I am trying to get the sum of count which I get from group, match. How can I get the same.
I have this code...
VisitorCompany.aggregate(
[
{
$match: {
$and:[
{ entry_date: { $gt: start, $lt: end } }
]
}
},
{
$group:
{
_id:
{
day: { $dayOfMonth: "$entry_date" },
month: { $month: "$entry_date" },
year: { $year: "$entry_date" }
},
count: { $sum:1 },
entry_date: { $first: "$entry_date" }
}
},
{
$project:
{
entry_date:
{
$dateToString: { format: "%Y-%m-%d", date: "$entry_date" }
},
count: 1,
_id: 0
}
},
{ $sort : { entry_date : -1 } },
])
and the output is ...
{
"count": 2,
"entry_date": "2018-12-12"
},
{
"count": 1
"entry_date": "2018-12-11"
}
Is anyone have idea that how to get sum of count i.e. 3 (2+1), means total number of records before group. thanks in advance.
Below modified query of yours will be giving you the sum of count, I have just added the
$group:{_id:"", sum:{$sum: "$count"}}}
to the existing aggregation pipeline query
Modified query
VisitorCompany.aggregate(
[
{
$match: {
$and:[
{ entry_date: { $gt: start, $lt: end } }
]
}
},
{
$group:
{
_id:
{
day: { $dayOfMonth: "$entry_date" },
month: { $month: "$entry_date" },
year: { $year: "$entry_date" }
},
count: { $sum:1 },
entry_date: { $first: "$entry_date" }
}
},
{
$project:
{
entry_date:
{
$dateToString: { format: "%Y-%m-%d", date: "$entry_date" }
},
count: 1,
_id: 0
}
},
{ $sort : { entry_date : -1 } },
{$group:{_id:"", sum:{$sum: "$count"}}}
])
The result
{ "_id" : "", "sum" : 3 }
Related
My records like this [{ createdAt }, {createdAt}, {createdAt} ]
I need average records per month.
january => 3 records
february => 2 records etc..
You can try to $group by month and year when counting and by month when averaging:
db.collection.aggregate([
{
$group: {
_id: {
month: {
$month: "$createdAt"
},
year: {
$year: "$createdAt"
},
},
count: {
$sum: 1
}
}
},
{
$group: {
_id: {
month: "$_id.month"
},
average: {
$avg: "$count"
}
}
},
{
$project: {
_id: 0,
month: "$_id.month",
average: 1
}
}
])
Link to playground
Not fully clear what you mean by "average records per month" but I think it would be this:
db.collection.aggregate([
{
$group: {
_id: {
$dateTrunc: {
date: "$createdAt",
unit: "month"
}
},
count: { $count: {} }
}
},
{
$group: {
_id: null,
data: { $push: { k: { $toString: { $month: "$_id" } }, v: "$count" } }
}
},
{ $replaceWith: { $arrayToObject: "$data" } }
])
Getting the month name is not so easy, either you use a external library or build your own with $switch
Q1. I need to filter data by created date and driverId then need to sum up the total by Hourly, Weekly, Monthly, and Yearly. I already checked with other solutions but it doesn't help much.
Sample Data:
[
{
id: "1",
created : "2022-01-04T03:22:18.739Z",
completed: "2022-01-06T03:53:28.463Z",
driverId: "B-72653",
total: 15,
},
{
id: "2",
created : "2022-01-01T03:22:18.739Z",
completed: "2022-01-02T03:53:28.463Z",
driverId: "B-72653",
total: 33
},
{
id: "3",
created : "2021-08-26T01:22:18.739Z",
completed: "2021-08-26T09:53:28.463Z",
driverId: "B-72653",
total: 43
},
{
id: "4",
created : "2021-03-26T02:22:18.739Z",
completed: "2021-03-26T07:53:28.463Z",
driverId: "B-73123",
total: 35
},
]
Response needed:
{
Hourly:[10,5,5,6,7,8,4,5,6,3,44,2,1,2,3,44,5,6,75,4,3,2,1], // 24 Hours (Each Hour Total)
Weekly:[10,30,34,45,56,67,78], // 7 days (Each Day Total)
Monthly:[10,30,34,45,56,67,78,55,44,33,22,12], // 12 Months (Each Month Total)
Yearly: [10,30] // Year Total (Each Year Total)
}
Q2. How can we filter nested array by-products > brand id and get the sum of product price by its id and filter by Hourly, Weekly, Monthly, Yearly?.
