Related
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 just learned mongoDB, I am trying to find some repeat customer info through my customer database.
The sample collection:
{
"_id" : ObjectId("5b7617e48146d8bae"),
"amazon_id" : "112",
"date" : "2018-01-25T18:40:55-08:00",
"email" : "xxxxx#marketplace.amazon.com",
"buy_name" : "xxxxx",
"sku" : "NPC-50",
"qty" : 8,
"price" : 215.92,
"reci_name" : "XXXXX",
"street1" : "XXXXX",
"street2" : "",
"street3" : "",
"city" : "XXXXX",
"state" : "XXXXX",
"zip_code" : "XXXXXX"
}
{
"_id" : ObjectId("5b761712e48146d8bae"),
"amazon_id" : "114",
"date" : "2018-01-27T18:40:55-08:00",
"email" : "xxxxx#marketplace.amazon.com",
"buy_name" : "xxxxx",
"sku" : "ABC",
"qty" : 1,
"price" : 19.99,
"reci_name" : "XXXXX",
"street1" : "XXXXX",
"street2" : "",
"street3" : "",
"city" : "XXXXX",
"state" : "XXXXX",
"zip_code" : "XXXXXX"
}
I group all customer info by their email id, and here is my code:
db.getCollection('order').aggregate([
{ $group: { _id: "$email",
OrderInfo: {$push: {orderId: "$amazon_id", sku: "$sku", qty: "$qty", price:"$price"
}},
CustomerInfo: {$addToSet: {buyName: "$buy_name",reName: "$reci_name", email: "$email", street1: "$street1",
street2: "$street2", city: "$city", state: "$state", zipCode: "$zip_code"} }
}},
{ $project: {_id: 1, OrderInfo: 1, CustomerInfo:1, total_price:{$sum: "$OrderInfo.price"} }},
{ $match: {total_price: {$gt:100} } },
{ $sort: {total_price:-1}},
], { allowDiskUse: true } );
It shows me the result:
{
"_id" : "xxxxxxx#marketplace.amazon.com",
"OrderInfo" : [
{
"orderId" : "112",
"sku" : "NPC-50",
"qty" : 8,
"price" : 215.92
},
{
"orderId" : "112",
"sku" : "NPC-50",
"qty" : 1,
"price" : 26.99
},
{
"orderId" : "114",
"sku" : "NPC-50",
"qty" : 1,
"price" : 26.99
},
{
"orderId" : "114",
"sku" : "ABC",
"qty" : 1,
"price" : 19.99
},
{
"orderId" : "116",
"sku" : "ABC",
"qty" : 1,
"price" : 19.99
},
],
"CustomerInfo" : [
{
"buyName" : "xxxxxxxxx",
"reName" : "xxxxxxxxxxxx",
"email" : "xxxxxxxxxxxx#marketplace.amazon.com",
"street1" : "xxxxxxxxxxx",
"street2" : "",
"city" : "xxxxxxxxxx",
"state" : "xxxxxxxxxxxx",
"zipCode" : "xxxxxxxxxx"
},
{
"buyName" : "xxxxxxxxxx",
"reName" : "xxxxxx",
"email" : "xxxxxxxx#marketplace.amazon.com",
"street1" : "xxxxxxxxxxx",
"street2" : "",
"city" : "xxxxx",
"state" : "xxxx",
"zipCode" : "xxxxxxxx"
}
],
"total_price" : 309.88
}
However, I want to group the sku and sum up the qty and price in the OrderInfo Set. My expected output is something like:
{
"OrderInfo" : [
{
"sku": "NPC-50",
"qty": 10,
"price": 269.9
},
{
"sku": "ABC",
"qty": 2,
"price": 39.98
},
],
"CustomerInfo" : [
{
"buyName" : "xxxxxxxxx",
"reName" : "xxxxxxxxxxxx",
"email" : "xxxxxxxxxxxx#marketplace.amazon.com",
"street1" : "xxxxxxxxxxx",
"street2" : "",
"city" : "xxxxxxxxxx",
"state" : "xxxxxxxxxxxx",
"zipCode" : "xxxxxxxxxx"
},
{
"buyName" : "xxxxxxxxxx",
"reName" : "xxxxxx",
"email" : "xxxxxxxx#marketplace.amazon.com",
"street1" : "xxxxxxxxxxx",
"street2" : "",
"city" : "xxxxx",
"state" : "xxxx",
"zipCode" : "xxxxxxxx"
}
],
"total_price" : 309.88
}
Any Help will be appreciated.
