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": [
"$$this.ID",
"$query_c"
]
}
}
}
}
},
The rest of your Aggregation pipeline can remain the same.
Working example
Related
I have a document with a nested array array_field:
{
"_id": {
"$oid": "1"
},
"id": "1",
"array_field": [
{
"data": [
{
"regions": [
{
"result": {
"item": [
"4",
"5",
"3"
]
}
},
{
"result": {
"item": [
"5"
]
}
},
{
"result": {
"item": [
"1"
]
}
}
]
}
]
}
]
}
I need add new field, new_added_field for example, with each array element from array_field.data.regions.result.item and remove array_field from document.
For example:
{
"_id": {
"$oid": "1"
},
"id": "1",
"new_added_field": [4,5,3,5,1]
}
I think i can do this with help of $unwind or $map but have difficulties and need dome hint, how i can do it with help op aggregation?
As you said,
db.collection.aggregate([
{
"$project": {
newField: {
"$map": {
"input": "$array_field",
"as": "m",
"in": "$$m.data.regions.result.item"
}
}
},
},
{ "$unwind": "$newField" },
{ "$unwind": "$newField" },
{ "$unwind": "$newField" },
{ "$unwind": "$newField" },
{
"$group": {
"_id": "$_id",
"newField": { "$push": "$newField" }
}
}
])
Working Mongo playground
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
}
}
])
I have a current MongoDB Aggregate framework pipeline from a previous question and I am unable to add populate query to grab user profile by id.
My code is below
Product.aggregate([
{
$group: {
_id: {
hub: "$hub",
status: "$productStatus",
},
count: { $sum: 1 },
},
},
{
$group: {
_id: "$_id.hub",
counts: {
$push: {
k: "$_id.status",
v: "$count",
},
},
},
},
{
$group: {
_id: null,
counts: {
$push: {
k: { $toString: "$_id" },
v: "$counts",
},
},
},
},
{
$addFields: {
counts: {
$map: {
input: "$counts",
in: {
$mergeObjects: [
"$$this",
{ v: { $arrayToObject: "$$this.v" } },
],
},
},
},
},
},
{
$replaceRoot: {
newRoot: { $arrayToObject: "$counts" },
},
},
]);
and got the following result
[
{
"5fe75679e6f7a62ddaf5b2e9": {
"in progress": 5,
"Cancelled": 4,
"return": 1,
"on the way": 3,
"pending": 13,
"Delivered": 4
}
}
]
Expected Output
I need to grab user information from user collections using the hubId "5fe75679e6f7a62ddaf5b2e9" and expect a final result of the form below
[
{
"hub": {
"photo": "avatar.jpg",
"_id": "5fe75679e6f7a62ddaf5b2e9",
"name": "Dhaka Branch",
"phone": "34534543"
},
"statusCounts": {
"in progress": 5,
"Cancelled": 4,
"return": 1,
"on the way": 3,
"pending": 13,
"Delivered": 4
}
}
]
First id is user id and available in user collections.
You need to tweak your aggregate pipeline a little bit and include new pipeline stage like $lookup that populates the
hub
Product.aggregate([
{ "$group": {
"_id": {
"hubId": "$hubId",
"status": "$productStatus"
},
"count": { "$sum": 1 }
} },
{ "$group": {
"_id": "$_id.hubId",
"statusCounts": {
"$push": {
"k": "$_id.status",
"v": "$count"
}
}
} },
{ "$lookup": {
"fron": "users",
"localField": "_id",
"foreignField": "_id",
"as": "user"
} },
{ "$project": {
"user": { "$arrayElemAt": ["$user", 0] },
// "hub": { "$first": "$hub" },
"statusCounts": { "$arrayToObject": "$statusCounts" }
} }
])
To project only some fields in the user profile, you can update your $lookup pipeline to have the form
{ "$lookup": {
"from": "users",
"let": { "userId": "$_id" },
"pipeline": [
{ "$match": {
"$expr": { "$eq": ["$_id", "$$userId"] }
} },
{ "$project": {
"name": 1,
"phone": 1,
"photo": 1
} }
],
"as": "user"
} }
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'))]}
I want to write a group by query to written active user and total count(both active and inactive) grouped by a date column in mongodb. I am able to run them as two separate scripts but how to retrieve the same information in one script
db.user.aggregate(
{
"$match": { 'phoneInfo.verifiedFlag': true}
},
{
"$project": {
yearMonthDayUTC: { $dateToString: { format: "%Y-%m-%d", date: "$createdOn" } }
}
},
{
"$group": {
"_id": {day: "$yearMonthDayUTC"},
count: {
"$sum": 1
}
}
},
{
$sort: {
"_id.day": 1,
}
})
You can use the $cond operator in your group to create a conditional count as follows (assuming the inactive/active values are in a field called status):
db.user.aggregate([
{ "$match": { 'phoneInfo.verifiedFlag': true} },
{
"$group": {
"_id": { "$dateToString": { "format": "%Y-%m-%d", "date": "$createdOn" } },
"total": { "$sum": 1 },
"active_count": {
"$sum": {
"$cond": [ { "$eq": [ "$status", "active" ] }, 1, 0 ]
}
},
"inactive_count": {
"$sum": {
"$cond": [ { "$eq": [ "$status", "inactive" ] }, 1, 0 ]
}
}
}
},
{ "$sort": { "_id": 1 } }
])
For different values you can adapt the following pipeline:
db.user.aggregate([
{ "$match": { 'phoneInfo.verifiedFlag': true} },
{
"$group": {
"_id": {
"day": {
"$dateToString": {
"format": "%Y-%m-%d",
"date": "$createdOn"
}
},
"status": { "$toLower": "$status" }
},
"count": { "$sum": 1 }
}
},
{
"$group": {
"_id": "$_id.day",
"counts": {
"$push": {
"status": "$_id.status",
"count": "$count"
}
}
}
},
{ "$sort": { "_id": 1 } }
])