I have below mongodb query, in which i am using $addToSet, Now i want to use it condition vise.
Worksheet.aggregate([
{
"$group": {
"_id": null,
"todayBilling": {
"$sum": {
"$cond": [{ "$and" : [ { "$eq": [ "$isBilling", true] }, { $eq: [ "$date",new Date(moment().format('l'))]}] },"$hours",0 ]
}
},
"todayProjects": { "$addToSet": "$projectId" }
},
},
{ "$addFields": { "todayProjects": { "$size": "$todayProjects" }}},
{
"$lookup":{
"from": "projects",
"let": {},
"pipeline": [
{
"$group": { "_id": null, "count": { "$sum": 1 } }
}
],
"as": "totalProjects"
}
},
{'$unwind':'$totalProjects'}
])
Now, I want to get the count of todayProjects field if got result today date vise. means where "todayProjects": { "$addToSet": "$projectId" } exists, i want to use $cond with below condition:
{ $eq: [ "$date",new Date(moment().format('l'))]}
Related
I have the following aggregation pipeline running in the latest version of mongoDB and pymongo:
[
{
"$project": {
"union": {
"$setUnion": [
"$query_a",
"$query_b"
]
}
}
},
{
"$unwind": "$union"
},
{
"$group": {
"_id": "$union.ID",
"date_a": {
"$addToSet": "$union.date_a"
},
"date_b": {
"$addToSet": "$union.date_b"
}
}
},
{
"$unwind": "$date_a"
},
{
"$unwind": "$date_b"
},
{
"$project": {
"_id": 1,
"date_a": "$date_a",
"date_b": "date_b",
"diff": {
"$subtract": [
{
"$toInt": "$date_b"
},
{
"$toInt": "$date_a"
}
]
}
}
},
{
"$match": {
"diff": {
"$gt": 0,
"$lte": 20
}
}
},
]
This gives the union of the 2 pipelines query_a and query_b. After this union I want to get an intersection on ID with the pipeline query_c: (query_a UNION query_b) INTERSECTION query_c.
For this playground example the desired output would be:
[
{
"ID": "c80ea2cb-3272-77ae-8f46-d95de600c5bf",
},
{
"ID": "cdbcc129-548a-9d51-895a-1538200664e6",
}
]
You could change and augment your pipeline a little to get your desired output.
db.collection.aggregate([
{
"$project": {
"union": {
// do the intersection here
"$filter": {
"input": {
"$setUnion": [
"$query_a",
"$query_b"
]
},
"as": "elem",
"cond": {
// only take IDs in query_c
"$in": ["$$elem.ID", "$query_c.ID"]
}
}
}
}
},
{
"$unwind": "$union"
},
{
"$group": {
"_id": "$union.ID",
"date_a": {
"$addToSet": "$union.date_a"
},
"date_b": {
"$addToSet": "$union.date_b"
}
}
},
{
"$unwind": "$date_a"
},
{
"$unwind": "$date_b"
},
{
"$project": {
"diff": {
"$subtract": [
{
"$toInt": "$date_b"
},
{
"$toInt": "$date_a"
}
]
}
}
},
{
"$match": {
"diff": {
"$gt": 0,
"$lte": 20
}
}
},
{ // get unique _id's
"$group": {
"_id": "$_id"
}
},
{ // rename _id to ID
"$project": {
"_id": 0,
"ID": "$_id"
}
}
])
Try it on mongoplayground.net.
You can do it with:
Updating first $project stage to also project an array of IDs from query_c.
Using $set as a second stage where you would filter out all items from the union of query_a and query_b, that does not have ID that's in query_c.
You can do it like this:
{
"$project": {
"union": {
"$setUnion": [
"$query_a",
"$query_b"
]
},
"query_c": {
"$map": {
"input": "$query_c",
"in": "$$this.ID"
}
}
}
},
{
"$set": {
"union": {
"$filter": {
"input": "$union",
"cond": {
"$in": [
"$$this.ID",
"$query_c"
]
}
}
}
}
},
The rest of your Aggregation pipeline can remain the same.
Working example
I'm new in mongoDB.
This is one example of record from collection:
{
supplier: 1,
type: "sale",
items: [
{
"_id": ObjectId("60ee82dd2131c5032342070f"),
"itemBuySum": 10
},
{
"_id": ObjectId("60ee82dd2131c50323420710"),
"itemBuySum": 10,
},
{
"_id": ObjectId("60ee82dd2131c50323420713"),
"itemBuySum": 10
},
{
"_id": ObjectId("60ee82dd2131c50323420714"),
"itemBuySum": 20
}
]
}
I need to group by TYPE field and get the SUM. This is output I need:
{
supplier: 1,
sales: 90,
returns: 170
}
please check Mongo playground for better understand. Thank you!
$match - Filter documents.
$group - Group by type and add item into data array which leads to the result like:
[
[/* data 1 */],
[/* data 2 */]
]
$project - Decorate output document.
