I have created a pipeline between 3 collections and the final result must be in count based on their respective field. Hope someone gives some assistance.
INPUT
{
"_id" : "josh_7#user.com",
"users" : [
{
"_id" : ObjectId("612f60cb5dce270014648294"),
"userType" : "Admin",
"userPlan" : "GROWTH",
"username" : "josh_7#user.com",
"company" : "josh_7#user.com",
"accounts" : [
{
"_id" : {
"username" : "josh_7#user.com"
}
},
{
"_id" : {
"username" : "josh_7#user.com",
"status" : "ERROR"
}
},
{
"_id" : {
"username" : "josh_7#user.com",
"status" : "SENT"
}
},
{
"_id" : {
"username" : "josh_7#user.com",
"status" : "REMOVED_FROM_QUEUE"
}
},
{
"_id" : {
"username" : "josh_7#user.com",
"status" : "REMOVED_FOR_PUBLISH"
}
},
{
"_id" : {
"username" : "josh_7#user.com",
"status" : "UNSCHEDULED"
}
}
]
},
]
}
EXPECTED OUTPUT
{
"_id": "josh_7#user.com",
"users": [
{
"username": "josh_7#user.com",
"userType": "Admin",
"userPlan": "GROWTH",
"company": "josh_7#user.com",
"accounts": [ // This section is where i got stuck
{
"_id": "josh_7#user.com,
"READY_TO_GO_count": 0,
"SENT": 36,
"UNSCHEDULED": 0,
"AWAITING_APPROVAL": 0,
"REMOVED_FROM_QUEUE": 16,
"FLAGGED": 1,
"ERROR": 1
}
]
},
I tried using the below line
{$group:{_id:"$status",count:{$sum:1}}}
The output was :
"accounts" : [
{
"_id" : "SENT",
"count" : 4.0
},
{
"_id" : "REMOVED_FROM_QUEUE",
"count" : 8.0
}
]
I Figured something for the above question, If it's not the best way, Please do correct me.
{$group:{_id:"$username","SENT":{$sum:{$cond:[{$eq:["$status","SENT"]},1,0]}},"AWAITING_APPROVAL":{$sum:{$cond:[{$eq:["$status","AWAITING_APPROVAL"]},1,0]}},"FLAGGED":{$sum:{$cond:[{$eq:["$status","FLAGGED"]},1,0]}},}}
Result
{
"_id" : ObjectId("5ed7abc5986c050012d4aa4a"),
"userType" : "Regular",
"userPlan" : "GRANDE",
"username" : "shan2#psk3n.com",
"company" : "tariyi8792#psk3n.com",
"accounts" : [
{
"_id" : "shan2#psk3n.com",
"SENT" : 1.0,
"AWAITING_APPROVAL" : 0.0,
"FLAGGED" : 0.0
}
]
}
{
"_id" : "tenant/data/EMAIL/ENGLISH",
"tenantId" : "tenant2",
"channelType" : "EMAIL",
"template" : [
{
"_id" : "1",
"templateName" : "abc",
"effectiveStartDate" : ISODate("2017-01-01T12:00:00.000Z"),
"modifiedDate" : ISODate("2017-06-02T22:08:55.782Z"),
"active" : false
}
]
}
I need to update the "templateName" : "xyz" on the basis of "_id" : "tenant/data/EMAIL/ENGLISH"
I have tried these queries but got no success
db.getCollection('data').updateOne({"_id": "tenant/data/EMAIL/ENGLISH"},
{$set : { "template.$.templateName" : "XYZ"}});
db.getCollection('data').updateOne({"_id": "tenant/data/EMAIL/ENGLISH"},
{$set : { "template.templateName" : "XYZ"}});
Any help will be appreciated.
I have used positional-all operator to update the array.
