I'm trying to create charts but I can't combine the data to be like "Expected result below"
What can I use to return "Expected result".
I tried using $group in $group and $reduce and it didn't work well.
I hope someone can help me solve this task
Current result is
[
{
"_id":"5fd4c3586e83b334d97c5218",
"consumption":5,
"charts":[
{
"date":"2020-10",
"consumption":1
},
{
"date":"2020-10",
"consumption":1
},
{
"date":"2020-11",
"consumption":1
},
{
"date":"2020-11",
"consumption":1
}
]
}
]
Expected result is
[
{
"_id":"5fd4c3586e83b334d97c5218",
"consumption":5,
"charts":[
{
"date":"2020-10",
"consumption":2
},
{
"date":"2020-11",
"consumption":2
},
}
]
You need to go with aggregations
db.collection.aggregate([
{ $unwind: "$charts" },
{
$group: {
_id: { _id: "$_id", month: "$charts.date.month", year: "$charts.date.year" },
consumption: { $first: "$consumption" },
total: { $sum: "$charts.consumption" },
date: { $first: "$charts.date" }
}
},
{
$group: {
_id: "$_id._id",
consumption: { $first: "$consumption" },
charts: {
$push: {
date: "$date",
consumption: "$total"
}
}
}
}
])
Working Mongo playground
Related
I have below data in my collection:
[
{
"_id":{
"month":"Jan",
"year":"2022"
},
"products":[
{
"product":"ProdA",
"status":"failed",
"count":15
},
{
"product":"ProdA",
"status":"success",
"count":5
},
{
"product":"ProdB",
"status":"failed",
"count":20
},
{
"product":"ProdB",
"status":"success",
"count":10
}
]
},
...//more such data
]
I want to group the elements of products array on the name of the product, so that we have record of how what was the count of failure of success of each product in each month. Every record is guaranteed to have both success and failure count each month. The output should look like below:
[
{
"_id":{
"month":"Jan",
"year":"2022"
},
"products":[
{
"product":"ProdA","status":[{"name":"success","count":5},{"name":"failed","count":15}]
},
{
"product":"ProdB","status":[{"name":"success","count":10},{"name":"failed","count":20}]
}
]
},
...//data for succeeding months
]
I have tried to do something like this:
db.collection.aggregate([{ $unwind: "$products" },
{
$group: {
"_id": {
month: "$_id.month",
year: "$_id.year"
},
products: { $push: { "product": "$product", status: { $push: { name: "$status", count: "$count" } } } }
}
}]);
But above query doesn't work.
On which level I need to group fields so as to obtain above output.
Please help me to find out what I am doing wrong.
Thank You!
Your first group stage needs to group by both the _id and the product name, aggregate a list of status counts and then another group stage which then forms the products list:
db.collection.aggregate([
{$unwind: "$products"},
{$group: {
_id: {
id: "$_id",
product: "$products.product",
},
status: {
$push: {
name: "$products.status",
count: "$products.count"
}
}
}
},
{$group: {
_id: "$_id.id",
products: {
$push: {
product: "$_id.product",
status: "$status"
}
}
}
}
])
Mongo Playground
I am using Mongo daily bucketing pattern. Each daily document contains an array with value calculated for every hour for that day:
{
meter: 'meterId',
date: 'dailyBucket',
hourlyConsumption: [0,0,1,1,1,2,2,2,4,4,4,4,3,3,3...] // array with 24 values for every hour of a day
}
Now in one of my aggregation queries, I would like to group documents for the same day of multiple meters and get a result like this:
INPUT (consumption of multiple meters in a same day)
{
meter: 'MeterA',
date: '2021-05-01',
hourlyConsumption: [0,0,1,1,1,2,2,2,4,4,4,4,3,3,3...]
},
{
meter: 'MeterB',
date: '2021-05-01',
hourlyConsumption: [10,10,10,10,10,10,10,10,10,10,10,10,10,10,10...]
}
RESULT (combined into single document)
{
date: '2021-05-01',
hourlyConsumption: [10,10,11,11,11,12,12,12,14,14,14,14,13,13,13...]
}
is there a way to achieve this without using $accumulator?