3.1. First $reduce is used to flatten the nested array to a single array (from Result (2)) via $concatArrays.
3.2. Second $reduce is used to aggregate $sum the itemBuySum.
db.collection.aggregate({
$match: {
supplier: 1
},
},
{
"$group": {
"_id": "$type",
"supplier": {
$first: "$supplier"
},
"data": {
"$push": "$items"
}
}
},
{
"$project": {
_id: 0,
"supplier": "$supplier",
"type": "$_id",
"returns": {
"$reduce": {
"input": {
"$reduce": {
input: "$data",
initialValue: [],
in: {
"$concatArrays": [
"$$value",
"$$this"
]
}
}
},
"initialValue": 0,
"in": {
$sum: [
"$$value",
"$$this.itemBuySum"
]
}
}
}
}
})
Sample Mongo Playground
db.collection.aggregate([
{
$match: {
supplier: 1
},
},
{
"$group": {
"_id": "$ID",
"supplier": {
"$first": "$supplier"
},
"sale": {
"$sum": {
"$cond": {
"if": {
"$eq": [
"$type",
"sale"
]
},
"then": {
"$sum": "$items.itemBuySum"
},
"else": {
"$sum": 0
}
}
}
},
"returns": {
"$sum": {
"$sum": {
"$cond": {
"if": {
"$eq": [
"$type",
"return"
]
},
"then": {
"$sum": "$items.itemBuySum"
},
"else": {
"$sum": 0
}
}
}
}
}
}
},
{
"$project": {
_id: 0,
supplier: 1,
sale: 1,
returns: 1
}
}
])
Trying to total a documents by a condition where timestamp equals the first timestamp found
Need to sum the number of documents that meet the condition that the document matched the first timestamp value found. Below is what I've tried in order to reference the timestamp equal to { "$first": "$timestamp" }
IP.aggregate([
{
"$sort":{'timestamp':-1}
},
{
"$group": {
"_id": "$application",
"url": { "$first": "$app_url_name" },
"timestamp": { "$first": "$timestamp" },
"total": {
$sum: {
$cond: {
if: {
$and:[
{$eq: ['$environment_category', 'PROD']},
{$eq: ['$timestamp', '$_id.timestamp']}
]
},
then: 1,
else: 0
}
}
},
"enabled": { $sum: {$cond: {if: {
$and: [
{$eq: ['$availability', 'available']},
{$eq: ['$state', 'enabled']},
{$eq: ['$environment_category', 'PROD']}
]
} ,
then: 1,
else: 0} }}
}
},
Here's the solution:
db.ips.aggregate([
{
"$sort": { "timestamp": -1 }
},
{
"$group": {
"_id": "$application",
"doc": { "$first": "$$ROOT" },
"items": {"$push": "$$ROOT"}
}
},
{
"$project": {
"_id": 0,
"application": "$_id",
"timestamp": "$doc.timestamp",
"items": {
"$filter": {
"input": "$items",
"as": "item",
"cond": { "$eq": [ "$$item.timestamp", "$doc.timestamp" ] }
}
}
}
},
]);
I am using below query to get combined data from users and project collections:
db.collection.aggregate([
{
"$group": {
"_id": "$userId",
"projectId": { "$push": "$projectId" }
}
},
{
"$lookup": {
"from": "users",
"let": { "userId": "$_id" },
"pipeline": [
{ "$match": { "$expr": { "$eq": [ "$_id", "$$userId" ] }}},
{ "$project": { "firstName": 1 }}
],
"as": "user"
}
},
{ "$unwind": "$user" },
{
"$lookup": {
"from": "projects",
"let": { "projectId": "$projectId" },
"pipeline": [
{ "$match": { "$expr": { "$in": [ "$_id", "$$projectId" ] }}},
{ "$project": { "projectName": 1 }}
],
"as": "projects"
}
}
])
and it results like below:
[
{
"_id": "5c0a29e597e71a0d28b910aa",
"projectId": [
"5c0a2a8897e71a0d28b910ac",
"5c0a4083753a321c6c4ee024"
],
"user": {
"_id": "5c0a29e597e71a0d28b910aa",
"firstName": "Amit"
},
"projects": [
{
"_id": "5c0a2a8897e71a0d28b910ac",
"projectName": "LN-PM"
},
{
"_id": "5c0a4083753a321c6c4ee024",
"projectName": "fallbrook winery"
}
]
},
{
"_id": "5c0a29c697e71a0d28b910a9",
"projectId": [
"5c0a4083753a321c6c4ee024"
],
"user": {
"_id": "5c0a29c697e71a0d28b910a9",
"firstName": "Rajat"
},
"projects": [
{
"_id": "5c0a4083753a321c6c4ee024",
"projectName": "fallbrook winery"
}
]
}
]
Now i have another table "Worksheets" and want to include hours field in projects Array, which will be calculated from the worksheets table by specifying the projectId which is _id in the projects array. It will be find in worksheet table and hours will be incremented how many times this _id has in worksheets table. Below is my worksheet collection:
