MongoDB $reduce(aggregation) 组与数组中嵌套文档的总和并按组计数
Posted
技术标签:
【中文标题】MongoDB $reduce(aggregation) 组与数组中嵌套文档的总和并按组计数【英文标题】：MongoDB $reduce(aggregation) group with the sum of the nested document in arrays and count by group 【发布时间】：2020-01-13 06:30:07 【问题描述】：MongoDB 聚合框架查询：$group、$project、$addFields 和 $reduce。
用例： 我在集合中有多个带有嵌套文档数组的文档，需要一个结果分组依据和每个分组项的总和作为累积量。此外，在年份（日期）上具有匹配参数，如果年份匹配，则只有该年份文档应分组，并且返回卷的总和（嵌套文档数组）。
以下是集合中的文档：
"_id": "1",
"LSD":
"name": "TDL 05",
"LSDNumber": "031"
,
"POD": [
"Volume": 35.40,
"VolUnit": "m3"
,
"Volume": 20.75,
"VolUnit": "m3"
,
"Volume": 15,
"VolUnit": "m3"
],
"createdon":
"$date": "2014-08-02T18:49:17.000Z"
,
"_id": "2",
"LSD":
"name": "Stock Watering",
"LSDNumber": "01"
,
"POD": [
"Volume": 105,
"VolUnit": "m3"
,
"Volume": 70,
"VolUnit": "m3"
,
"Volume": 35,
"VolUnit": "m3"
],
"createdon":
"$date": "2014-08-02T18:49:17.000Z"
,
"_id": "3",
"LSD":
"name": "TDL 30 Stock Water",
"LSDNumber": "030"
,
"POD": [
"Volume": 87,
"VolUnit": "m3"
],
"createdon":
"$date": "2019-08-02T18:49:17.000Z"
,
"_id": "4",
"LSD":
"name": "TDL 30 Stock Water",
"LSDNumber": "030"
,
"POD": [
"Volume": 25.12,
"VolUnit": "m3"
],
"createdon":
"$date": "2019-08-02T18:49:17.000Z"
,
"_id": "5",
"LSD":
"name": "TDL 05",
"LSDNumber": "031"
,
"POD": [
"Volume": 21,
"VolUnit": "m3"
],
"createdon":
"$date": "2014-08-02T18:49:17.000Z"
我有一个查询（C# Driver 2.0），按“LSD.LSDNumber”和“POD.Volume”的总和分组。此处未添加匹配参数。这很好用。
查询：
aggregate([
"$group":
"_id": "$LSD.LSDNumber",
"doc":
"$push": "$POD"
,
"data":
"$first": "$$ROOT"
,
"$addFields":
"LSDNumber": "$_id",
"GroupByDocCount":
"$size": "$doc"
,
"Cumulative":
"$reduce":
"input": "$doc",
"initialValue": [],
"in":
"$concatArrays": ["$$value", "$$this"]
,
"$project":
"LSDNumber": 1,
"GroupByDocCount": 1,
"CumulativeVol":
"$sum": "$Cumulative.Volume"
])
下面是结果。
"LSDNumber":"031",
"GroupByDocCount": 2,
"CumulativeVol": 92.15
,
"LSDNumber":"030",
"GroupByDocCount": 2,
"CumulativeVol": 112.12
,
"LSDNumber":"01",
"GroupByDocCount": 1,
"CumulativeVol": 210
但是，我想按年份（在“createdon”）日期以及按（LSD.LSDNumber）和总和（POD.Volume）分组来获取文档匹配。 例如，如果年份是 2014 年，那么下面的结果应该是。
"LSDNumber":"031",
"GroupByDocCount": 2,
"CumulativeVol": 92.15,
"Year": 2014
,
"LSDNumber":"01",
"GroupByDocCount": 1,
"CumulativeVol": 210,
"Year": 2014
我尝试的查询总是什么都不返回。
aggregate([
"$project":
"LSDNumber": 1,
"GroupByDocCount": 1,
"CumulativeVol":
"$sum": "$Cumulative.Volume"
,
"year":
"$year": "$data.createdon"
,
"$match":
"year": 2014
,
"$group":
"_id": "$LSD.LSDNumber",
"year":
"$first": "$year"
,
"doc":
"$push": "$POD"
,
"data":
"$first": "$$ROOT"
,
"$addFields":
"LSDNumber": "$_id",
"yearCreate": "$year",
"GroupByDocCount":
"$size": "$doc"
,
"Cumulative":
"$reduce":
"input": "$doc",
"initialValue": [],
"in":
"$concatArrays": ["$$value", "$$this"]
])
这里出了什么问题。任何帮助将不胜感激！
【问题讨论】：
为什么项目中"$year": "$data.createdon"中有$data？应该只是$createdon？
@DaveStSomeWhere 抱歉回复晚了。无论如何，用$data.createdon 更正了$createdon，但结果相同。
【参考方案1】：
您可以在 $addField 管道中添加 Year 变量，然后添加 $match。
"$group":
"_id": "$LSD.LSDNumber",
"doc":
"$push": "$POD"
,
"data":
"$first": "$$ROOT"
,
"$addFields":
"LSDNumber": "$_id",
"GroupByDocCount":
"$size": "$doc"
,
"Cumulative":
"$reduce":
"input": "$doc",
"initialValue": [],
"in":
"$concatArrays": ["$$value", "$$this"]
,
"Year":
"$year": "$data.createdon"
,
"$match" : "Year" : 2014
,
"$project":
"LSDNumber": 1,
"GroupByDocCount": 1,
"CumulativeVol":
"$sum": "$Cumulative.Volume"
,
"Year" : "$Year"
=== 结果 ===
/* 1 */
"_id" : "01",
"LSDNumber" : "01",
"GroupByDocCount" : 1,
"CumulativeVol" : 210,
"Year" : 2014
/* 2 */
"_id" : "031",
"LSDNumber" : "031",
"GroupByDocCount" : 2,
"CumulativeVol" : 92.15,
"Year" : 2014
【讨论】：
【参考方案2】：有点晚了，但这是我的答案。我们只需要在最后阶段向管道添加一个项目阶段（额外）。但是，@Valijon 的回答符合同样的要求。
aggregate([
"$project":
"LSDNumber": "$LSD.LSDNumber",
"year":
"$year": "$createdon"
,
"PointOfDiversionVolumeDetails": 1
,
"$match":
"year": 2014
,
"$group":
"_id": "$LSDNumber",
"doc":
"$push": "$PointOfDiversionVolumeDetails"
,
"$addFields":
"GroupByDocCount":
"$size": "$doc"
,
"Cumulative":
"$reduce":
"input": "$doc",
"initialValue": [],
"in":
"$concatArrays": ["$$value", "$$this"]
,
"$project":
"CumulativeVol":
"$sum": "$Cumulative.Volume"
,
"LSDNumber": 1,
"GroupByDocCount": 1
,
"$sort":
"GroupByDocCount": -1
])
【讨论】：
以上是关于MongoDB $reduce(aggregation) 组与数组中嵌套文档的总和并按组计数的主要内容，如果未能解决你的问题，请参考以下文章