Question

Essentially I'm trying to filter OUT subdocuments and sub-subdocuments that have been "trashed". Here's a stripped-down version of my schema:

permitSchema = {
  _id,
  name,
  ...
  feeClassifications: [
    new Schema({
      _id,
      _trashed,
      name,
      fees: [
        new Schema({
          _id,
          _trashed,
          name,
          amount
        })
      ]
    })
  ],
  ...
}

So I'm able to get the effect I want with feeClassifications. But I'm struggling to find a way to have the same effect for feeClassifications.fees as well.

So, this works as desired:

Permit.aggregate([
  { $match: { _id: mongoose.Types.ObjectId(req.params.id) }},
  { $project: {
    _id: 1,
    _name: 1,
    feeClassifications: {
      $filter: {
        input: '$feeClassifications',
        as: 'item',
        cond: { $not: {$gt: ['$$item._trashed', null] } }
      }
    }
  }}
])

But I also want to filter the nested array fees. I've tried a few things including:

Permit.aggregate([
  { $match: { _id: mongoose.Types.ObjectId(req.params.id) }},
  { $project: {
    _id: 1,
    _name: 1,
    feeClassifications: {
      $filter: {
        input: '$feeClassifications',
        as: 'item',
        cond: { $not: {$gt: ['$$item._trashed', null] } }
      },
      fees: {
        $filter: {
          input: '$fees',
          as: 'fee',
          cond: { $not: {$gt: ['$$fee._trashed', null] } }
        }
      }
    }
  }}
])

Which seems to follow the mongodb docs the closest. But I get the error: this object is already an operator expression, and can't be used as a document expression (at 'fees')

Update: -----------

As requested, here's a sample document:

{
    "_id" : ObjectId("57803fcd982971e403e3e879"),
    "_updated" : ISODate("2016-07-11T19:24:27.204Z"),
    "_created" : ISODate("2016-07-09T00:05:33.274Z"),
    "name" : "Single Event",
    "feeClassifications" : [ 
        {
            "_updated" : ISODate("2016-07-11T19:05:52.418Z"),
            "_created" : ISODate("2016-07-11T17:49:12.247Z"),
            "name" : "Event Type 1",
            "_id" : ObjectId("5783dc18e09be99840fad29f"),
            "fees" : [ 
                {
                    "_updated" : ISODate("2016-07-11T18:51:10.259Z"),
                    "_created" : ISODate("2016-07-11T18:41:16.110Z"),
                    "name" : "Basic Fee",
                    "amount" : 156.5,
                    "_id" : ObjectId("5783e84cc46a883349bb2339")
                }, 
                {
                    "_updated" : ISODate("2016-07-11T19:05:52.419Z"),
                    "_created" : ISODate("2016-07-11T19:05:47.340Z"),
                    "name" : "Secondary Fee",
                    "amount" : 50,
                    "_id" : ObjectId("5783ee0bad7bf8774f6f9b5f"),
                    "_trashed" : ISODate("2016-07-11T19:05:52.410Z")
                }
            ]
        }, 
        {
            "_updated" : ISODate("2016-07-11T18:22:21.567Z"),
            "_created" : ISODate("2016-07-11T18:22:21.567Z"),
            "name" : "Event Type 2",
            "_id" : ObjectId("5783e3dd540078de45bbbfaf"),
            "_trashed" : ISODate("2016-07-11T19:24:27.203Z")
        }
    ]
}

And here's the desired output ("trashed" subdocuments are excluded from BOTH feeClassifications AND fees):

{
    "_id" : ObjectId("57803fcd982971e403e3e879"),
    "_updated" : ISODate("2016-07-11T19:24:27.204Z"),
    "_created" : ISODate("2016-07-09T00:05:33.274Z"),
    "name" : "Single Event",
    "feeClassifications" : [ 
        {
            "_updated" : ISODate("2016-07-11T19:05:52.418Z"),
            "_created" : ISODate("2016-07-11T17:49:12.247Z"),
            "name" : "Event Type 1",
            "_id" : ObjectId("5783dc18e09be99840fad29f"),
            "fees" : [ 
                {
                    "_updated" : ISODate("2016-07-11T18:51:10.259Z"),
                    "_created" : ISODate("2016-07-11T18:41:16.110Z"),
                    "name" : "Basic Fee",
                    "amount" : 156.5,
                    "_id" : ObjectId("5783e84cc46a883349bb2339")
                }
            ]
        }
    ]
}