You can use $reduce
db.collection.aggregate([
{
$group: {
_id: "$date",
hourlyConsumption: { $push: "$hourlyConsumption" }
}
},
{
$set: {
hourlyConsumption: {
$reduce: {
input: "$hourlyConsumption",
initialValue: [],
in: { $map: { input: { $range: [ 0, 23 ] },
as: "h",
in: {
$sum: [
{ $arrayElemAt: [ "$$value", "$$h" ] },
{ $arrayElemAt: [ "$$this", "$$h" ] }
]
}
}
}
}
}
}
}
])
Mongo Playground
Or you use $unwind and $group:
db.collection.aggregate([
{
$unwind: {
path: "$hourlyConsumption",
includeArrayIndex: "hour"
}
},
{
$group: {
_id: {
date: "$date",
hour: "$hour"
},
hourlyConsumption: { $sum: "$hourlyConsumption" }
}
},
{ $sort: { "_id.hour": 1 } },
{
$group: {
_id: "$_id.date",
hourlyConsumption: { $push: "$hourlyConsumption" }
}
}
])
Mongo Playground
However, when you use $unwind, then you actually contradict your bucketing design pattern.
This is my first experience using aggregate pipeline. I'm not able to get a "$match" expression to work inside the pipeline. If I remove the "_id" match, I get every document in the collection past the start date, but once I add the $eq expression, it returns empty.
I read a lot of other examples and tried many different ways, and this seems like it is correct. But the result is empty.
Any suggestions?
let now = new Date()
let doc = await Team.aggregate([
{ $match: { created_by: mongoose.Types.ObjectId(req.params.user_oid)} },
{ $sort: { create_date: 1 } },
{ $lookup: {
from: 'events',
let: { "team_oid": "$team_oid" },
pipeline: [
{ $addFields: { "team_oid" : { "$toObjectId": "$team_oid" }}},
{ $match: {
$expr: {
$and: [
{ $gt: [ "$start", now ] },
{ $eq: [ "$_id", "$$team_oid" ] }
]
},
}
},
{
$sort: { start: 1 }
},
{
$limit: 1
}
],
as: 'events',
}},
{
$group: {
_id: "$_id",
team_name: { $first: "$team_name" },
status: { $first: "$status" },
invited: { $first: "$invited" },
uninvited: { $first: "$uninvited" },
events: { $first: "$events.action" },
dates: { $first: "$events.start" } ,
team_oid: { $first: "$events.team_oid" }
}
}])
Example Docs (added by request)
Events:
_id:ObjectId("60350837c57b3a15a414d265")
invitees:null
accepted:null
sequence:7
team_oid:ObjectId("60350837c57b3a15a414d263")
type:"Calendar Invite"
action:"Huddle"
status:"Questions Issued"
title:"Huddle"
body:"This is a Huddle; you should receive new questions 5 days befor..."
creator_oid:ObjectId("5ff9e50a206b1924dccd691e")
start:2021-02-26T07:00:59.999+00:00
end:2021-02-26T07:30:59.999+00:00
__v:0
Team:
_id:ObjectId("60350837c57b3a15a414d263")
weekly_schedule:1
status:"Live"
huddle_number:2
reminders:2
active:true
created_by:ObjectId("5ff9e50a206b1924dccd691e")
team_name:"tESTI"
create_date:2021-02-23T13:50:47.172+00:00
__v:0
This is just a guess since you don't have schema in your question. But it looks like your have some of your _ids mixed up. Where you are currently trying to $match events whose _id is equal to a team_oid. Rather than the event's team_oid field being equal to the current 'team' _id.
I'm pretty confident this will produce the correct output. If you post any schema or sample docs I will edit it.
https://mongoplayground.net/p/5i1w2Ii7KCR
let now = new Date()
let doc = await Team.aggregate([
{ $match: { created_by: mongoose.Types.ObjectId(req.params.user_oid)} },
{ $sort: { create_date: 1 } },
{ $lookup: {
from: 'events',
// Set tea_oid as the current team _id
let: { "team_oid": "$_id" },
pipeline: [
{ $match: {
$expr: {
$and: [
{ $gt: [ "$start", now ] },
// Match events whose 'team_oid' field matches the 'team' _id set above
{ $eq: [ "$team_oid", "$$team_oid" ] }
]
},
}
},
{
$sort: { start: 1 }
},
{
$limit: 1
}
],
as: 'events',
}},
{
$group: {
_id: "$_id",
team_name: { $first: "$team_name" },
status: { $first: "$status" },
invited: { $first: "$invited" },
uninvited: { $first: "$uninvited" },
events: { $first: "$events.action" },
dates: { $first: "$events.start" } ,
team_oid: { $first: "$events.team_oid" }
}
}])
Hey i need to get the sum of all totalPrice group by days
I get this result
but i need to fetch all rest days of month even if it returns 0
i need solution
this is my code
Order.aggregate([
{ $project: { yearMonthDay: { $dateToString: { format: "%Y-%m-%d", date: '$created' }}, totalPrice:"$totalPrice" }},
{ $group: { _id: "$yearMonthDay", count: { $sum: 1 }, total: {"$sum": "$totalPrice"} }},
{ $sort: { _id: -1 } },
{ $group: { _id: null, stats: { $push: "$$ROOT" }}},
{
$project: {
results: {
$map: {
input:{ $range:[16,31] },
as: 'day',
in: {
$let: {
vars: {
dateIndex: {
"$indexOfArray": ["$stats._id", {$dateToString:{ date:{$dateFromParts:{'year':2020, 'month':5, 'day':"$$day"}}, format:'%Y-%m-%d'}}]
}
},
in: {
$cond: {
if: { $ne: ["$$dateIndex", -1] },
then: { $arrayElemAt: ["$stats", "$$dateIndex"] },
else: { _id: {$dateToString:{ date:{$dateFromParts:{'year':2020, 'month':5, 'day':"$$day"}}, format:'%Y-%m-%d'}, count: 0, total: 0 } }
}
}
}
}
}
}
}
},
{ $unwind: "$results" },
{ $replaceRoot: { newRoot: "$results"}}
]
This query should work for you.
