I'm trying to get the result in some form using mongodb aggregation.
here is my sample document in the collection:
[{
"_id": "34243243243",
"workType": "TESTWORK1",
"assignedDate":ISODate("2021-02-22T00:00:00Z"),
"status":"Completed",
},
{
"_id": "34243243244",
"workType": "TESTWORK2",
"assignedDate":ISODate("2021-02-21T00:00:00Z"),
"status":"Completed",
},
{
"_id": "34243243245",
"workType": "TESTWORK3",
"assignedDate":ISODate("2021-02-20T00:00:00Z"),
"status":"InProgress",
}...]
I need to group last 5 days data in an array by workType count having staus completed.
Expected result:
{_id: "TESTWORK1" , value: [1,0,4,2,3] ,
_id: "TESTWORK2" , value: [3,9,,3,5],
_id : "TESTWORK3", value: [,,,3,5]}
Here is what I'm trying to do, but not sure how to get the expected result.
db.testcollection.aggregate([
{$match:{"status":"Completed"}},
{$project: {_id:0,
assignedSince:{$divide:[{$subtract:[new Date(),$assignedDate]},86400000]},
workType:1
}
},
{$match:{"assignedSince":{"lte":5}}},
{$group : { _id:"workType", test :{$push:{day:"$assignedSince"}}}}
])
result: {_id:"TESTWORK1": test:[{5},{3}]} - here I'm getting the day , but I need the count of the workTypes on that day.
Is there any easy way to do this? Any help would be really appreciated.
Try this:
db.testcollection.aggregate([
{
$match: { "status": "Completed" }
},
{
$project: {
_id: 0,
assignedDate: 1,
assignedSince: {
$toInt: {
$divide: [{ $subtract: [new Date(), "$assignedDate"] }, 86400000]
}
},
workType: 1
}
},
{
$match: { "assignedSince": { "$lte": 5 } }
},
{
$group: {
_id: {
workType: "$workType",
assignedDate: "$assignedDate"
},
count: { $sum: 1 }
}
},
{
$group: {
_id: "$_id.workType",
values: { $push: "$count" }
}
}
]);
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 have a mongodb document that contains customer id, status (active, deactivate) and date.
[
{
id:1,
date:ISODate('2022-12-01'),
status:'activate'
},
{
id:2,
date:ISODate('2022-12-01'),
status:'activate'
},
{
id:1,
date:ISODate('2022-12-02'),
status:'deactivate'
},
{
id:2,
date:ISODate('2022-12-21'),
status:'deactivate'
}
]
I need to get daywise customer status count.
I came up with below aggregation.
db.collection.aggregate([
{
$addFields: {
"day": {
"$dateToString": {
"format": "%Y-%m-%d",
"date": "$date"
}
}
}
},
{
$group: {
_id: "$day",
type: {
$push: "$status"
}
}
}
])
this way I can get status in a array. like below.
[
{
_id:"2022-12-01",
type:[
0:"activate",
1:"activate"
]
},
{
_id:"2022-12-02",
type:[
0:"deactivate"
]
},
{
_id:"2022-12-21",
type:[
0:"deactivate"
]
}
]
now it's working as intended. but I need the output like below.
[
{
_id:"2022-12-01",
type:{
"activate":2,
}
},
{
_id:"2022-12-02",
type:{
"deactivate":1
}
},
{
_id:"2022-12-21",
type:{
"deactivate":1
}
}
]
this table has around 100,000 documents and doing this programmatically will take about 10 seconds. that's why I'm searching a way to do this as a aggregation
One option is to group twice and then use $arrayToObject:
db.collection.aggregate([
{$group: {
_id: {day: "$date", status: "$status"},
count: {$sum: 1}
}},
{$group: {
_id: {$dateToString: {format: "%Y-%m-%d", date: "$_id.day"}},
data: {$push: {k: "$_id.status", v: "$count"}}
}},
{$project: {type: {$arrayToObject: "$data"}}}
])
See how it works on the playground example
There are two collections (view and click) like following:
# View collection
_id publisher_id created_at
617f8ea98e0f54f05e10e796 1 2021-11-01T00:00:00.000Z
617f8eab8e0f54f05e10e798 1 2021-11-01T00:00:00.000Z
617f8eac8e0f54f05e10e79a 1 2021-11-01T00:00:00.000Z
617f90cea187d30ebbecdee9 2 2021-11-01T00:00:00.000Z
# Click collection
_id publisher_id created_at
617f8ea98e0f54f05e10e796 1 2021-11-01T00:00:00.000Z
617f8eab8e0f54f05e10e798 2 2021-11-01T00:00:00.000Z
How can I get the following expected results with one query?
