是否有可能做出这样的计算并将结果返回给MongoDB？

Question

我对MongoDB很新。考虑下面的集合：

{ 
"_id" : ObjectId("c0c672fa6db9b3f954732b1a"), 
"date" : ISODate("2016-11-12T00:00:00.000Z"), 
"statistics" : { 
    "members" : { 
     "topPerformers" : { 
      "hours" : [ 
       { 
        "workHour" : 10, 
        "Darth Vader" : 72, 
        "Walrus Man" : 80, 
        "Imperial Stromtrooper" : 60 
       }, 
       { 
        "workHour" : 11, 
        "Darth Vader" : 142, 
        "Walrus Man" : 115, 
        "Imperial Stromtrooper" : 100 
       }, 
       { 
        "workHour" : 12, 
        "Darth Vader" : 116, 
        "Walrus Man" : 81, 
        "Imperial Stromtrooper" : 113 
       }, 
       { 
        "workHour" : 13, 
        "Darth Vader" : 128, 
        "Walrus Man" : 90, 
        "Imperial Stromtrooper" : 141 
       }, 
       { 
        "workHour" : 14, 
        "Darth Vader" : 95, 
        "Walrus Man" : 118, 
        "Imperial Stromtrooper" : 116 
       }, 
       { 
        "workHour" : 15, 
        "Darth Vader" : 91, 
        "Walrus Man" : 93, 
        "Imperial Stromtrooper" : 124 
       }, 
       { 
        "workHour" : 16, 
        "Darth Vader" : 144, 
        "Walrus Man" : 95, 
        "Imperial Stromtrooper" : 111 
       }, 
       { 
        "workHour" : 17, 
        "Darth Vader" : 143, 
        "Walrus Man" : 72, 
        "Imperial Stromtrooper" : 136 
       }, 
       { 
        "workHour" : 18, 
        "Darth Vader" : 54, 
        "Walrus Man" : 88, 
        "Imperial Stromtrooper" : 87 
       }, 
       { 
        "workHour" : 19, 
        "Darth Vader" : 82, 
        "Walrus Man" : 146, 
        "Imperial Stromtrooper" : 67 
       }, 
       { 
        "workHour" : 20, 
        "Darth Vader" : 88, 
        "Walrus Man" : 136, 
        "Imperial Stromtrooper" : 52 
       }, 
       { 
        "workHour" : 21, 
        "Darth Vader" : 92, 
        "Walrus Man" : 113, 
        "Imperial Stromtrooper" : 124 
       }, 
       { 
        "workHour" : 22, 
        "Darth Vader" : 91, 
        "Walrus Man" : 68, 
        "Imperial Stromtrooper" : 128 
       }, 
       { 
        "workHour" : 23, 
        "Darth Vader" : 125, 
        "Walrus Man" : 64, 
        "Imperial Stromtrooper" : 84 
       }, 
       { 
        "workHour" : 0, 
        "Darth Vader" : 97, 
        "Walrus Man" : 108, 
        "Imperial Stromtrooper" : 75 
       } 
      ] 
     } 
    } 
} 
} 

1天每一个记录是这样的，比如我有收集每天在30份文件。我可以用我想要的日期范围做db.getCollection('name').find({ date: { $gte: new ISODate(), $lt: new ISODate() } })，然后如果我选择了整个月的记录，我可以循环使用statistics.members.topPerformers.hours并计算当天每个成员在客户端的总数，如下所示：

statistics.members.topPerformers.hours.forEach((hour) => { 
      Object 
      .keys(hour) 
      .filter(key => key !== 'workHour') 
      .forEach((key) => { 
       result[key] = (result[key] || 0) + hour[key]; 
      }); 
     }); 

我能做到这一点的服务器端与蒙戈并返回修改后的结果是这样一个例子：

{ 
"_id" : ObjectId("c0c672fa6db9b3f954732b1a"), 
"date" : ISODate("2016-11-12T00:00:00.000Z"), 
"statistics" : { 
    "members" : { 
     "topPerformers" : { 
      "hours" : [ 
       { 
        "workHour" : 10, 
        "Darth Vader" : 2512, 
        "Walrus Man" : 1423, 
        "Imperial Stromtrooper" : 1487 
       }, 
      ] 
      } 
     } 
    } 

Answer 1

你可以运行聚合管道，它利用了$match操作流水线阶段来过滤col中的文档以前的$unwind运算符可以将嵌入的小时数组展平，然后您可以使用管道对非规格化文档进行分组并计算总和。

以下蒙戈外壳操作演示上面：

var start = new Date(); 
start.setHours(0,0,0,0); 

var end = new Date(); 
end.setHours(23,59,59,999); 

db.collection.aggregate([ 
    { "$match": { "date": { "$gte": start, "$lte": end } } }, 
    { "$unwind": "$statistics.members.topPerformers.hours" }, 
    { 
     "$group": { 
      "_id": "$_id", 
      "date": { "$first": "$date" }, 
      "workHour" : { 
       "$sum": "$statistics.members.topPerformers.hours.workHour" 
      }, 
      "Darth Vader" : { 
       "$sum": "$statistics.members.topPerformers.hours.Darth Vader" 
      }, 
      "Walrus Man" : { 
       "$sum": "$statistics.members.topPerformers.hours.Walrus Man" 
      }, 
      "Imperial Stromtrooper" : { 
       "$sum": "$statistics.members.topPerformers.hours.Imperial Stromtrooper" 
      } 
     } 
    } 
]); 

样本输出

{ 
    "_id" : ObjectId("c0c672fa6db9b3f954732b1a"), 
    "date" : ISODate("2016-11-12T00:00:00.000Z"), 
    "workHour" : 231.0, 
    "Darth Vader" : 1560.0, 
    "Walrus Man" : 1467.0, 
    "Imperial Stromtrooper" : 1518.0 
} 

---

虽然不是必需的，你可以重塑通过附加一个$project最后文件领域管道如下

db.collection.aggregate([ 
    { "$match": { "date": { "$gte": start, "$lte": end } } }, 
    { "$unwind": "$statistics.members.topPerformers.hours" }, 
    { 
     "$group": { 
      "_id": "$_id", 
      "date": { "$first": "$date" }, 
      "workHour" : { 
       "$sum": "$statistics.members.topPerformers.hours.workHour" 
      }, 
      "Darth Vader" : { 
       "$sum": "$statistics.members.topPerformers.hours.Darth Vader" 
      }, 
      "Walrus Man" : { 
       "$sum": "$statistics.members.topPerformers.hours.Walrus Man" 
      }, 
      "Imperial Stromtrooper" : { 
       "$sum": "$statistics.members.topPerformers.hours.Imperial Stromtrooper" 
      } 
     } 
    }, 
    { 
     "$project": { 
      "date": 1, 
      "statistics.members.topPerformers.hours.workHour": "$workHour",, 
      "statistics.members.topPerformers.hours.Darth Vader": "$Darth Vader", 
      "statistics.members.topPerformers.hours.Walrus Man": "$Walrus Man", 
      "statistics.members.topPerformers.hours.Imperial Stromtrooper": "$Imperial Stromtrooper" 
     } 
    } 
]) 

输出

{ 
    "_id" : ObjectId("c0c672fa6db9b3f954732b1a"), 
    "date" : ISODate("2016-11-12T00:00:00.000Z"), 
    "statistics" : { 
     "members" : { 
      "topPerformers" : { 
       "hours" : { 
        "workHour" : 231.0, 
        "Darth Vader" : 1560.0, 
        "Walrus Man" : 1467.0, 
        "Imperial Stromtrooper" : 1518.0 
       } 
      } 
     } 
    } 
}