } } ] )
该操作返回以下文档：
{ "_id" : 1, "item" : "ABC", "price" : NumberDecimal("80"), "sizes" : "S" }
{ "_id" : 1, "item" : "ABC", "price" : NumberDecimal("80"), "sizes" : "M" }
{ "_id" : 1, "item" : "ABC", "price" : NumberDecimal("80"), "sizes" : "L" }
{ "_id" : 3, "item" : "IJK", "price" : NumberDecimal("160"), "sizes" : "M" }
includeArrayIndex
以下$unwind操作使用 includeArrayIndex选项在输出中包含数组索引。
db.inventory2.aggregate( [
{
$unwind:
{
path: "$sizes",
includeArrayIndex: "arrayIndex"
}
}])
该操作展开sizes数组并在新arrayIndex字段中包含数组索引的数组索引。如果该sizes 字段未解析为数组但不缺失、为 null 或空数组，则该arrayIndex字段为null。
操作返回结果：
{ "_id" : 1, "item" : "ABC", "price" : NumberDecimal("80"), "sizes" : "S", "arrayIndex" : NumberLong(0) }
{ "_id" : 1, "item" : "ABC", "price" : NumberDecimal("80"), "sizes" : "M", "arrayIndex" : NumberLong(1) }
{ "_id" : 1, "item" : "ABC", "price" : NumberDecimal("80"), "sizes" : "L", "arrayIndex" : NumberLong(2) }
{ "_id" : 3, "item" : "IJK", "price" : NumberDecimal("160"), "sizes" : "M", "arrayIndex" : null }
preserveNullAndEmptyArrays
以下$unwind操作使用 preserveNullAndEmptyArrays 选项来包含sizes字段为空、缺失或空数组的文档。
db.inventory2.aggregate( [
{ $unwind: { path: "$sizes", preserveNullAndEmptyArrays: true } }
] )
输出包括sizes字段为空、缺失或空数组的文档：
{ "_id" : 1, "item" : "ABC", "price" : NumberDecimal("80"), "sizes" : "S" }
{ "_id" : 1, "item" : "ABC", "price" : NumberDecimal("80"), "sizes" : "M" }
{ "_id" : 1, "item" : "ABC", "price" : NumberDecimal("80"), "sizes" : "L" }
{ "_id" : 2, "item" : "EFG", "price" : NumberDecimal("120") }
{ "_id" : 3, "item" : "IJK", "price" : NumberDecimal("160"), "sizes" : "M" }
{ "_id" : 4, "item" : "LMN", "price" : NumberDecimal("10") }
{ "_id" : 5, "item" : "XYZ", "price" : NumberDecimal("5.75"), "sizes" : null }
按展开值分组
示例数据：
db.inventory2.insertMany([
{ "_id" : 1, "item" : "ABC", price: NumberDecimal("80"), "sizes": [ "S", "M", "L"] },
{ "_id" : 2, "item" : "EFG", price: NumberDecimal("120"), "sizes" : [ ] },
{ "_id" : 3, "item" : "IJK", price: NumberDecimal("160"), "sizes": "M" },
{ "_id" : 4, "item" : "LMN" , price: NumberDecimal("10") },
{ "_id" : 5, "item" : "XYZ", price: NumberDecimal("5.75"), "sizes" : null }
])
以下管道展开sizes数组并按展开大小值对结果文档进行分组：
db.inventory2.aggregate( [
// First Stage
{
$unwind: { path: "$sizes", preserveNullAndEmptyArrays: true }
},
// Second Stage
{
$group:
{
_id: "$sizes",
averagePrice: { $avg: "$price" }
}
},
// Third Stage
{
$sort: { "averagePrice": -1 }
}
] )
第一阶段：
该$unwind阶段为sizes数组中的每个元素输出一个新文档。该阶段使用 preserveNullAndEmptyArrays 选项在输出中包含sizes字段缺失、为空或空数组的文档。此阶段将以下文档传递到下一阶段：
{ "_id" : 1, "item" : "ABC", "price" : NumberDecimal("80"), "sizes" : "S" }
{ "_id" : 1, "item" : "ABC", "price" : NumberDecimal("80"), "sizes" : "M" }
{ "_id" : 1, "item" : "ABC", "price" : NumberDecimal("80"), "sizes" : "L" }
{ "_id" : 2, "item" : "EFG", "price" : NumberDecimal("120") }
{ "_id" : 3, "item" : "IJK", "price" : NumberDecimal("160"), "sizes" : "M" }
{ "_id" : 4, "item" : "LMN", "price" : NumberDecimal("10") }
{ "_id" : 5, "item" : "XYZ", "price" : NumberDecimal("5.75"), "sizes" : null }
第二阶段：
该$group阶段将文档分组sizes 并计算每个尺寸的平均价格。此阶段将以下文档传递到下一阶段：
{ "_id" : "S", "averagePrice" : NumberDecimal("80") }
{ "_id" : "L", "averagePrice" : NumberDecimal("80") }
{ "_id" : "M", "averagePrice" : NumberDecimal("120") }
{ "_id" : null, "averagePrice" : NumberDecimal("45.25") }
第三阶段：
该$sort阶段按averagePrice降序对文档进行排序。该操作返回以下结果：
{ "_id" : "M", "averagePrice" : NumberDecimal("120") }
