I have a collection in which each object contains details of the user along with the comments user has given on specific products which is given below
{
"_id" : ObjectId("51efcbc8786df13540e46887"),
"value": {
"UserDetails" : [
[
{
"country" : "CA",
"gender" : "M",
"age" : "18",
"userIdtemp" : ObjectId("51efcbc8786df13540e46887")
}
]
],
"comments" : [
{
"commentId" : ObjectId("51efcc41786df13540e46891"),
"comment" : "Hey, what's up?",
"created" : ISODate("2013-07-24T12:44:49.400Z"),
"productId" : ObjectId("51efcbd4786df13540e4688c"),
"userId" : ObjectId("51efcbc8786df13540e46887")
},
{
"commentId" : ObjectId("51efcc43786df13540e46893"),
"comment" : "Cool",
"created" : ISODate("2013-07-24T12:44:51.004Z"),
"productId" : ObjectId("51efcbd2786df13540e4688b"),
"userId" : ObjectId("51efcbc8786df13540e46887")
}
]
}
}
{
"_id" : ObjectId("51efcbc8786df13540e46888"),
"value" : {
"UserDetails" : [
[
{
"country" : "US",
"gender" : "M",
"age" : "25",
"userIdtemp" : ObjectId("51efcbc8786df13540e46888")
}
]
],
"comments" : [
{
"commentId" : ObjectId("51efcc41786df13540e46892"),
"comment" : "Not much",
"created" : ISODate("2013-07-24T12:44:49.475Z"),
"productId" : ObjectId("51efcbd4786df13540e4688c"),
"userId" : ObjectId("51efcbc8786df13540e46888")
}
]
}
}
{
"_id" : ObjectId("51efcbc8786df13540e46889"),
"value" : {
"UserDetails" : [
{
"country" : "US",
"gender" : "F",
"age" : "13",
"userIdtemp" : ObjectId("51efcbc8786df13540e46889")
}
]
}
}
I have to extract comments separately along with there userDetails with key as productId so i have written map something like following
mapCommentsFrom = function(){
if("comments" in this.value)
{
for(var idx = 0;idx<this.value.comments.length;idx++){
var key = this.value.comments[idx].productId;
var value = [{
commentId: this.value.comments[idx].commentId,
comment:this.value.comments[idx].comment,
created:this.value.comments[idx].created,
productId:this.value.comments[idx].productId,
userId:this.value.comments[idx].userId,
country:this.value.UserDetails[0][0].country,
gender:this.value.UserDetails[0][0].gender,
age : this.value.UserDetails[0][0].age
}]
}
}
emit(key,value);
}
reduceFrom = function(k,values){
return values;
}
but where ever the number of comments are more than one i am getting only the last comment along with user details and other's key as well as value is coming null. Something like this
{ "_id" : null, "value" : null }
{
"_id" : ObjectId("51efcbd2786df13540e4688b"),
"value" : [
{
"length" : 2,
"commentId" : ObjectId("51efcc43786df13540e46893"),
"comment" : "Cool",
"created" : ISODate("2013-07-24T12:44:51.004Z"),
"productId" : ObjectId("51efcbd2786df13540e4688b"),
"userId" : ObjectId("51efcbc8786df13540e46887"),
"country" : "CA",
"gender" : "M",
"age" : "18"
}
]
}
{
"_id" : ObjectId("51efcbd4786df13540e4688c"),
"value" : [
{
"length" : 1,
"commentId" : ObjectId("51efcc41786df13540e46892"),
"comment" : "Not much",
"created" : ISODate("2013-07-24T12:44:49.475Z"),
"productId" : ObjectId("51efcbd4786df13540e4688c"),
"userId" : ObjectId("51efcbc8786df13540e46888"),
"country" : "US",
"gender" : "M",
"age" : "25"
}
]
}
Can somebody please help me as to what i am missing?
Thanks for help in advance
I cannot add comments due to reputation. But had you considered using the aggregation framework.
The $unwind operator will return you an array of sub documents quite easily and it's faster than using map/reduce.
