问题描述
我的问题是,我在下面有一个集合,_id被忽略了
My problem is that, i have a collection below, _id is ignored
{ "value" : -10, "r" : [ { "v" : 1 }, { "v" : 3 } ] }
{ "value" : 2, "r" : [ { "v" : 4 }, { "v" : 1 } ] }
{ "value" : -100, "r" : [ { "v" : 4 }, { "v" : 1 }, { "v" : 10 } ] }
{ "value" : -3, "r" : [ ] }
然后我要根据数组r的最后一个值对它进行排序,也就是说,我想在下面得到一个结果,
And i what to sort it by the last value of array r, that is to say, i want to have a result below,
{ "value" : -3, "r" : [ ] } # this one should be either the first one or the last one
{ "value" : 2, "r" : [ { "v" : 4 }, { "v" : 1 } ] }
{ "value" : -10, "r" : [ { "v" : 1 }, { "v" : 3 } ] }
{ "value" : -100, "r" : [ { "v" : 4 }, { "v" : 1 }, { "v" : 10 } ] }
我知道我可以按数组r的第一个值排序
I know that i can sort by the first vaue of the array r by
db.my.find().sort({'r.0.v': 1})
但是怎么才能用最后的值呢?
But how can do it by the last value?
并且,如果使用下面的mongoengine模型
And, if with its mongoengine model below
class V(EmbeddedDocument):
v = IntField()
class M(Document):
value = IntFiled
r = ListField(EmbeddedDocumentField(V))
我应该如何使用mongoengine? IntField
可能还有其他字段,例如DateTimeField
,StringField
...
How should i do with mongoengine? IntField
maybe other fields such as DateTimeField
, StringField
...
谢谢
推荐答案
如果可能的话,我建议您总是(双重)存储要排序的值.将其放在数组和第二个字段中.每当将新值推送到数组(或存储数组)时,都添加一个与数组中的最后一个值"相对应的新字段,然后对其进行索引和排序.在下面的示例中,我将其命名为lastR
:
If possible, I'd suggest you just always (double) store the value you want to sort on. Put it in the array and in a second field. Whenever you push a new value to the array (or store the array), add a new field corresponding to the "last value in array" and then index and sort on that. In the example below, I called it lastR
:
{ "value" : -10, "r" : [ { "v" : 1 }, { "v" : 3 } ], "lastR": 3 }
{ "value" : 2, "r" : [ { "v" : 4 }, { "v" : 1 } ], "lastR": 1 }
{ "value" : -100, "r" : [ { "v" : 4 }, { "v" : 1 }, { "v" : 10 } ], "lastR": 10 }
{ "value" : -3, "r" : [ ] }
创建索引:
db.so.ensureIndex({lastR: 1})
然后使用:
> db.so.find().sort({lastR: 1})
{ "_id" : ObjectId("5203a1c83c5438af60de63a1"), "value" : -3, "r" : [ ] }
{ "_id" : ObjectId("5203a1ad3c5438af60de639f"), "value" : 2, "r" : [ { "v" : 4 }, { "v" : 1 } ], "lastR" : 1 }
{ "_id" : ObjectId("5203a1d33c5438af60de63a2"), "value" : -10, "r" : [ { "v" : 1 }, { "v" : 3 } ], "lastR" : 3 }
{ "_id" : ObjectId("5203a1b73c5438af60de63a0"), "value" : -100, "r" : [ { "v" : 4 }, { "v" : 1 }, { "v" : 10 } ], "lastR" : 10 }
与尝试使用聚合解决方案相比,它将具有更多的用途和可扩展性(聚合解决方案的结果集将有16MB的限制,并且在需要处理投影时检索复杂的文档要复杂得多).
It will be far more versatile and expandable than trying to use an aggregation solution (which will have a 16MB limit to the result set and makes it far more complex to retrieve complex documents when needing to deal with a projection).
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