(or)
What is the best way for the following expected results?
# Expected For Publisher ID(1)
_id view_count click_count
2021/11/1 3 1
# Expected For Publisher ID(2)
_id view_count click_count
2021/11/1 1 1
Currently, I am using 2 queries for both collections and combining results as one in code.
For View
db.view.aggregate([
/*FirstStage*/
{
$match:
{
"$and":
[
{
"publisher_id": 1
},
{
"created_at": {$gte: new ISODate("2021-11-01"), $lt: new ISODate("2021-11-28")}
}
]
}
},
/*SecondStage*/
{
$group:
{
_id: {$dateToString: {format: '%Y/%m/%d', date: "$created_at"}},
count: {
$sum: 1
}
}
}
])
For Click
db.click.aggregate([
/*FirstStage*/
{
$match:
{
"$and":
[
{
"publisher_id": 1
},
{
"created_at": {$gte: new ISODate("2021-11-01"), $lt: new ISODate("2021-11-28")}
}
]
}
},
/*SecondStage*/
{
$group:
{
_id: {$dateToString: {format: '%Y/%m/%d', date: "$created_at"}},
count: {
$sum: 1
}
}
}
])
Because you are querying two different collections there is no "good" way to merge this into one query, the only way I can think of is using $facet, where the first stage is the "normal" one, and the other stage starts with a $lookup from the other collection.
This approach does add overhead, which is why I recommend to just keep doing the merge in code, however for the sake of answering here is a sample:
db.view.aggregate([
{
$facet: {
views: [
{
$match: {
"$and": [
{
"publisher_id": 1
},
{
"created_at": {
$gte: ISODate("2021-11-01"),
$lt: ISODate("2021-11-28")
}
}
]
}
},
],
clicks: [
{
$limit: 1
},
{
$lookup: {
from: "click",
let: {},
pipeline: [
{
$match: {
"$and": [
{
"publisher_id": 1
},
{
"created_at": {
$gte: ISODate("2021-11-01"),
$lt: ISODate("2021-11-28")
}
}
]
}
},
],
as: "clicks"
}
},
{
$unwind: "$clicks"
},
{
$replaceRoot: {
newRoot: "$clicks"
}
}
]
}
},
{
$project: {
merged: {
"$concatArrays": [
"$views",
"$clicks"
]
}
}
},
{
$unwind: "$merged"
},
{
$group: {
_id: {
$dateToString: {
format: "%Y/%m/%d",
date: "$merged.created_at"
}
},
count: {
$sum: 1
}
}
}
])
Mongo Playground
I have a document which describes counts of different things observed by a camera within a 15 minute period. It looks like this:
{
"_id" : ObjectId("5b1a709a83552d002516ac19"),
"start" : ISODate("2018-06-08T11:45:00.000Z"),
"end" : ISODate("2018-06-08T12:00:00.000Z"),
"recording" : ObjectId("5b1a654683552d002516ac16"),
"data" : {
"counts" : {
"5b434d05da1f0e00252566be" : 12,
"5b434d05da1f0e00252566cc" : 4,
"5b434d05da1f0e00252566ca" : 1
}
}
}
The keys inside the data.counts object change with each document and refer to additional data that is fetched at a later date. There are unlimited number of keys inside data.counts (but usually about 20)
I am trying to aggregate all these 15 minute documents up to daily aggregated documents.
I have this query at the moment to do that:
db.getCollection("segments").aggregate([
{$match:{
"recording": ObjectId("5bf7f68ad8293a00261dd83f")
}},
{$project:{
"start": 1,
"recording": 1,
"data": 1
}},
{$group:{
_id: { $dateToString: { format: "%Y-%m-%d", date: "$start" } },
"segments": { $push: "$$ROOT" }
}},
{$sort: {_id: -1}},
]);
This does the grouping and returns all the segments in an array.
I want to also aggregate the information inside data.counts, so that I get the sum of values for all keys that are the same within the daily group.