I'm not sure it will exactly do what you're looking for but may help.
Take a look, http://docs.mongodb.org/manual/reference/aggregation/unwind/
Its because you are not emitting them in the map function.
Move the emit function inside the for loop.
mapCommentsFrom = function(){
if("comments" in this.value){
for(var idx = 0;idx<this.value.comments.length;idx++){
var key = this.value.comments[idx].productId;
var value = {
commentId: this.value.comments[idx].commentId,
comment:this.value.comments[idx].comment,
created:this.value.comments[idx].created,
productId:this.value.comments[idx].productId,
userId:this.value.comments[idx].userId,
country:this.value.UserDetails[0][0].country,
gender:this.value.UserDetails[0][0].gender,
age : this.value.UserDetails[0][0].age
}
emit(key,value);
}
}
}
Then you may also need to rewrite your reduce function to something like this
reduceFrom = function(k,valueArray){
var returnData = { values : [] } ;
for(var i=0;i<valueArray.length;i++)
returnData.values.push(valueArray[i]);
return returnData;
}
By far the easiest is to just use the aggregation framework for this. The aggregation framework allows you to execute operators on data, there is $match for doing queries (like find()) and various others. See for more information: http://docs.mongodb.org/manual/core/aggregation/
The aggregation framework also has an $unwind function that does exactly what you want. You use it like:
db.collection.aggregate( [
{ $unwind: '$value.comments' },
{ $project: {
_id: '$value.comments.productId',
value: 1
} }
] );
On your sample documents, this returns:
{
"result" : [
{
"_id" : ObjectId("51efcbd4786df13540e4688c"),
"value" : {
"UserDetails" : [
[
{
"country" : "CA",
"gender" : "M",
"age" : "18",
"userIdtemp" : ObjectId("51efcbc8786df13540e46887")
}
]
],
"comments" : {
"commentId" : ObjectId("51efcc41786df13540e46891"),
"comment" : "Hey, what's up?",
"created" : ISODate("2013-07-24T12:44:49.400Z"),
"productId" : ObjectId("51efcbd4786df13540e4688c"),
"userId" : ObjectId("51efcbc8786df13540e46887")
}
}
},
{
"_id" : ObjectId("51efcbd2786df13540e4688b"),
"value" : {
"UserDetails" : [
[
{
"country" : "CA",
"gender" : "M",
"age" : "18",
"userIdtemp" : ObjectId("51efcbc8786df13540e46887")
}
]
],
"comments" : {
"commentId" : ObjectId("51efcc43786df13540e46893"),
"comment" : "Cool",
"created" : ISODate("2013-07-24T12:44:51.004Z"),
"productId" : ObjectId("51efcbd2786df13540e4688b"),
"userId" : ObjectId("51efcbc8786df13540e46887")
}
}
},
{
"_id" : ObjectId("51efcbd4786df13540e4688c"),
"value" : {
"UserDetails" : [
[
{
"country" : "US",
"gender" : "M",
"age" : "25",
"userIdtemp" : ObjectId("51efcbc8786df13540e46888")
}
]
],
"comments" : {
"commentId" : ObjectId("51efcc41786df13540e46892"),
"comment" : "Not much",
"created" : ISODate("2013-07-24T12:44:49.475Z"),
"productId" : ObjectId("51efcbd4786df13540e4688c"),
"userId" : ObjectId("51efcbc8786df13540e46888")
}
}
}
],
"ok" : 1
}
Related
I am using mongoDB as backend server, I have nested array(one level array) like this
{
"_id" : ObjectId("60b1fc6d3c43f74e0c1dba92"),
"seriesId" : "60acebf73acb5b3a98d14331",
"name" : "Season 1",
"logoURL" : "uploads/season/1622277216401.png",
"yearOfPublish" : "2021-05-29",
"description" : "Season 1",
"createdBy" : ObjectId("609cbf49ba46cc3924859ab5"),
"createdOn" : "2021-05-29T08:33:49.480Z",
"episode" : [
{
"seasonId" : "60b1fc6d3c43f74e0c1dba92",
"name" : "Episode 1",
"id" : 0,
"logoURL" : "uploads/episode/1622278616899.png",
"dateOfTelecast" : null,
"description" : "sadfgh",
"duration" : "30",
"videoType" : "customURL",
"embedCode" : "",