You can use below aggregation.
db.order.aggregate([
{"$group":{
"_id":{"email":"$email","sku":"$sku"},
"qty":{"$sum":"$qty"},
"price":{"$sum":"$price"},
"CustomerInfo":{
"$addToSet":{
"buyName":"$buy_name",
"reName":"$reci_name",
"email":"$email",
"street1":"$street1",
"street2":"$street2",
"city":"$city",
"state":"$state",
"zipCode":"$zip_code"
}
}
}},
{"$group":{
"_id":"$_id.email",
"OrderInfo":{"$push":{"sku":"$_id.sku","qty":"$qty","price":"$price"}},
"total_price":{"$sum":"$price"},
"CustomerInfo":{"$first":"$CustomerInfo"}
}},
{"$match":{"total_price":{"$gt":100}}},
{"$sort":{"total_price":-1}}
])
You can try below aggregation
db.collection.aggregate([
{ "$group": {
"_id": {
"email": "$email",
"sku": "$sku"
},
"CustomerInfo": {
"$addToSet": {
"buyName": "$buy_name",
"otherFields": "$otherFields",
}
},
"price": { "$sum": "$price" },
"qty": { "$sum": "$qty" }
}},
{ "$group": {
"_id": "$_id.email",
"CustomerInfo": { "$first": "$CustomerInfo" },
"OrderInfo": {
"$push": {
"sku": "$_id.sku",
"qty": "$qty",
"price": "$price"
}
}
}}
])
I have the following query, what I want is to have a combined group of custom group field names, with field value.
db.getCollection('mycollection').aggregate([
{"$match":{
"expireDate":{"$gte":"2018-02-06T00:00:00.000Z"},
"publishDate":{"$lte":"2018-02-06T00:00:00.000Z"},
"isPublished":true,"isDrafted":false,
"deletedAt":{"$eq":null},"deleted":false
}},
{"$group":{
"twentyFourHourAgo":{
"$sum":{
"$cond":[
{"$gt":["$publishDate","2018-02-04T08:48:16.892Z"]},1,0
]
}
},
"fortyEightHourAgo":{
"$sum":{
"$cond":[
{"$gt":["$publishDate","2018-02-01T08:48:16.892Z"]},1,0
]
}
},
"thirtyDaysAgo":{
"$sum":{
"$cond":[
{"$gt":["$publishDate","2017-12-31T08:48:16.892Z"]},1,0
]
}
},
"_id":{
"position":{"$ifNull":["$position","Unknown"]},
"workType":{"$ifNull":["$workType","Unknown"]},
"functionalArea":{"$ifNull":["$functionalArea","Unknown"]},
"minimumEducation":{"$ifNull":["$minimumEducation","Unknown"]},
"gender":{"$ifNull":["$gender","Unknown"]},
"contractType":{"$ifNull":["$contractType","Unknown"]},
"locations":{"$ifNull":["$locations","Unknown"]},
"requiredLanguages":{"$ifNull":["$requiredLanguages","Unknown"]},
"company":{"$ifNull":["$company.name","Unknown"]}},"count":{"$sum":1}
}
},
{"$group":{
"_id":null,
"twentyFourHourAgo":{
"$sum":"twentyFourHourAgo"
},
"fortyEightHourAgo":{
"$sum":"$fortyEightHourAgo"
},
"thirtyDaysAgo":{
"$sum":"$thirtyDaysAgo"
},
"position":{"$addToSet":{"Name":"$_id.position","Count":"$count"}},
"workType":{"$addToSet":{"Name":"$_id.workType","Count":"$count"}},
"functionalArea":{
"$addToSet":{"Name":"$_id.functionalArea","Count":"$count"}
},
"minimumEducation":{
"$addToSet":{"Name":"$_id.minimumEducation","Count":"$count"}
},
"gender":{"$addToSet":{"Name":"$_id.gender","Count":"$count"}},"contractType":{"$addToSet":{"Name":"$_id.contractType","Count":"$count"}},"locations":{"$addToSet":{"Name":"$_id.locations","Count":"$count"}},"requiredLanguages":{"$addToSet":{"Name":"$_id.requiredLanguages","Count":"$count"}},"company":{"$addToSet":{"Name":"$_id.company","Count":"$count"}}}}]
