How to filter and aggregate data from one collection into another format using MongoDB - mongodb

Question

I have one collection named 'ctrlcharts'.
e.g.
{
"_id" : ObjectId("57fc695492af567031246736"),
"deviceId" : "A001",
"sensorId" : "S003",
"time" : "2016/10/11 12:23:50",
"charts" : [
{
"sensor" : "ch_11",
"value" : 120
},
{
"sensor" : "ch_12",
"value" : 150
}
]
}
How to filter "sensor" : "ch_11" and aggregate data from one collection into another format using MongoDB
e.g.
{
"time" : "2016/10/11 12:23:50",
"sensor" : "ch_12",
"value" : 150
}
I tried below code
db.ctrlcharts.aggregate([
{ $match: {"deviceId" : "A001", "sensorId" : "S003", "time" : "2016/10/11 12:23:50"}},
{ $project: {
_id: 0,
time : 1 ,
sensor : "$charts.sensor"
value : "$charts.value"
}
}
])
But I got the result as
{
"time" : "2016/10/11 12:23:50",
"sensor" : ["ch_11","ch_12"],
"value" : [120,150]
}
Thanks

Answer 1

You tried best....just use $unwind
db.ctrlcharts.aggregate(
{$unwind:"$charts"},
{$match: {"deviceId" :"A001", "charts.sensor":"ch_12", "time" : "2016/10/11 12:23:50"}},
{$project:{_id:0,time:1, sensor : "$charts.sensor", value :"$charts.value"}}).pretty()

Answer 2

You can use $unwind (aggregation) to separate charts array.
db.ctrlcharts.aggregate( [ { $unwind : "$charts" } ] )
This will produce result like -
{ "_id" : ObjectId("57ff397a007c43ecacf10512"), "deviceId" : "A001", "sensorId" : "S003", "time" : "2016/10/11 12:23:50", "charts" : { "sensor" : "ch_11", "value" : 120 } }
{ "_id" : ObjectId("57ff397a007c43ecacf10512"), "deviceId" : "A001", "sensorId" : "S003", "time" : "2016/10/11 12:23:50", "charts" : { "sensor" : "ch_12", "value" : 150 } }
and then use your match query

Answer 3

Use the $arrayElemAt and $filter operators to query the array more efficiently without the need to $unwind. The reason why $unwind is not as efficient is that it produces a cartesian product of the documents i.e. a copy of each document per array entry, which uses more memory (possible memory cap on aggregation pipelines of 10% total memory) and therefore takes time to produce as well processing the documents during the flattening process.
The $filter will return a subset of the array that only contains the elements that match the filter condition. The $arrayElemAt operator then returns the element from the filtered array at the specified array index to give you the subdocument you need.
A further $project is necessary to flatten the fields to give you the desired result:
db.ctrlcharts.aggregate([
{ "$match": {
"deviceId": "A001",
"sensorId": "S003",
"time": "2016/10/11 12:23:50",
"charts.sensor": "ch_11"
} },
{
"$project": {
"time": 1,
"chart": {
"$arrayElemAt": [
"$filter": {
"input": "$charts",
"as": "item",
"cond": { "$eq": ["$$item.sensor", "ch_11"] }
}, 0
]
}
}
},
{
"$project": {
"_id": 0,
"time": 1,
"sensor": "$chart.sensor"
"value": "$chart.value"
}
}
])