"url" : "https://youtu.be/kbpsXMUr7ss",
"liveboxChannel" : "",
"createdOn" : "2021-05-29T08:56:59.230Z",
"createdBy" : ObjectId("609cbf49ba46cc3924859ab5"),
"_id" : "ZaVrpOLO5"
},
{
"seasonId" : "60b1fc6d3c43f74e0c1dba92",
"name" : "Episode 2",
"id" : 0,
"logoURL" : "uploads/episode/1622279206607.png",
"dateOfTelecast" : null,
"description" : "adfd",
"duration" : "30",
"videoType" : "customURL",
"embedCode" : "",
"url" : "https://youtu.be/kbpsXMUr7ss",
"liveboxChannel" : "",
"createdOn" : "2021-05-29T09:06:48.637Z",
"createdBy" : ObjectId("609cbf49ba46cc3924859ab5"),
"_id" : "9GKqXhxcH"
},}
I have more no of seasons. from the season collection,i have episode array under the name of Episode.
Now My frontend page required that episode array alone.
response = {episode: all the episode data} and this episode data is based on skip and limit value
I have tried something in mongodb,
db.getCollection('season_copy').aggregate([
{$project: {
episodes: {
$cond:{ if: { $isArray: "$episode" }, then: { input:"$episode" }, else: 0 }
},
},
},
])
Can anyone suggest me some idea?
Check this out:
Without aggregate:
db.getCollection('season_copy')
.find({ _id: ObjectID(id)})
.project({ episode: 1 }).toArray();
With aggregate:
MongoDB playground
db.getCollection('season_copy')
.aggregate([
{
$match: {
_id: ObjectId("60b1fc6d3c43f74e0c1dba92")
}
},
{
$project: {
episode: 1
}
}
])
I've 1000's of users and user data looks like the below.
Some users have the devices as [{some data}] (array), some users have devices as {some data}, and some users have devices as empty [].
I need mongodb query to find the userslist with devices {some data}.
Here is the sample of my users data.
{
"_id" : ObjectId("56fe07bab95708fa18d45ac4"),
"username" : "abcd",
"devices" : []
},
{
"_id" : ObjectId("56fe07bab95708fa18d45df7"),
"username" : "efgh",
"devices" : [
{
"_id" : ObjectId("5827804ef659a60400e12fcb"),
"devicetype" : "web"
}
],
},
{
"_id" : ObjectId("56fe07bab95708fa18d45ae8"),
"username" : "efgh",
"devices" : {
"_id" : ObjectId("5951ea8b47abe300046ea26e"),
"devicetype" : "web"
}
},
{
"_id" : ObjectId("56fe07bab95708fa18d45b5b"),
"username" : "ijkl",
"devices" : [
{
"_id" : ObjectId("59bd2317eeff3200049a2ba6"),
"devicetype" : "ios"
"devicetoken" : "1abffaa4419d498b48d0bf982"
}
],
},
{
"_id" : ObjectId("56fe07bab95708fa18d46102"),
"username" : "efgh",
"devices" : {
"_id" : ObjectId("58c433da28841d00040d3cdb"),
"devicetype" : "web"
}
},
{
"_id" : ObjectId("56fe07bab95708fa18d46177"),
"username" : "efgh",
"devices" : {
"_id" : ObjectId("59d073d96974d20004a4bb9f"),
"devicetype" : "web"
}
},
{
"_id" : ObjectId("56fe07bab95708fa18d456c9"),
"username" : "ijkl",
"devices" : [
{
"_id" : ObjectId("59b93dd2e6673c00044cca49"),
"devicetype" : "ios"
"devicetoken" : "1abffaa4419d498b48d0bf982"
}
],
},
{
"_id" : ObjectId("56fe07bab95708fa18d456f4"),
"username" : "abcd",
"devices" : []
}
You can use $type operator like this
db.collection.find( { "devices" : { $type : "object" } } );
or
db.collection.find({ "devices": { $not: { $type: "array" } }})
Update:
Try one of below query as per your requirement (remove empty objects or keep only empty objects):
db.device.find( {$and:[ {devices:{ $type : "object" }},{devices:{$not: { $type: "array" }}}], devices:{$ne:{}}} );
db.device.find( {$and:[ {devices:{ $type : "object" }},{devices:{$not: { $type: "array" }}}], devices:{$eq:{}}} );
Check this screenshot:
Moreover, please note that you have duplicate keys (_id) in your data set which means those data sets are not inserted into your DB. So query will obviously won't give proper results.