)
my document inside collection schema is like:
/* 1 */
{
"_id" : ObjectId("59e4540bf14f1607b90ffb81"),
"vacancyNumber" : "1",
"position" : "Software Tester",
"publishDate" : ISODate("2018-01-02T00:00:00.000Z"),
"expireDate" : ISODate("2018-05-29T00:00:00.000Z"),
"yearsOfExperience" : 40,
"minimumEducation" : "Doctorate",
"functionalArea" : "Education",
"company" : {
"id" : ObjectId("59e453fbf14f1607b90ffb80"),
"name" : "First Company",
"profile" : "profile",
"logo" : {
"container" : "companyFiles",
"name" : "abbbff58cd3fda2c59ab2ee620ea5aa0",
"mime" : ".png",
"size" : 5806
}
},
"durations" : {
"years" : 3,
"months" : 4
},
"probationPeriod" : {
"duration" : 34,
"unit" : "month"
},
"salary" : {
"minSalary" : 1000,
"maxSalary" : 2000,
"currency" : "USD",
"period" : "monthly",
"isNegotiable" : true
},
"locations" : [
"Germany",
"Itly",
"Iran"
],
"canApplyOnline" : true,
"skills" : [
"Skill1",
"Skill2",
"Skill3",
"Skill4"
],
"requiredLanguages" : [
"Arabic",
"English",
"Russian",
"Dari",
"French"
],
"keywords" : [
"Key1",
"Key2"
],
"deleted" : false,
"deletedAt" : null,
"isDrafted" : false,
"isPublished" : true,
"requiresTravel" : true,
"gender" : "male",
"nationalities" : [
"afghan"
],
"workType" : "Full Time",
"contractType" : "Permanent",
}
/* 2 */
{
"_id" : ObjectId("59f9402e05d04ebe5653d98f"),
"vacancyNumber" : "1",
"position" : "Software Engineer",
"publishDate" : ISODate("2018-01-03T00:00:00.000Z"),
"expireDate" : ISODate("2018-11-10T00:00:00.000Z"),
"yearsOfExperience" : 40,
"minimumEducation" : "Doctorate",
"functionalArea" : "Education",
"company" : {
"id" : ObjectId("59e453fbf14f1607b90ffb80"),
"name" : "First Company",
"profile" : "profile",
"logo" : {
"container" : "logo container",
"name" : "logo name",
"mime" : "logo mime type",
"size" : 1
}
},
"durations" : {
"years" : 3,
"months" : 4
},
"probationPeriod" : {
"duration" : 34,
"unit" : "month"
},
"salary" : {
"minSalary" : 1000,
"maxSalary" : 2000,
"currency" : "USD",
"period" : "monthly",
"isNegotiable" : true
},
"locations" : [
"Afghanistan",
"Itly",
"Iran"
],
"skills" : [
"Skill1",
"Another Skill"
],
"requiredLanguages" : [
"Arabic",
"English",
"Russian",
"Dari",
"French"
],
"keywords" : [
"Keyword",
"Key1"
],
"deleted" : false,
"deletedAt" : null,
"isDrafted" : false,
"isPublished" : true,
"gender" : "male",
"nationalities" : [
"afghan",
"iranian"
],
"workType" : "Full Time",
"contractType" : "Short-Term",
}
/* 3 */
{
"_id" : ObjectId("5a03235234f7504f13970abd"),
"vacancyNumber" : "1",
"position" : "Software Tester",
"publishDate" : ISODate("2017-10-10T00:00:00.000Z"),
"expireDate" : ISODate("2018-11-25T00:00:00.000Z"),
"yearsOfExperience" : 40,
"minimumEducation" : "Doctorate",
"functionalArea" : "IT Software",
"company" : {
"id" : ObjectId("59e453fbf14f1607b90ffb80"),