This would save me from having another service loop through each 15 minute segment summing values with the same keys. E.g. the query would return something like this:
{
"_id" : "2019-02-27",
"counts" : {
"5b434d05da1f0e00252566be" : 351,
"5b434d05da1f0e00252566cc" : 194,
"5b434d05da1f0e00252566ca" : 111
... any other keys that were found within a day
}
}
How might I amend the query I already have, or use a different query?
Thanks!
You could use the $facet pipeline stage to create two sub-pipelines; one for segments and another for counts. These sub-pipelines can be joined by using $zip to stitch them together and $map to merge each 2-element array produced from zip. Note this will only work correctly if the sub-pipelines output sorted arrays of the same size, which is why we group and sort by start_date in each sub-pipeline.
Here's the query:
db.getCollection("segments").aggregate([{
$match: {
recording: ObjectId("5b1a654683552d002516ac16")
}
}, {
$project: {
start: 1,
recording: 1,
data: 1,
start_date: { $dateToString: { format: "%Y-%m-%d", date: "$start" }}
}
}, {
$facet: {
segments_pipeline: [{
$group: {
_id: "$start_date",
segments: {
$push: {
start: "$start",
recording: "$recording",
data: "$data"
}
}
}
}, {
$sort: {
_id: -1
}
}],
counts_pipeline: [{
$project: {
start_date: "$start_date",
count: { $objectToArray: "$data.counts" }
}
}, {
$unwind: "$count"
}, {
$group: {
_id: {
start_date: "$start_date",
count_id: "$count.k"
},
count_sum: { $sum: "$count.v" }
}
}, {
$group: {
_id: "$_id.start_date",
counts: {
$push: {
$arrayToObject: [[{
k: "$_id.count_id",
v: "$count_sum"
}]]
}
}
}
}, {
$project: {
counts: { $mergeObjects: "$counts" }
}
}, {
$sort: {
_id: -1
}
}]
}
}, {
$project: {
result: {
$map: {
input: { $zip: { inputs: ["$segments_pipeline", "$counts_pipeline"] }},
in: { $mergeObjects: "$$this" }
}
}
}
}, {
$unwind: "$result"
}, {
$replaceRoot: {
newRoot: "$result"
}
}])
Try it out here: Mongoplayground.
i did this Aggregate pipeline , and i want add a field contains the Global Total of all groups total.
{ "$match": query },
{ "$sort": cursor.sort },
{ "$group": {
_id: { key:"$paymentFromId"},
items: {
$push: {
_id:"$_id",
value:"$value",
transaction:"$transaction",
paymentMethod:"$paymentMethod",
createdAt:"$createdAt",
...
}
},
count:{$sum:1},
total:{$sum:"$value"}
}}
{
//i want to get
...project groups , goupsTotal , groupsCount
}
,{
"$skip":cursor.skip
},{
"$limit":cursor.limit
},
])
you need to use $facet (avaialble from MongoDB 3.4) to apply multiple pipelines on the same set of docs
first pipeline: skip and limit docs
second pipeline: calculate total of all groups
{ "$match": query },
{ "$sort": cursor.sort },
{ "$group": {
_id: { key:"$paymentFromId"},
items: {
$push: "$$CURRENT"
},
count:{$sum:1},
total:{$sum:"$value"}
}
},
{
$facet: {
docs: [
{ $skip:cursor.skip },
{ $limit:cursor.limit }
],
overall: [
{$group: {
_id: null,
groupsTotal: {$sum: '$total'},
groupsCount:{ $sum: '$count'}
}
}
]
}
the final output will be
{
docs: [ .... ], // array of {_id, items, count, total}
overall: { } // object with properties groupsTotal, groupsCount
}
PS: I've replaced the items in the third pipe stage with $$CURRENT which adds the whole document for the sake of simplicity, if you need custom properties then specify them.
i did it in this way , project the $group result in new field doc and $sum the sub totals.
{
$project: {
"doc": {
"_id": "$_id",
"total": "$total",
"items":"$items",
"count":"$count"
}
}
},{
$group: {
"_id": null,
"globalTotal": {
$sum: "$doc.total"
},
"result": {
$push: "$doc"
}
}
},
{
$project: {
"result": 1,
//paging "result": {$slice: [ "$result", cursor.skip,cursor.limit ] },
"_id": 0,
"globalTotal": 1
}
}
the output
[
{
globalTotal: 121500,
result: [ [group1], [group2], [group3], ... ]
}
]