Mongodb Interval Query - mongodb

Question

I have a mongodb database with a collection user_arrival. The documents look like:
{
"_id" : ObjectId("5e0431821d0f986bdb338e82"),
"location" : {
"uuid" : "b8e671f3-742e-4a24-ae3e-6cd543e7c5bb",
"name" : "London"
},
"time" : ISODate("2019-12-16T16:37:45.000Z"),
"actor" : {
"user" : {
"uuid" : "c42f7cbf-84a6-4912-b414-6afc873e229d",
"name" : "User 1"
}
}
},
{
"_id" : ObjectId("5e0431d31d0f986bdb338e83"),
"location" : {
"uuid" : "b8e671f3-742e-4a24-ae3e-6cd543e7c5bb",
"name" : "London"
},
"time" : ISODate("2019-12-16T17:00:00.000Z"),
"actor" : {
"user" : {
"uuid" : "c42f7cbf-84a6-4912-b414-6afc873e229d",
"name" : "User 1"
}
}
},
{
"_id" : ObjectId("5e0431e41d0f986bdb338e84"),
"location" : {
"uuid" : "b8e671f3-742e-4a24-ae3e-6cd543e7c5bb",
"name" : "London"
},
"time" : ISODate("2019-12-16T17:05:00.000Z"),
"actor" : {
"user" : {
"uuid" : "c42f7cbf-84a6-4912-b414-6afc873e229d",
"name" : "User 1"
}
}
},
{
"_id" : ObjectId("5e04320f1d0f986bdb338e85"),
"location" : {
"uuid" : "b8e671f3-742e-4a24-ae3e-6cd543e7c5bb",
"name" : "London"
},
"time" : ISODate("2019-12-16T17:06:00.000Z"),
"actor" : {
"user" : {
"uuid" : "d42f7cbf-84a6-4912-b414-6afc873e229d",
"name" : "User 2"
}
}
},
{
"_id" : ObjectId("5e0432191d0f986bdb338e86"),
"location" : {
"uuid" : "b8e671f3-742e-4a24-ae3e-6cd543e7c5bb",
"name" : "London"
},
"time" : ISODate("2019-12-16T17:15:00.000Z"),
"actor" : {
"user" : {
"uuid" : "d42f7cbf-84a6-4912-b414-6afc873e229d",
"name" : "User 2"
}
}
}
According to above documents
User 1 - First-time card scan at 16:37:45
User 1 - Second-time card scan at 17:00:00
User 1 - Third-time card scan at 17:05:00
User 2 - First-time card scan at 17:06:00
User 2 - Second-time card scan at 17:15:00
Mongodb Group Query
db.getCollection('test').aggregate([
{
$match: {
time: { $gt: new Date('2019-12-16T00:00:00.000Z'), $lte: new Date('2019-12-17T00:00:00.000Z') },
'location.uuid': 'b8e671f3-742e-4a24-ae3e-6cd543e7c5bb',
},
},
{
$group: {
_id: {
hour: { $hour: { date: '$time' } },
minute: {
$subtract: [
{ $minute: { date: '$time'} },
{ $mod: [{ $minute: '$time' }, 60] },
],
},
},
count: { $addToSet: '$actor.user.uuid' },
},
},
{
$project: {
start_time: { $add: ['$_id.hour', 0] },
end_time: { $add: ['$_id.hour', 1] },
total_user_arrivals: { $size: '$count' },
_id: 0,
},
},
])
When I execute the above MongoDB query below results get.
[{
"start_time" : 16.0,
"end_time" : 17.0,
"total_user_arrivals" : 1
},
{
"start_time" : 17.0,
"end_time" : 18.0,
"total_user_arrivals" : 2
}]
Expexted Result
User 1 first-time card scan between 16:00:00 to 17:00:00
User 2 first-time card scan between 17:00:00 to 18:00:00
[{
"start_time" : 16.0,
"end_time" : 17.0,
"total_user_arrivals" : 1
},
{
"start_time" : 17.0,
"end_time" : 18.0,
"total_user_arrivals" : 1
}]

Answer 1

Before grouping, you need to get the first transaction of the users.
db.getCollection('test').aggregate([
{
$match: {
time: { $gt: new Date('2019-12-16T00:00:00.000Z'), $lte: new Date('2019-12-17T00:00:00.000Z') },
'location.uuid': 'b8e671f3-742e-4a24-ae3e-6cd543e7c5bb',
},
},
{ $sort: { time: 1 } },
{
$group: {
_id: {
uuid: '$actor.user.uuid',
},
tran: { $first: '$$ROOT' },
},
},
{
$group: {
_id: {
hour: { $hour: { date: '$tran.time' } },
minute: {
$subtract: [
{ $minute: { date: '$tran.time'} },
{ $mod: [{ $minute: '$tran.time' }, 60] },
],
},
},
count: { $addToSet: '$tran.actor.user.uuid' },
},
},
{
$project: {
start_time: { $add: ['$_id.hour', 0] },
end_time: { $add: ['$_id.hour', 1] },
total_user_arrivals: { $size: '$count' },
_id: 0,
},
},
])