"name" : "My First Company",
"profile" : "profile",
"logo" : {
"container" : "logo container",
"name" : "logo name",
"mime" : "logo mime type",
"size" : 1
}
},
"durations" : {
"years" : 3,
"months" : 4
},
"probationPeriod" : {
"duration" : 34,
"unit" : "month"
},
"salary" : {
"minSalary" : 1000,
"maxSalary" : 2000,
"currency" : "USD",
"period" : "monthly",
"isNegotiable" : true
},
"locations" : [
"Germany",
"Itly",
"Iran"
],
"skills" : [
"Skill1",
"Test Skill"
],
"requiredLanguages" : [
"Arabic",
"English",
"Russian",
"Dari",
"French"
],
"keywords" : [
"Test Key",
"Keyword"
],
"deleted" : false,
"deletedAt" : null,
"isDrafted" : false,
"isPublished" : true,
"gender" : "female",
"nationalities" : [
"afghan"
],
"workType" : "Part Time",
"contractType" : "Permanent",
}
Now I want to count the group of data by my custom expression check 'twentyFourHourAgo, fortyEightHourAgo, thirtyDaysAgo', and also by the value of a field (functionalArea, position, locations, keywords, workType).
My current query result is
{
"_id" : null,
"twentyFourHourAgo" : 0,
"fortyEightHourAgo" : 0.0,
"thirtyDaysAgo" : 2.0,
"position" : [
{
"Name" : "Software Engineer",
"Count" : 1.0
},
{
"Name" : "Software Tester",
"Count" : 1.0
}
],
"workType" : [
{
"Name" : "Full Time",
"Count" : 1.0
},
{
"Name" : "Part Time",
"Count" : 1.0
}
],
"functionalArea" : [
{
"Name" : "Education",
"Count" : 1.0
},
{
"Name" : "IT Software",
"Count" : 1.0
}
],
"minimumEducation" : [
{
"Name" : "Doctorate",
"Count" : 1.0
}
],
"gender" : [
{
"Name" : "male",
"Count" : 1.0
},
{
"Name" : "female",
"Count" : 1.0
}
],
"contractType" : [
{
"Name" : "Short-Term",
"Count" : 1.0
},
{
"Name" : "Permanent",
"Count" : 1.0
}
],
"locations" : [
{
"Name" : [
"Afghanistan",
"Itly",
"Iran"
],
"Count" : 1.0
},
{
"Name" : [
"Germany",
"Itly",
"Iran"
],
"Count" : 1.0
}
],
"requiredLanguages" : [
{
"Name" : [
"Arabic",
"English",
"Russian",
"Dari",
"French"
],
"Count" : 1.0
}
],
"company" : [
{
"Name" : "First Company",
"Count" : 1.0
},
{
"Name" : "My First Company",
"Count" : 1.0
}
]
}
As you see, I have three document that has following properties:
Two document that has the same position Software Tester, but query return 1 Software Tester (It means if I have multiple documents that have some common values in specific columns, their count result is wrong). The same problem exists for other fields 'contractType, workType, etc...'.
In array-type fields such as locations, my first document has Germany, Italy, Iran values in locations array, my second document has Afghanistan, Italy, Iran, and my third document has Germany, Italy, Iran. But query result is like this:
"locations" : [
{
"Name" : [
"Afghanistan",
"Itly",
"Iran"
],
"Count" : 1.0
},
{
"Name" : [
"Germany",
"Itly",
"Iran"
],
"Count" : 1.0
}
],
This should be like: Germany => 2, Italy,Iran => 3, and Afghanistan => 1
The same problem exists for other array type fields.