{ "_id" : "L", "averagePrice" : NumberDecimal("80") }
{ "_id" : "S", "averagePrice" : NumberDecimal("80") }
{ "_id" : null, "averagePrice" : NumberDecimal("45.25") }
也可以看看：
展开嵌入式数组
在mongosh中，创建一个sales使用以下文档命名的示例集合 ：
db.sales.insertMany([
{
_id: "1",
"items" : [
{
"name" : "pens",
"tags" : [ "writing", "office", "school", "stationary" ],
"price" : NumberDecimal("12.00"),
"quantity" : NumberInt("5")
},
{
"name" : "envelopes",
"tags" : [ "stationary", "office" ],
"price" : NumberDecimal("1.95"),
"quantity" : NumberInt("8")
}
]
},
{
_id: "2",
"items" : [
{
"name" : "laptop",
"tags" : [ "office", "electronics" ],
"price" : NumberDecimal("800.00"),
"quantity" : NumberInt("1")
},
{
"name" : "notepad",
"tags" : [ "stationary", "school" ],
"price" : NumberDecimal("14.95"),
"quantity" : NumberInt("3")
}
]
}
])
以下操作按标签对出售的商品进行分组，并计算每个标签的总销售额。
db.sales.aggregate([
// First Stage
{ $unwind: "$items" },
// Second Stage
{ $unwind: "$items.tags" },
// Third Stage
{
$group:
{
_id: "$items.tags",
totalSalesAmount:
{
$sum: { $multiply: [ "$items.price", "$items.quantity" ] }
}
}
}
])
第一阶段：
第一阶段$unwind为items数组中的每个元素输出一个新文档：
{ "_id" : "1", "items" : { "name" : "pens", "tags" : [ "writing", "office", "school", "stationary" ], "price" : NumberDecimal("12.00"), "quantity" : 5 } }
{ "_id" : "1", "items" : { "name" : "envelopes", "tags" : [ "stationary", "office" ], "price" : NumberDecimal("19.95"), "quantity" : 8 } }
{ "_id" : "2", "items" : { "name" : "laptop", "tags" : [ "office", "electronics" ], "price" : NumberDecimal("800.00"), "quantity" : 1 } }
{ "_id" : "2", "items" : { "name" : "notepad", "tags" : [ "stationary", "school" ], "price" : NumberDecimal("14.95"), "quantity" : 3 } }
第二阶段：
第二阶段$unwind为items.tags数组中的每个元素输出一个新文档：
{ "_id" : "1", "items" : { "name" : "pens", "tags" : "writing", "price" : NumberDecimal("12.00"), "quantity" : 5 } }
{ "_id" : "1", "items" : { "name" : "pens", "tags" : "office", "price" : NumberDecimal("12.00"), "quantity" : 5 } }
{ "_id" : "1", "items" : { "name" : "pens", "tags" : "school", "price" : NumberDecimal("12.00"), "quantity" : 5 } }
{ "_id" : "1", "items" : { "name" : "pens", "tags" : "stationary", "price" : NumberDecimal("12.00"), "quantity" : 5 } }
{ "_id" : "1", "items" : { "name" : "envelopes", "tags" : "stationary", "price" : NumberDecimal("19.95"), "quantity" : 8 } }
{ "_id" : "1", "items" : { "name" : "envelopes", "tags" : "office", "price" : NumberDecimal("19.95"), "quantity" : 8 } }
{ "_id" : "2", "items" : { "name" : "laptop", "tags" : "office", "price" : NumberDecimal("800.00"), "quantity" : 1 } }
{ "_id" : "2", "items" : { "name" : "laptop", "tags" : "electronics", "price" : NumberDecimal("800.00"), "quantity" : 1 } }
{ "_id" : "2", "items" : { "name" : "notepad", "tags" : "stationary", "price" : NumberDecimal("14.95"), "quantity" : 3 } }
{ "_id" : "2", "items" : { "name" : "notepad", "tags" : "school", "price" : NumberDecimal("14.95"), "quantity" : 3 } }
第三阶段：
该阶段$group按标签对文档进行分组，并计算带有每个标签的商品的总销售额：
{ "_id" : "writing", "totalSalesAmount" : NumberDecimal("60.00") }
{ "_id" : "stationary", "totalSalesAmount" : NumberDecimal("264.45") }
{ "_id" : "electronics", "totalSalesAmount" : NumberDecimal("800.00") }
{ "_id" : "school", "totalSalesAmount" : NumberDecimal("104.85") }
{ "_id" : "office", "totalSalesAmount" : NumberDecimal("1019.60") }
也可以看看：
参考
https://docs.mongodb.com/manual/reference/operator/aggregation/unwind/
