我正在看一个教程,我可以理解这个聚合是如何工作的,pings
和$$ROOT
在其中的用途是什么。
client = pymongo.MongoClient(MY_URL)
pings = client['mflix']['watching_pings']
cursor = pings.aggregate([
{
"$sample": { "size": 50000 }
},
{
"$addFields": {
"dayOfWeek": { "$dayOfWeek": "$ts" },
"hourOfDay": { "$hour": "$ts" }
}
},
{
"$group": { "_id": "$dayOfWeek", "pings": { "$push": "$$ROOT" } }
},
{
"$sort": { "_id": 1 }
}
]);
发布于 2020-05-16 15:15:53
让我们假设我们的集合如下所示:
{
"_id" : ObjectId("b9"),
"key" : 1,
"value" : 20,
"history" : ISODate("2020-05-16T00:00:00Z")
},
{
"_id" : ObjectId("ba"),
"key" : 1,
"value" : 10,
"history" : ISODate("2020-05-13T00:00:00Z")
},
{
"_id" : ObjectId("bb"),
"key" : 3,
"value" : 50,
"history" : ISODate("2020-05-12T00:00:00Z")
},
{
"_id" : ObjectId("bc"),
"key" : 2,
"value" : 0,
"history" : ISODate("2020-05-13T00:00:00Z")
},
{
"_id" : ObjectId("bd"),
"key" : 2,
"value" : 10,
"history" : ISODate("2020-05-16T00:00:00Z")
}
现在,基于要分组的history
字段,将整个文档插入到一个数组字段'items‘中。这里的$$ROOT
变量会很有帮助。
因此,实现上述功能的聚合查询将是:
db.collection.aggregate([{
$group: {
_id: '$history',
items: {$push: '$$ROOT'}
}
}])
它将导致以下输出:
{
"_id" : ISODate("2020-05-12T00:00:00Z"),
"items" : [
{
"_id" : ObjectId("bb"),
"key" : 3,
"value" : 50,
"history" : ISODate("2020-05-12T00:00:00Z")
}
]
},
{
"_id" : ISODate("2020-05-13T00:00:00Z"),
"items" : [
{
"_id" : ObjectId("ba"),
"key" : 1,
"value" : 10,
"history" : ISODate("2020-05-13T00:00:00Z")
},
{
"_id" : ObjectId("bc"),
"key" : 2,
"value" : 0,
"history" : ISODate("2020-05-13T00:00:00Z")
}
]
},
{
"_id" : ISODate("2020-05-16T00:00:00Z"),
"items" : [
{
"_id" : ObjectId("b9"),
"key" : 1,
"value" : 20,
"history" : ISODate("2020-05-16T00:00:00Z")
},
{
"_id" : ObjectId("bd"),
"key" : 2,
"value" : 10,
"history" : ISODate("2020-05-16T00:00:00Z")
}
]
}
我希望它能帮上忙。
发布于 2020-05-16 15:15:53
$$ROOT是一个变量,它包含组的源文档
https://stackoverflow.com/questions/61804268
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