This give you what you were asking:
db.getCollection('foo').aggregate([
{"$match":{
"expireDate":{"$gte": ISODate("2018-01-02T00:00:00.000Z")},
"publishDate":{"$lte": ISODate("2018-05-29T00:00:00.000Z")},
"isPublished":true,"isDrafted":false,
"deletedAt":{"$eq":null},
"deleted":false
}},
{"$group":{
"twentyFourHourAgo":{
"$sum":{
"$cond":[
{"$gte":["$publishDate", ISODate("2018-01-02T00:00:00.000Z")]},1,0
]
}
},
"fortyEightHourAgo":{
"$sum":{
"$cond":[
{"$gte":["$publishDate", ISODate("2018-01-02T00:00:00.000Z")]},1,0
]
}
},
"thirtyDaysAgo":{
"$sum":{
"$cond":[
{"$gte":["$publishDate", ISODate("2018-01-02T00:00:00.000Z")]},1,0
]
}
},
"_id":{
"$ifNull":["$functionalArea","Unknown"]
},
/* Changes start from here */
"count" : { "$sum" : 1 } } },
{ "$group" : {
"_id" : "null", "fortyEightHourAgo" : { "$sum" : "$fortyEightHourAgo"},
"thirtyDaysAgo" : { "$sum" : "$thirtyDaysAgo"},
"twentyFourHourAgo" : { "$sum" : "$twentyFourHourAgo"},
"functionalArea" : { "$addToSet" : { "Name": "$_id", "Count" : "$count" } } }}
])
Output:
{
"_id" : null,
"fortyEightHourAgo" : 3.0,
"thirtyDaysAgo" : 3.0,
"twentyFourHourAgo" : 3.0,
"functionalArea" : [
{
"Name" : "Education",
"Count" : 1.0
},
{
"Name" : "IT Software",
"Count" : 2.0
}
]
}
I have the following query, what I want is to have a combined group of custom group field names, with field value.
db.getCollection('mycollection').aggregate([
{"$match":{
"expireDate":{"$gte":"2018-02-06T00:00:00.000Z"},
"publishDate":{"$lte":"2018-02-06T00:00:00.000Z"},
"isPublished":true,"isDrafted":false,
"deletedAt":{"$eq":null},"deleted":false
}},
{"$group":{
"twentyFourHourAgo":{
"$sum":{
"$cond":[
{"$gt":["$publishDate","2018-02-04T08:48:16.892Z"]},1,0
]
}
},
"fortyEightHourAgo":{
"$sum":{
"$cond":[
{"$gt":["$publishDate","2018-02-01T08:48:16.892Z"]},1,0
]
}
},
"thirtyDaysAgo":{
"$sum":{
"$cond":[
{"$gt":["$publishDate","2017-12-31T08:48:16.892Z"]},1,0
]
}
},
"_id":{
"position":{"$ifNull":["$position","Unknown"]},
"workType":{"$ifNull":["$workType","Unknown"]},
"functionalArea":{"$ifNull":["$functionalArea","Unknown"]},
"minimumEducation":{"$ifNull":["$minimumEducation","Unknown"]},
"gender":{"$ifNull":["$gender","Unknown"]},
"contractType":{"$ifNull":["$contractType","Unknown"]},
"locations":{"$ifNull":["$locations","Unknown"]},
"requiredLanguages":{"$ifNull":["$requiredLanguages","Unknown"]},
"company":{"$ifNull":["$company.name","Unknown"]}},"count":{"$sum":1}
}
},
{"$group":{
"_id":null,
"twentyFourHourAgo":{
"$sum":"twentyFourHourAgo"
},
"fortyEightHourAgo":{
"$sum":"$fortyEightHourAgo"
},
"thirtyDaysAgo":{
"$sum":"$thirtyDaysAgo"
},
"position":{"$addToSet":{"Name":"$_id.position","Count":"$count"}},
"workType":{"$addToSet":{"Name":"$_id.workType","Count":"$count"}},
"functionalArea":{
"$addToSet":{"Name":"$_id.functionalArea","Count":"$count"}
},
"minimumEducation":{
"$addToSet":{"Name":"$_id.minimumEducation","Count":"$count"}
},
"gender":{"$addToSet":{"Name":"$_id.gender","Count":"$count"}},"contractType":{"$addToSet":{"Name":"$_id.contractType","Count":"$count"}},"locations":{"$addToSet":{"Name":"$_id.locations","Count":"$count"}},"requiredLanguages":{"$addToSet":{"Name":"$_id.requiredLanguages","Count":"$count"}},"company":{"$addToSet":{"Name":"$_id.company","Count":"$count"}}}}]
)
my document inside collection schema is like:
/* 1 */
{
"_id" : ObjectId("59e4540bf14f1607b90ffb81"),
"vacancyNumber" : "1",
"position" : "Software Tester",
"publishDate" : ISODate("2018-01-02T00:00:00.000Z"),
"expireDate" : ISODate("2018-05-29T00:00:00.000Z"),