Here is the query:
db.sample.update(
{
"_id": "tenant/data/EMAIL/ENGLISH"
},
{
$set:{
"template.$[].templateName":"XYZ"
}
}
)
Output
{
"_id" : "tenant/data/EMAIL/ENGLISH",
"tenantId" : "tenant2",
"channelType" : "EMAIL",
"template" : [
{
"_id" : "1",
"templateName" : "XYZ",
"effectiveStartDate" : ISODate("2017-01-01T12:00:00Z"),
"modifiedDate" : ISODate("2017-06-02T22:08:55.782Z"),
"active" : false
}
]
}
hope this will help :)
I´m facing a challenge here. I have this collection here
{
"_id" : ObjectId("5e0ff6d424f9fc12bc3d9464"),
"name" : "Pizzaria Don Juan",
"active" : true,
"branches" : [
{
"location" : {
"type" : "Point",
"coordinates" : [ ]
},
"_id" : ObjectId("5e19cafc31d60216b8dbd649"),
"name" : "Parque da Mooca",
"address" : "Rua Dianópolis",
"addressNumber" : 1283,
"federalId" : "10.445.089/0001-44",
"complement" : "Ap 55",
"postalCode" : "03126-007",
"coveredArea" : 0,
"neighborhood" : "Parque da Mooca",
"deliveryTime" : 0,
"deliveryRate" : 0,
"standard" : false,
"city" : "Mococa",
"state" : "RJ",
"emails" : [ ],
"phones" : [ ],
"daysWeek" : [ ],
"socialMedias" : [ ],
"paymentTerms" : [ ],
"sections" : [ ]
},
{
"location" : {
"type" : "Point",
"coordinates" : [ ]
},
"_id" : ObjectId("5e19c9a531d60216b8dbd639"),
"name" : "Principal",
"address" : "Rua Nicolau Filizola",
"addressNumber" : null,
"federalId" : "10.445.089/0001-53",
"complement" : "",
"postalCode" : "05547-010",
"coveredArea" : 0,
"neighborhood" : "Jardim Rosa Maria",
"deliveryTime" : 0,
"deliveryRate" : 0,
"standard" : true,
"city" : "São Paulo",
"state" : "SP",
"emails" : [
{
"_id" : ObjectId("5e19ca9531d60216b8dbd643"),
"name" : "Contato",
"address" : "contato#pizzariadonjuan.com.br"
},
{
"_id" : ObjectId("5e19ca9531d60216b8dbd642"),
"name" : "Contato2",
"address" : "contato2#pizzariadonjuan.com.br"
}
],
"phones" : [
{
"_id" : ObjectId("5e19ca9531d60216b8dbd645"),
"name" : "Principal",
"number" : "(11) 99740-2216"
},
{
"_id" : ObjectId("5e19ca9531d60216b8dbd644"),
"name" : "Secundario",
"number" : "(11) 2562-2759"
}
],
"daysWeek" : [
{
"_id" : ObjectId("5e1cf99741c52d4a587a9162"),
"startsAt" : 64800000,
"endsAt" : 82800000,
"opens" : true,
"dayWeekId" : ObjectId("5e1a124a17fd054900a1afb2")
},
{
"_id" : ObjectId("5e1cf99741c52d4a587a9161"),
"startsAt" : 0,
"endsAt" : 0,
"opens" : false,
"dayWeekId" : ObjectId("5e1a126817fd054900a1afb3")
},
{
"_id" : ObjectId("5e1cfbed41c52d4a587a9170"),
"startsAt" : 64980000,
"endsAt" : 82800000,
"opens" : true,
"dayWeekId" : ObjectId("5e1a126e17fd054900a1afb4")
},
{
"_id" : ObjectId("5e1b8fac96516432845e364c"),
"startsAt" : 64980000,
"endsAt" : 82800000,
"opens" : true,
"dayWeekId" : ObjectId("5e1a127517fd054900a1afb5")
},
{
"_id" : ObjectId("5e1cfbed41c52d4a587a916f"),
"startsAt" : 64980000,
"endsAt" : 82800000,
"opens" : true,
"dayWeekId" : ObjectId("5e1a127a17fd054900a1afb6")
},
{
"_id" : ObjectId("5e1cfbed41c52d4a587a916e"),
"startsAt" : 64800000,
"endsAt" : 82800000,
"opens" : true,
"dayWeekId" : ObjectId("5e1a23f8bf353f493c74e8ae")