db.collectionName.aggregate([
{ $project: { yearMonthDay: { $dateToString: { format: "%Y-%m-%d", date: '$created' }}, totalPrice:"$totalPrice" }},
{ $group: { _id: "$yearMonthDay", count: { $sum: 1 }, total: {"$sum": "$totalPrice"} }},
{ $sort: { _id: -1 } },
{ $group: { _id: null, stats: { $push: "$$ROOT" }},
{
$project: {
results: {
$map: {
input: ["2020-05-16","2020-05-15","2020-05-14","2020-05-13","2020-05-12"],
as: "date",
in: {
$let: {
vars: {
dateIndex: {
"$indexOfArray": ["$stats._id", "$$date"]
}
},
in: {
$cond: {
if: { $ne: ["$$dateIndex", -1] },
then: { $arrayElemAt: ["$stats", "$$dateIndex"] },
else: { _id: "$$date", count: 0, total: 0 }
}
}
}
}
}
}
}
},
{ $unwind: "$results" },
{ $replaceRoot: { newRoot: "$results"}}
])
The First 3 steps is same as yours.
{ $group: { _id: null, stats: { $push: "$$ROOT" }} will push previous stage results into an arrray stats which we will use for lookup in later stage.
In last stage, we will create possible date range and iterate over that.
for each key in range.
"$indexOfArray": ["$stats._id", "$$date"] will check if date is present in stats array or not
Then we will use that index to fetch value from stats array otherwise push default values.
As these results are still under results, we will unwind that array and move to root.
If you server version is above 3.6,
we can simplify date range creation part as well. let's initialize input arrays as days using $range.
input:{ $range:[16,31] },
as: 'day'
and modifiy dateIndex part like this
dateIndex: {
"$indexOfArray": ["$stats._id", {$dateToString:{ date:{$dateFromParts:{'year':2020, 'month':5, 'day':"$$day"}}, format:'%Y-%m-%d'}]
}
And change default value part as well similarly.
else: { _id: {$dateToString:{ date:{$dateFromParts:{'year':2020, 'month':5, 'day':"$$day"}}, format:'%Y-%m-%d'}}, count: 0, total: 0 }
Or alternatively, we can also use concat for generating keys
dateIndex: {
"$indexOfArray": ["$stats._id", {$concat:["2020-05","-", {$convert:{input:"$$day", to:"string"}}]}]
}
// And default value
else: { _id: {$concat:["2020-05","-", {$convert:{input:"$$day", to:"string"}}]}, count: 0, total: 0 }
Similarly, you can run another loop for months as well.
I am trying mongoDB for first time. I need to aggregate my data from one collection to another. Trying this code but it doesn't execute because of unexpected error :
"unexpected expression $group"
db.import.aggregate([{
$group: {
_id: {
day: "$Day",
month: "$Month",
year: "$Year"
},
manufacturers: {
$push: {
$group: {
_id: {
manID: "$Man_ID",
man_name: "$Man_Name"
},
types: {
$push: {
model_name: "$Model_name",
body_type: "$Body_type"
}
}
}
}
}
}
},
{ $out: "output_doc" }
], {
allowDiskUse: true,
cursor: {}
});
Expected Output:
["$Day","$Month","$Year",
["$Man_ID","$Man_Name",
["$Model_name","$Body_type"]
]
]
You can just push your new _id field and create your types array without any operator :
db.import.aggregate([{
$group: {
_id: {
day: "$Day",
month: "$Month",
year: "$Year"
},
manufacturers: {
$push: {
_id: {
manID: "$Man_ID",
man_name: "$Man_Name"
},
types: [{ model_name: "$Model_name", body_type: "$Body_type" }]
}
}
}
}])