"yearsOfExperience" : 40,
"minimumEducation" : "Doctorate",
"functionalArea" : "Education",
"company" : {
"id" : ObjectId("59e453fbf14f1607b90ffb80"),
"name" : "First Company",
"profile" : "profile",
"logo" : {
"container" : "companyFiles",
"name" : "abbbff58cd3fda2c59ab2ee620ea5aa0",
"mime" : ".png",
"size" : 5806
}
},
"durations" : {
"years" : 3,
"months" : 4
},
"probationPeriod" : {
"duration" : 34,
"unit" : "month"
},
"salary" : {
"minSalary" : 1000,
"maxSalary" : 2000,
"currency" : "USD",
"period" : "monthly",
"isNegotiable" : true
},
"locations" : [
"Germany",
"Itly",
"Iran"
],
"canApplyOnline" : true,
"skills" : [
"Skill1",
"Skill2",
"Skill3",
"Skill4"
],
"requiredLanguages" : [
"Arabic",
"English",
"Russian",
"Dari",
"French"
],
"keywords" : [
"Key1",
"Key2"
],
"deleted" : false,
"deletedAt" : null,
"isDrafted" : false,
"isPublished" : true,
"requiresTravel" : true,
"gender" : "male",
"nationalities" : [
"afghan"
],
"workType" : "Full Time",
"contractType" : "Permanent",
}
/* 2 */
{
"_id" : ObjectId("59f9402e05d04ebe5653d98f"),
"vacancyNumber" : "1",
"position" : "Software Engineer",
"publishDate" : ISODate("2018-01-03T00:00:00.000Z"),
"expireDate" : ISODate("2018-11-10T00:00:00.000Z"),
"yearsOfExperience" : 40,
"minimumEducation" : "Doctorate",
"functionalArea" : "Education",
"company" : {
"id" : ObjectId("59e453fbf14f1607b90ffb80"),
"name" : "First Company",
"profile" : "profile",
"logo" : {
"container" : "logo container",
"name" : "logo name",
"mime" : "logo mime type",
"size" : 1
}
},
"durations" : {
"years" : 3,
"months" : 4
},
"probationPeriod" : {
"duration" : 34,
"unit" : "month"
},
"salary" : {
"minSalary" : 1000,
"maxSalary" : 2000,
"currency" : "USD",
"period" : "monthly",
"isNegotiable" : true
},
"locations" : [
"Afghanistan",
"Itly",
"Iran"
],
"skills" : [
"Skill1",
"Another Skill"
],
"requiredLanguages" : [
"Arabic",
"English",
"Russian",
"Dari",
"French"
],
"keywords" : [
"Keyword",
"Key1"
],
"deleted" : false,
"deletedAt" : null,
"isDrafted" : false,
"isPublished" : true,
"gender" : "male",
"nationalities" : [
"afghan",
"iranian"
],
"workType" : "Full Time",
"contractType" : "Short-Term",
}
/* 3 */
{
"_id" : ObjectId("5a03235234f7504f13970abd"),
"vacancyNumber" : "1",
"position" : "Software Tester",
"publishDate" : ISODate("2017-10-10T00:00:00.000Z"),
"expireDate" : ISODate("2018-11-25T00:00:00.000Z"),
"yearsOfExperience" : 40,
"minimumEducation" : "Doctorate",
"functionalArea" : "IT Software",
"company" : {
"id" : ObjectId("59e453fbf14f1607b90ffb80"),
"name" : "My First Company",
"profile" : "profile",
"logo" : {
"container" : "logo container",
"name" : "logo name",
"mime" : "logo mime type",
"size" : 1
}
},
"durations" : {
"years" : 3,
"months" : 4
},
"probationPeriod" : {
"duration" : 34,
"unit" : "month"
},
"salary" : {
"minSalary" : 1000,
"maxSalary" : 2000,
"currency" : "USD",
"period" : "monthly",
"isNegotiable" : true
},
"locations" : [
"Germany",
"Itly",
"Iran"
],
"skills" : [
"Skill1",
"Test Skill"
],
"requiredLanguages" : [
"Arabic",
"English",
"Russian",
"Dari",
"French"
],
"keywords" : [
"Test Key",
"Keyword"
],
"deleted" : false,
"deletedAt" : null,
"isDrafted" : false,
"isPublished" : true,
"gender" : "female",
"nationalities" : [
"afghan"
],
"workType" : "Part Time",
"contractType" : "Permanent",
}
Now I want to count the group of data by my custom expression check 'twentyFourHourAgo, fortyEightHourAgo, thirtyDaysAgo', and also by the value of a field (functionalArea, position, locations, keywords, workType).