},
{
"_id" : ObjectId("5e1cfbed41c52d4a587a916d"),
"startsAt" : 61380000,
"endsAt" : 83154000,
"opens" : true,
"dayWeekId" : ObjectId("5e1a2407bf353f493c74e8af")
}
],
"socialMedias" : [
{
"_id" : ObjectId("5e1d082641c52d4a587a9191"),
"socialMediaId" : ObjectId("5e10089a3330ad05d4e1867d"),
"url" : "rewrwerwerwerwerwerwerwer"
}
],
"paymentTerms" : [
{
"_id" : ObjectId("5e1d143041c52d4a587a91b7"),
"paymentTermId" : ObjectId("5e1a2277bf353f493c74e8a7")
},
{
"_id" : ObjectId("5e1d143041c52d4a587a91b6"),
"paymentTermId" : ObjectId("5e1a228cbf353f493c74e8a8")
},
{
"_id" : ObjectId("5e1d143041c52d4a587a91b5"),
"paymentTermId" : ObjectId("5e1a229ebf353f493c74e8a9")
}
],
"sections" : [
{
"_id" : ObjectId("5e1e535441c52d4a587a9208"),
"name" : "Camisetas",
"products" : [
{
"_id" : ObjectId("5e1e662f044582129844ffd5"),
"name" : "DonJuan M",
"description" : "",
"quantityAvailable" : 0,
"image" : "",
"price" : 0,
"validFrom" : ISODate("2020-01-15T01:08:49.552Z"),
"validTo" : ISODate("2020-01-15T01:08:49.552Z"),
"enabled" : true
}
]
},
{
"_id" : ObjectId("5e20ec889c05f229a484ea3d"),
"name" : "Imãs",
"products" : [
{
"_id" : ObjectId("5e20ec889c05f229a484ea3e"),
"name" : "Imã",
"description" : "Imã",
"quantityAvailable" : 0,
"image" : "",
"price" : 0,
"validFrom" : ISODate("0001-01-01T00:00:00Z"),
"validTo" : ISODate("9999-12-31T00:00:00Z"),
"enabled" : true
}
]
}
]
}
],
"users" : [
{
"_id" : ObjectId("5e10fc2adc147a373c312144")
},
{
"_id" : ObjectId("5e11ff8003eb832ef84342a6")
}
],
"socialMedias" : [
{
"_id" : ObjectId("5e165672a2204b49c892db74"),
"socialMediaId" : ObjectId("5e10089a3330ad05d4e1867d"),
"url" : "uuuutt"
},
{
"_id" : ObjectId("5e15385fb3a0aa1004ac3598"),
"socialMediaId" : ObjectId("5e1009043330ad05d4e1867f"),
"url" : "jkkjkjkjkjk"
}
],
"sections" : [
{
"_id" : ObjectId("5e15313b2e985e16ec4e7413"),
"name" : "Bebidas",
"products" : [
{
"_id" : ObjectId("5e1e6381044582129844ffc2"),
"name" : "Coca Cola Zero 2 Litros",
"description" : "",
"quantityAvailable" : 0,
"image" : "",
"price" : 18.39,
"validFrom" : ISODate("1970-01-01T00:00:00Z"),
"validTo" : ISODate("1970-01-01T00:00:00Z"),
"enabled" : true
},
{
"_id" : ObjectId("5e1e6381044582129844ffc3"),
"name" : "Coca Cola 2 Litros",
"description" : "",
"quantityAvailable" : 0,
"image" : "",
"price" : 21.42,
"validFrom" : ISODate("1970-01-01T00:00:00Z"),
"validTo" : ISODate("1970-01-01T00:00:00Z"),
"enabled" : true
},
{
"_id" : ObjectId("5e1e662f044582129844ffda"),
"name" : "Cerveja Heineken Lata 350ml",
"description" : "Cerveja Heineken Lata 350ml",
"quantityAvailable" : 0,
"image" : "volkswagen-polo.jpg",
"price" : 1.55,
"validFrom" : ISODate("2020-01-01T00:00:00Z"),
"validTo" : ISODate("1970-01-01T00:00:00Z"),
"enabled" : true
}
]
},
{
"_id" : ObjectId("5e20e8de9c05f229a484ea27"),
"name" : "Esfihas",
"products" : [
{
"_id" : ObjectId("5e20e8de9c05f229a484ea28"),
"name" : "Esfiha de carne",
"description" : "Esfiha de carne",
"quantityAvailable" : 0,
"image" : "",
"price" : 5,