You can use $group with _id being $hour / $week / $month / $year to aggregate the sum. $push them into an array to get your expected result.
Use $facet to repeat the process for all 4 cases.
db.collection.aggregate([
{
"$facet": {
"Hourly": [
{
$group: {
_id: {
$hour: "$created"
},
total: {
$sum: "$total"
}
}
},
{
$sort: {
_id: 1
}
},
{
$group: {
_id: null,
result: {
$push: {
hour: "$_id",
total: "$total"
}
}
}
}
],
Weekly: [
{
$group: {
_id: {
"$week": "$created"
},
total: {
$sum: "$total"
}
}
},
{
$sort: {
_id: 1
}
},
{
$group: {
_id: null,
result: {
$push: {
week: "$_id",
total: "$total"
}
}
}
}
],
Monthly: [
{
$group: {
_id: {
$month: "$created"
},
total: {
$sum: "$total"
}
}
},
{
$sort: {
_id: 1
}
},
{
$group: {
_id: null,
result: {
$push: {
month: "$_id",
total: "$total"
}
}
}
}
],
Yearly: [
{
$group: {
_id: {
$year: "$created"
},
total: {
$sum: "$total"
}
}
},
{
$sort: {
_id: 1
}
},
{
$group: {
_id: null,
result: {
$push: {
year: "$_id",
total: "$total"
}
}
}
}
]
}
},
{
"$addFields": {
"Hourly": {
"$arrayElemAt": [
"$Hourly",
0
]
},
"Weekly": {
"$arrayElemAt": [
"$Weekly",
0
]
},
"Monthly": {
"$arrayElemAt": [
"$Monthly",
0
]
},
"Yearly": {
"$arrayElemAt": [
"$Yearly",
0
]
}
}
},
{
"$addFields": {
"Hourly": "$Hourly.result",
"Weekly": "$Weekly.result",
"Monthly": "$Monthly.result",
"Yearly": "$Yearly.result"
}
}
])
Here is the Mongo playground for your reference.
let pipeline = [{
$match: {
time: { $gt: 980985600 },
user_id: mongoose.Types.ObjectId("60316a2e7641bd0017ced7b1")
}
},
{
$project: {
newDate: { '$toDate': "$time" },
user_id: '$user_id'
}
},
{
$group: {
_id: { week: { $week: "$newDate" }, year: { $year: "$newDate" }},
count: { $sum: 1 }
}
}]
I am currently trying to perform an aggregate through mongoose to find the average logins per week for a specific user. So far I have been able to get to the total number of logins each week, but was curious if there was a way to find the average of these final groupings within the same function. How would I go about doing this?
Just add one last stage to your query:
{
$group: {
_id: null,
avg: { $avg: "$count" }
}
}
So try this:
let pipeline = [
{
$match: {
time: { $gt: 980985600 },
user_id: mongoose.Types.ObjectId("60316a2e7641bd0017ced7b1")
}
},
{
$project: {
newDate: { '$toDate': "$time" },
user_id: '$user_id'
}
},
{
$group: {
_id: { week: { $week: "$newDate" }, year: { $year: "$newDate" } },
count: { $sum: 1 }
}
},
{
$group: {
_id: null,
avg: { $avg: "$count" }
}
}
];
I have a pipeline that gives me the result according to the players belonging to a certain company in a daily, weekly, and monthly manner. I have a date filter in the dashboard which gives an iso date range. I want to limit or range my results according to the date filter? is there any way to do it in the pipeline?