My current query result is
{
"_id" : null,
"twentyFourHourAgo" : 0,
"fortyEightHourAgo" : 0.0,
"thirtyDaysAgo" : 2.0,
"position" : [
{
"Name" : "Software Engineer",
"Count" : 1.0
},
{
"Name" : "Software Tester",
"Count" : 1.0
}
],
"workType" : [
{
"Name" : "Full Time",
"Count" : 1.0
},
{
"Name" : "Part Time",
"Count" : 1.0
}
],
"functionalArea" : [
{
"Name" : "Education",
"Count" : 1.0
},
{
"Name" : "IT Software",
"Count" : 1.0
}
],
"minimumEducation" : [
{
"Name" : "Doctorate",
"Count" : 1.0
}
],
"gender" : [
{
"Name" : "male",
"Count" : 1.0
},
{
"Name" : "female",
"Count" : 1.0
}
],
"contractType" : [
{
"Name" : "Short-Term",
"Count" : 1.0
},
{
"Name" : "Permanent",
"Count" : 1.0
}
],
"locations" : [
{
"Name" : [
"Afghanistan",
"Itly",
"Iran"
],
"Count" : 1.0
},
{
"Name" : [
"Germany",
"Itly",
"Iran"
],
"Count" : 1.0
}
],
"requiredLanguages" : [
{
"Name" : [
"Arabic",
"English",
"Russian",
"Dari",
"French"
],
"Count" : 1.0
}
],
"company" : [
{
"Name" : "First Company",
"Count" : 1.0
},
{
"Name" : "My First Company",
"Count" : 1.0
}
]
}
As you see, I have three document that has following properties:
Two document that has the same position Software Tester, but query return 1 Software Tester (It means if I have multiple documents that have some common values in specific columns, their count result is wrong). The same problem exists for other fields 'contractType, workType, etc...'.
In array-type fields such as locations, my first document has Germany, Italy, Iran values in locations array, my second document has Afghanistan, Italy, Iran, and my third document has Germany, Italy, Iran. But query result is like this:
"locations" : [
{
"Name" : [
"Afghanistan",
"Itly",
"Iran"
],
"Count" : 1.0
},
{
"Name" : [
"Germany",
"Itly",
"Iran"
],
"Count" : 1.0
}
],
This should be like: Germany => 2, Italy,Iran => 3, and Afghanistan => 1
The same problem exists for other array type fields.
Apologies I misunderstood your question earlier. To be able to $unwind the location array, but NOT effect your twentyFourHourAgo etc you could look at using $first.
You'll need to $unwind any array if you wish count/sum the individual elements.