Answer 1

由于我们要过滤外部和内部数组字段，我们可以使用$map变量运算符，它返回一个包含我们想要的“值”的数组。

在$map表达式中，我们提供了一个逻辑$cond itional $filter，用于从文档和子文档数组字段中删除不匹配的文档。

条件为$lt，当子文档和/或子文档数组字段中不存在“_trashed”字段时，该条件返回true。

请注意，在$cond表达式中，我们也会为<false case>返回false。当然，我们需要对$map结果应用过滤器，以删除所有false。

Permit.aggregate(
    [ 
        { "$match": { "_id": mongoose.Types.ObjectId(req.params.id) } },
        { "$project": { 
            "_updated": 1, 
            "_created": 1, 
            "name": 1, 
            "feeClassifications": { 
                "$filter": {
                    "input": {
                        "$map": { 
                            "input": "$feeClassifications", 
                            "as": "fclass", 
                            "in": { 
                                "$cond": [ 
                                    { "$lt": [ "$$fclass._trashed", 0 ] }, 
                                    { 
                                        "_updated": "$$fclass._updated", 
                                        "_created": "$$fclass._created", 
                                        "name": "$$fclass.name", 
                                        "_id": "$$fclass._id", 
                                        "fees": { 
                                            "$filter": { 
                                                "input": "$$fclass.fees", 
                                                "as": "fees", 
                                                "cond": { "$lt": [ "$$fees._trashed", 0 ] }
                                            }
                                        }
                                    }, 
                                    false 
                                ]
                            }
                        }
                    }, 
                    "as": "cls",  
                    "cond": "$$cls"
                }
            }
        }}
    ]
)

在即将发布的MongoDB版本中（截至撰写本文时及MongoDB 3.3.5版本），您可以使用$cond表达式替换$map表达式中的$switch表达式：< / p>

Permit.aggregate(
    [ 
        { "$match": { "_id": mongoose.Types.ObjectId(req.params.id) } },
        { "$project": { 
            "_updated": 1, 
            "_created": 1, 
            "name": 1, 
            "feeClassifications": { 
                "$filter": {
                    "input": {
                        "$map": { 
                            "input": "$feeClassifications", 
                            "as": "fclass", 
                            "in": { 
                                "$switch": { 
                                    "branches": [ 
                                        { 
                                            "case": { "$lt": [ "$$fclass._trashed", 0 ] }, 
                                            "then": { 
                                                "_updated": "$$fclass._updated", 
                                                "_created": "$$fclass._created", 
                                                "name": "$$fclass.name", 
                                                "_id": "$$fclass._id", 
                                                "fees": { 
                                                    "$filter": { 
                                                        "input": "$$fclass.fees", 
                                                        "as": "fees", 
                                                        "cond": { "$lt": [ "$$fees._trashed", 0 ] }
                                                    }
                                                }
                                            } 
                                        } 
                                    ], 
                                    "default":  false 
                                }
                            }
                        }
                    },
                    "as": "cls",  
                    "cond": "$$cls"
                }
            }
        }}
    ]
)

Answer 2

对于更复杂的bigdats，这将不必要地困难。只需在$ filter输入中添加点注释字段即可对其进行编辑。您可以通过点注释将文档搜索到JSON的任何深度，而无需进一步复杂的$ filter映射。

"$filter":{
       "input": "$feeClassifications._trashed",
       "as": "trashed",
       "cond": { "$lt": [ "$$trashed._trashed", 0 ] }                           
 }

Nested filters: $filter array, then $filter child array

2 个答案: