MongoDB: aggregate and group by splitting the id - mongodb

Question

My schema implementation is influenced from this tutorial on official mongo site
{
_id: String,
data:[
{
point_1: Number,
ts: Date
}
]
}
This is basically schema designed for time series data and I store data for each hour per device in an array in a single document. I create _id field combining device id which is sending the data and time. For example if a device having id xyz1234 sends a data at 2018-09-11 12:30:00 then my _id field becomes xyz1234:2018091112.
I create new doc if the document for that hour for that device doesn't exist otherwise I just push my data to the data array.
client.db('iot')
.collection('iotdata')
.update({_id:id},{$push:{data:{point_1,ts:date}}},{upsert:true});
Now I am facing problem while doing aggregation. I am trying to get these types of values
Min point_1 value for many devices in last 24 hours by grouping on device id
Max point_1 value for many devices in last 24 hours by grouping on device id
Average point_1 for many devices in last 24 hours by grouping on device id
I thought this is very simple aggregation then I realized device id is not direct but mixed with time data so it's not so direct to group data by device id. How can I split the _id and group based on device id? I tried my level best to write the question as clearly as possible so please ask questions in comments if any part of the question is not clear.

Answer 1

You can start with $unwind on data to get single document per entry. Then you can get deviceId using $substr and $indexOfBytes operators. Then you can apply your filtering condition (last 24 hours) and use $group to get min, max and avg
db.col.aggregate([
{
$unwind: "$data"
},
{
$project: {
point_1: "$data.point_1",
deviceId: { $substr: [ "$_id", 0, { $indexOfBytes: [ "$_id", ":" ] } ] },
dateTime: "$data.ts"
}
},
{
$match: {
dateTime: { $gte: ISODate("2018-09-10T12:00:00Z") }
}
},
{
$group: {
_id: "$deviceId",
min: { $min: "$point_1" },
max: { $max: "$point_1" },
avg: { $avg: "$point_1" }
}
}
])

Answer 2

You can use below query in 3.6.
db.colname.aggregate([
{"$project":{
"deviceandtime":{"$split":["$_id", ":"]},
"minpoint":{"$min":"$data.point_1"},
"maxpoint":{"$min":"$data.point_1"},
"sumpoint":{"$sum":"$data.point_1"},
"count":{"$size":"$data.point_1"}
}},
{"$match":{"$expr":{"$gte":[{"$arrayElemAt":["$deviceandtime",1]},"2018-09-10 00:00:00"]}}},
{"$group":{
"_id":{"$arrayElemAt":["$deviceandtime",0]},
"minpoint":{"$min":"$minpoint"},
"maxpoint":{"$max":"$maxpoint"},
"sumpoint":{"$sum":"$sumpoint"},
"countpoint":{"$sum":"$count"}
}},
{"$project":{
"minpoint":1,
"maxpoint":1,
"avgpoint":{"$divide":["$sumpoint","$countpoint"]}
}}
])