if (chartType === 'Daily') {
statsPipelineCondition = {
_id: { day: { $dayOfMonth: '$createdAt' }, month: { $month: '$createdAt' }, year: { $year: '$createdAt' } },
};
sortCondition = { '_id.year': 1, '_id.month': 1, '_id.day': 1 };
} else if (chartType === 'Monthly') {
statsPipelineCondition = {
_id: { month: { $month: '$createdAt' }, year: { $year: '$createdAt' } },
};
sortCondition = { '_id.year': 1, '_id.month': 1 };
} else {
statsPipelineCondition = {
_id: { week: { $week: '$createdAt' }, year: { $year: '$createdAt' } },
};
sortCondition = { '_id.year': 1, '_id.week': 1 };
}
const statsPipeline = [
{
$group: {
...statsPipelineCondition,
TOTAL: { $sum: 1 },
XR: { $sum: { $cond: [{ $in: ['$company', ['XR', 'CR', 'DX']] }, 1, 0] } },
CT: { $sum: { $cond: [{ $eq: ['$company', 'CT'] }, 1, 0] } },
MR: { $sum: { $cond: [{ $eq: ['$company', 'MR'] }, 1, 0] } },
MG: { $sum: { $cond: [{ $in: ['$company', ['NM', 'MM', 'MG']] }, 1, 0] } },
},
},
{
$sort: {
...sortCondition,
},
},
];
Date filter:
datefilter - { '$gte': '2020-09-01T04:49:50.899Z',
'$lte': '2020-11-03T04:49:50.899Z' }
You need to add a $match stage prior to the $group stage to filter our based on the range:
let datefilter = {
'$gte': new Date('2020-09-01T04:49:50.899Z'),
'$lte': new Date('2020-11-03T04:49:50.899Z')
};
const statsPipeline = [
{
$match: {
createdAt: datefilter
}
},
{
$group: {
...statsPipelineCondition,
TOTAL: { $sum: 1 },
XR: { $sum: { $cond: [{ $in: ['$company', ['XR', 'CR', 'DX']] }, 1, 0] } },
CT: { $sum: { $cond: [{ $eq: ['$company', 'CT'] }, 1, 0] } },
MR: { $sum: { $cond: [{ $eq: ['$company', 'MR'] }, 1, 0] } },
MG: { $sum: { $cond: [{ $in: ['$company', ['NM', 'MM', 'MG']] }, 1, 0] } },
},
},
{
$sort: {
...sortCondition,
},
},
];
Okay, So for some reason. MongoDB doesn't like dates in strings. It would be much better if we just convert the strings by an operator provided by the aggregation framework and this will make the things work.
{
$match: {
$expr: {
$and: [
{
$gte: [
'$createdAt',
{
$dateFromString: {
dateString: dateFilter.$gte,
},
},
],
},
{
$lte: [
'$createdAt',
{
$dateFromString: {
dateString: dateFilter.$lte,
},
},
],
},
],
},
},
},
I have documents like these:
{
"_id" : ObjectId("5cc80389c723e046f504b5a9"),
"adddress" : "string",
"checkIn" : "2019-04-30T08:12:57.909Z"
},
{
"_id" : ObjectId("5cc995f5a6f3eb7c483b019f"),
"adddress" : "string",
"checkIn" : "2019-05-01T12:49:57.561Z"
}
I have tried aggrgation like this:
var start = new Date("2019-04-30T08:12:57.909Z");
var end = new Date("2019-05-01T12:49:57.561Z");
var pipeline = [
{
$match: {
checkIn: {
$gte: start,
$lte: end
}
}
},
{
$group: {
_id: {
year: {
$year: "$checkIn"
},
month: {
$month: "$checkIn"
},
day: {
$dayOfYear: "$checkIn"
}
},
count: {
$sum: 1
}
}
}];
db.collections.aggregate(pipeline).toArray()
Is it possible to count them by checkIn date and get result like this:
"_id": [{
"checkIn": "2019-03-15T00:00:00Z",
"count": 4
}, {
"checkIn": "2019-04-30T00:00:00Z",
"count": 1
}, {
"checkIn": "2019-05-10T00:00:00Z",
"count": 1
}],
The result is shown the total number of the day.
{$project: {
checkIn: { $dateToString: { format: '%Y-%m-%d', date: '$checkIn' } }
}},
{$group: {
_id: '$checkIn',
checkIn: {$first: '$checkIn'},
count: {$sum: 1}
}},
{$sort: {checkIn: 1}}
Try this: I have tested this query and its working.
db.sample.aggregate([{
$addFields: {
date: {
$dateFromString: {
dateString: "$checkIn"
}
}
}
},{
$match: {
date: {
$gte: start,
$lte: end
}
}
},
{
$addFields: {
dateString: {
$dateToString: {
format: "%Y-%m-%d",
date: "$date"
}
}
}
},
{
$group: {
_id: "$dateString",
count: {
$sum: 1
}
}
}
]);