"validFrom" : ISODate("2020-01-01T00:00:00Z"),
"validTo" : null,
"enabled" : true
}
]
}
],
"__v" : 0
}
{
"_id" : ObjectId("5e0ffd23991918424c8d7c3b"),
"name" : "Pizza Ruth",
"active" : true,
"users" : [ ],
"socialMedias" : [ ],
"branches" : [ ],
"sections" : [ ],
"__v" : 0
}
{
"_id" : ObjectId("5e0ffd3d991918424c8d7c3c"),
"name" : "Feijão de Corda",
"active" : true,
"users" : [ ],
"socialMedias" : [ ],
"branches" : [ ],
"sections" : [ ],
"__v" : 0
}
The fields validFrom and validTo (Date fields) from the collection products nested in branches.sections need to be converted to the format yyyy-mm-dd. I can do that with this aggregation pipeline:
{ $unwind: { path: "$branches.sections", preserveNullAndEmptyArrays: true } },
{
"$addFields": {
"branches.sections.products": {
$map: {
input: "$branches.sections.products",
as: "product",
in: {
'_id': "$$product._id",
'name': "$$product.name",
'description': "$$product.description",
'quantityAvailable': "$$product.quantityAvailable",
'image': "$$product.image",
'imageUrl': "$$product.imageUrl",
'price': "$$product.price",
'validFrom' : {"$dateToString": { "date": "$$product.validFrom", "format": "%Y-%d-%m" }},
'validTo' : {"$dateToString": { "date": "$$product.validTo", "format": "%Y-%d-%m" }},
'enabled': "$$product.enabled",
}
}
}
}
}
I can successfully convert those date fields, but I need now to "re-unwind" the array products, in order to be just like before the unwind.
Any clue in how to proceed? Or even a different way to format those dates without having to unwind? Tried dozens of ways of $group, but without any success.
You just need to $map over each nested array to drill upload the validTo and validFrom field
.aggregate([
{ "$addFields": {
"branches": {
"$map": {
"input": "$branches",
"as": "branch",
"in": {
"$mergeObjects": [
"$$branch",
{ "section": {
"$map": {
"input": "$$branch.sections",
"as": "section",
"in": {
"$mergeObjects": [
"$$section",
{ "product": {
"$map": {
"input": "$$section.products",
"as": "product",
"in": {
"$mergeObjects": [
"$$product",
{
"validFrom": { "$dateToString": { "date": "$$product.validFrom", "format": "%Y-%d-%m" }},
"validTo": { "$dateToString": { "date": "$$product.validTo", "format": "%Y-%d-%m" }}
}
]
}
}
}}
]
}
}
}}
]
}
}
}
}}
])
MongoPlayground
I have the following document and want to update state
Document ID: ObjectId("5a4e5a448b70d50e34d204a5")
Target ID: ObjectId("5a4e5a438b70d50e34d203ea")
I have no idea how to update the state to e.g. 4
{
"_id" : ObjectId("5a4e5a448b70d50e34d204a5"),
"name" : "Wirtschaftsdienst",
"date" : ISODate("2012-10-07T00:00:00.000Z"),
"comment" : null,
"tasks" : [
{
"name" : "Speisen und Getränke",
"sections" : [
{
"start" : 46800,
"end" : 72000,
"entirely" : true,
"assistants" : [
{
"assistant" : {
"_id" : ObjectId("5a4e5a438b70d50e34d203ea")
},
"state" : 3
},
{
"assistant" : {
"_id" : ObjectId("5a4e5a438b70d50e34d203f4")
},
"state" : 3
}
]
}
]
}
]
}
Use positional operator $[] along with arrayFilters to get your job done!