{
"_id" : ObjectId("5c0a4efa91b5021228681f7a"),
"projectId" : ObjectId("5c0a4083753a321c6c4ee024"),
"hours" : 8,
"userId" : ObjectId("5c0a29c697e71a0d28b910a9"),
"__v" : 0
}
{
"_id" : ObjectId("5c0a4f4191b5021228681f7c"),
"projectId" : ObjectId("5c0a2a8897e71a0d28b910ac"),
"hours" : 6,
"userId" : ObjectId("5c0a29e597e71a0d28b910aa"),
"__v" : 0
}
The result will look like below:
{
"_id": "5c0a29c697e71a0d28b910a9",
"projectId": [
"5c0a4083753a321c6c4ee024"
],
"user": {
"_id": "5c0a29c697e71a0d28b910a9",
"firstName": "Rajat"
},
"projects": [
{
"_id": "5c0a4083753a321c6c4ee024",
"projectName": "fallbrook winery",
"hours":8
}
]
}
You can use below aggregation
$lookup 3.6 nested syntax allows you to join nested collection inside the $lookup pipeline. You can perform all the aggregation inside the nested $lookup pipline
db.collection.aggregate([
{ "$group": {
"_id": "$userId",
"projectId": { "$push": "$projectId" }
}},
{ "$lookup": {
"from": "users",
"let": { "userId": "$_id" },
"pipeline": [
{ "$match": { "$expr": { "$eq": [ "$_id", "$$userId" ] }}},
{ "$project": { "firstName": 1 }}
],
"as": "user"
}},
{ "$unwind": "$user" },
{ "$lookup": {
"from": "projects",
"let": { "projectId": "$projectId" },
"pipeline": [
{ "$match": { "$expr": { "$in": [ "$_id", "$$projectId" ] }}},
{ "$lookup": {
"from": "worksheets",
"let": { "projectId": "$_id" },
"pipeline": [
{ "$match": { "$expr": { "$eq": [ "$projectId", "$$projectId" ] }}},
{ "$group": {
"_id": "$projectId",
"totalHours": { "$sum": "$hours" }
}}
],
"as": "workHours"
}}
{ "$project": {
"projectName": 1,
"hours": { "$arrayElemAt": ["$workHours.totalHours", 0] }
}}
],
"as": "projects"
}}
])
I am using $lookup to join two collections and get data from below query:
let condition = {status:{$ne:config.PROJECT_STATUS.completed}, assignId:mongoose.Types.ObjectId(req.params.id)};
Project.aggregate([
{
$match: condition
},
{
"$group":{
"_id": "$_id"
}
},
{
"$lookup": {
"from": "worksheets",
"let": { "projectId": "$_id" },
"pipeline": [
{ "$match": { "$expr": { "$eq": [ "$projectId", "$$projectId" ] }}},
{ "$group": {_id:"$projectId", totalHours:{"$sum": "$hours"}}},
{
"$lookup": {
"from": "projects",
"let": { "projectId": "$_id" },
"pipeline": [
{ "$match": { "$expr": { "$eq": [ "$_id", "$$projectId" ] }}},
{ "$project": { "projectName": 1,"upworkdId":1,"status":1,"developers":1,"hoursApproved":1 }}
],
"as": "project"
}
}
],
"as": "projects"
}
}
])
.then((data)=>{
res.json(data);
})
And above query is giving me below result:
[
{
"_id": "5c0a4083753a321c6c4ee024",
"projects": [
{
"_id": "5c0a4083753a321c6c4ee024",
"totalHours": 11,
"project": [
{
"_id": "5c0a4083753a321c6c4ee024",
"hoursApproved": 24,
"developers": [
"5c0a29c697e71a0d28b910a9"
],
"projectName": "fallbrook winery",
"status": "pending"
}
]
}
]
}
]
Now i want to populate the developers subfield inside the project Array. How can i modify the above code to get that.
You can use $lookup one more deep level with the developers array.
Something like this
Project.aggregate([
{ "$match": condition },
{ "$group": { "_id": "$_id" }},
{ "$lookup": {
"from": "worksheets",
"let": { "projectId": "$_id" },
"pipeline": [
{ "$match": { "$expr": { "$eq": ["$projectId", "$$projectId"] } } },
{ "$group": { "_id": "$projectId", "totalHours": { "$sum": "$hours" } }},
{ "$lookup": {
"from": "projects",
"let": { "projectId": "$_id" },
"pipeline": [
{ "$match": { "$expr": { "$eq": ["$_id", "$$projectId"] } } },
{ "$lookup": {
"from": "developers",
"let": { "developers": "$developers" },
"pipeline": [
{ "$match": { "$expr": { "$in": ["$_id", "$$developers"] } } },
],
"as": "developers"
}},
{ "$project": {
"projectName": 1, "upworkdId": 1, "status": 1, "developers": 1, "hoursApproved": 1
}}
],
"as": "project"
}}
],
"as": "projects"
}}
])