Example of how using $first.
db.getCollection('foo').aggregate([
{ $unwind : "$locations" },
{ "$group" : { "_id" : "$_id",
"twentyFourHourAgo":{ $first : {
"$sum" : { "$cond":[
{"$gt":["$publishDate", ISODate("2016-10-10T00:00:00.000Z")]},1,0 ] } } },
"fortyEightHourAgo" : { $first : {
"$sum" : { "$cond" : [
{ "$gt" : [ "$publishDate","2018-01-02T00:00:00.000Z"]},1,0 ] } } },
"thirtyDaysAgo" : { $first : {
"$sum" : { "$cond" : [
{ "$gt" : [ "$publishDate","2017-12-31T08:48:16.892Z"]},1,0 ] } } },
} },
{ "$group" : { "_id" : null,
"twentyFourHourAgo" : { "$sum" : "$twentyFourHourAgo" },
"fortyEightHourAgo" : { "$sum" : "$fortyEightHourAgo" },
"thirtyDaysAgo" : { "$sum" : "$thirtyDaysAgo" },
}}
])
Output:
"_id" : null,
"twentyFourHourAgo" : 0,
"fortyEightHourAgo" : 3.0,
"thirtyDaysAgo" : 3.0,
Please see here $first for further information on why I think it might be of use. I've stuck an $unwind at the beginning to help prove that it will solve the problem in your OP.
I have following structure in my collection:
users:[
{
"name":"ABC",
"address":{
"city":"London",
"country":"UK",
}
},
{
"name":"XYZ",
"address":{
"city":"London",
"country":"UK",
}
},
{
"name":"PQR",
"address":{
"city":"NewYork",
"country":"US",
}
}
]
I want count of number of occurrences of 'city' key in 'address' and 'name' as a result.
I want to query above collection and want following output:
[{
"name":"ABC",
"city":"London",
"count":2
},{
"name":"XYZ",
"city":"London",
"count":2
}, {
"name":"PQR",
"city":"NewYork",
"count":1
}
]
I simulated your collection
{
"_id" : ObjectId("547c30ae371ea419f07b9550"),
"users" : [
{
"name" : "ABC",
"address" : {
"city" : "London",
"country" : "UK"
}
},
{
"name" : "XYZ",
"address" : {
"city" : "London",
"country" : "UK"
}
},
{
"name" : "PQR",
"address" : {
"city" : "NewYork",
"country" : "US"
}
}
]
}
And then I use aggregate framework
db.coll.aggregate([
{
$unwind:"$users"
},
{
$group:{
_id:"$users.address.city",
name:{$push:"$users.name"},
city:{$first:"$users.address.city"},
count:{$sum:1}
}
},{
$unwind:"$name"
},{
$project:{
_id:0,
"city":"$_id",
"name":1,
"city":1,
"count":1
}
}])
result:
{
"result" : [
{
"name" : "PQR",
"city" : "NewYork",
"count" : 1
},
{
"name" : "ABC",
"city" : "London",
"count" : 2
},
{
"name" : "XYZ",
"city" : "London",
"count" : 2
}
],
"ok" : 1
}
UPDATE AFTER QUESTION
I added a new Document
{
"_id" : ObjectId("547c394c371ea419f07b9551"),
"users" : [
{
"address" : {
"city" : "Livorno",
"country" : "LI"
}
},
{
"address" : {
"city" : "Livorno",
"country" : "LI"
}
},
{
"address" : {
"city" : "NewYork",
"country" : "US"
}
}
]
}
and new Query
db.coll.aggregate([
{
$unwind:"$users"
},
{
$group:{
_id:"$users.address.city",
"name": {
$push:{"$ifNull": ["$users.name","$_id"]}
},
city:{$first:"$users.address.city"},
count:{$sum:1}
}
},{
$unwind:"$name"
},{
$project:{
_id:0,
"city":"$_id",
"name":1,
"city":1,
"count":1
}
}])
Result:
{
"result" : [
{
"name" : "PQR",
"city" : "NewYork",
"count" : 2
},
{
"name" : ObjectId("547c394c371ea419f07b9551"),
"city" : "NewYork",
"count" : 2
},
{
"name" : ObjectId("547c394c371ea419f07b9551"),
"city" : "Livorno",
"count" : 2
},
{
"name" : ObjectId("547c394c371ea419f07b9551"),
"city" : "Livorno",
"count" : 2
},
{
"name" : "ABC",
"city" : "London",
"count" : 2
},
{
"name" : "XYZ",
"city" : "London",
"count" : 2
}
],
"ok" : 1
}