Try this query:
db.collection.update(
{"_id" : ObjectId("5a4e5a448b70d50e34d204a5")},
{$set: {"tasks.$[].sections.$[].assistants.$[element].state":4}},
{arrayFilters: [ {"element.assistant":{"_id" :
ObjectId("5a4e5a438b70d50e34d203ea")} }
], multi:true}
)
And the output is:
/* 1 */
{
"_id" : ObjectId("5a4e5a448b70d50e34d204a5"),
"name" : "Wirtschaftsdienst",
"date" : ISODate("2012-10-07T00:00:00.000Z"),
"comment" : null,
"tasks" : [
{
"name" : "Speisen und Getränke",
"sections" : [
{
"start" : 46800,
"end" : 72000,
"entirely" : true,
"assistants" : [
{
"assistant" : {
"_id" : ObjectId("5a4e5a438b70d50e34d203ea")
},
"state" : 4.0
},
{
"assistant" : {
"_id" : ObjectId("5a4e5a438b70d50e34d203f4")
},
"state" : 3.0
}
]
}
]
}
]
}
I have the following mongo query.
db.ServiceProvider.aggregate([
{
$unwind: "$PostCommentUserIDs"
},
{
$lookup:
{
from: "Parents",
localField: "PostCommentUserIDs",
foreignField: "ID",
as: "ParentDetailsArr"
}
},
{
$match: { "ParentDetailsArr": { $ne: [] } }
}
])
It gives following result:
{
"_id" : ObjectId("57245af1588aec5b118b4567"),
"ServiceProviderID" : 3,
"Title" : "test",
"PostedMessage" : "test",
"TotalComments" : 0,
"TotalShares" : 0,
"TotalThanks" : 0,
"AddedOn" : "2016-04-30",
"LastModifiedOn" : "2016-04-30 07:12:49",
"PostAttachment" : {
"ImagePath" : ""
},
"PostCommentUserIDs" : "3",
"PostComments" : [
{
"ID" : "1462000372388480634",
"UserID" : 3,
"CommentMessage" : "1",
"TotalThanks" : 0,
"AddedOn" : "2016-04-30 07:12:52",
"LastModifiedOn" : "2016-04-30 07:12:52",
"CommentAttachment" : {
"ImagePath" : ""
}
},
],
"Subscriber" : [ ],
"ParentDetailsArr" : [
{
"_id" : ObjectId("572447e6588aec32108b4569"),
"ID" : "3",
"UID" : "0Xb1fHqzR3HZVJWQc8aAbB77UkwSnmasdQrtp9qySVdqipsYs6eC7rEt",
"Name" : "Chinmay Kulkarni",
"ProfileImagePath" : "images3_3_1460348144#SIZE#.jpeg"
}
]
}
{
"_id" : ObjectId("57246137588aec41118b4567"),
"ServiceProviderID" : 3,
"Title" : "test",
"PostedMessage" : "test",
"TotalComments" : 0,
"TotalShares" : 0,
"TotalThanks" : 0,
"AddedOn" : "2016-04-30",
"LastModifiedOn" : "2016-04-30 07:39:35",
"PostAttachment" : {
"ImagePath" : ""
},
"PostCommentUserIDs" : "3",
"PostComments" : [
{
"ID" : "14620019791507102321",
"UserID" : 3,
"CommentMessage" : "1",
"TotalThanks" : 0,
"AddedOn" : "2016-04-30 07:39:39",
"LastModifiedOn" : "2016-04-30 07:39:39",
"CommentAttachment" : {
"ImagePath" : ""
}
},
],
"Subscriber" : [ ],
"ParentDetailsArr" : [
{
"_id" : ObjectId("572447e6588aec32108b4569"),
"ID" : "3",
"UID" : "0Xb1fHqzR3HZVJWQc8aAbB77UkwSnmasdQrtp9qySVdqipsYs6eC7rEt",
"Name" : "Chinmay Kulkarni",
"ProfileImagePath" : "images3_3_1460348144#SIZE#.jpeg"
}
]
}
I want to modify the above query and add the _id condition to it. So that it only gives me 1 result with matches with given _id.
But not able to crack it through. Please help!
The $match takes filter criterion. Add the _id query filter criteria inside $match aggregate function - https://docs.mongodb.org/manual/reference/operator/aggregation/match/
Run the query with below $match condition at last pipeline of your aggregate query.
db.ServiceProvider.aggregate([
{
$unwind: "$PostCommentUserIDs"
},
{
$lookup:
{
from: "Parents",
localField: "PostCommentUserIDs",
foreignField: "ID",
as: "ParentDetailsArr"
}
},
{
$match: { "ParentDetailsArr": { $ne: [] }, "_id" : ObjectId("XXXX") }
}
])