Edit:
OP removed duplicate keys from data set.
You can use $type operator.
Find more detail on this link https://docs.mongodb.com/manual/reference/operator/query/type/
I want to sum counts values for each beacon. I'm using aggregate query but it returns with counts 0. Please let me know if there is mistake in query.
Sample Data
[ {
"_id" : ObjectId("5a8166392aa41ec66efc66bf"),
"userID" : "5a7c3410bdff0f0014181874",
"date" : ISODate("2018-02-08T11:04:54.000Z"),
"beacons" : [
{
"counts" : "2",
"UUID" : "red"
},
{
"counts" : "1",
"UUID" : "blue"
}
]
},
{
"_id" : ObjectId("5a8166392aa41ec66efc66c0"),
"userID" : "5a7c3410bdff0f0014181874",
"date" : ISODate("2018-02-08T11:04:54.000Z"),
"beacons" : [
{
"counts" : "2",
"UUID" : "red"
},
{
"counts" : "1",
"UUID" : "blue"
}
]
}
]
Query
/* Query */
db.getCollection('CountsDetail')
.aggregate([
{
"$unwind":"$beacons"
},
{
"$group": {
"_id":"$beacons.UUID", "counts":{ "$sum":"$counts"}
}
}]);
Response
/* Response */
{
"_id" : "red",
"counts" : 0
}
{
"_id" : "blue",
"counts" : 0
}
Response is returning 0 in sum, which is weird. Please correct what I am doing wrong. Thanks
Sorry miss read your OP. Your counts field is nested so use a dot notation:
"counts":{ "$sum":"$beacons.counts"}
I have several hundred thousands of documents in mongoDB to update.
here is an example of existing documents from collection Users:
{
"_id" : "549120bcf5115900124fb6e1",
"user" : "Tom",
"country" : "United Kingdom",
"province" : "North Yorkshire",
"city" : "York",
"organization" : ""
},
{
"_id" : "143184fbf5482260184ac6e2",
"user" : "Jack",
"country" : "Not Listed",
"province" : "",
"city" : "",
"organization" : "United Nations"
},
{
"_id" : "1234567890123456748979",
"user" : "Sarah",
"country" : "Not Listed",
"province" : "",
"city" : "",
"organization" : ""
},
{
"_id" : "98765432411654987654",
"user" : "Mat"
}
Each document has the possibility to have values in these fields :
a country, a province, and a city
or a country and a state
and here is the sample from another collection Countries:
{
"_id" : "123456789",
"key" : "Not Listed",
"uuid" : "ca55b53a-ef5b-43ed-90ed-b857f45ddb6d",
"organization" : [
{
"key" : "United Nations",
"uuid" : "1c4ae4c6-00c5-405d-98fa-ca7cc9edc72a"
},
{
"key" : "FIFA",
"uuid" : "11cfe606-821f-40fb-b1d0-bb7f9abb21dc"
}
],
"province" : [],
},
{
"_id" : "1123465498742",
"key" : "United Kingdom",
"uuid" : "d756e167-25ec-4aa9-b231-4dbf6d4bfce4",
"organization" : [],
"province" : [
{
"key" : "North Yorkshire",
"uuid" : "73d07c77-eba4-4dfa-9ada-e0ba8d8a2d55",
"city" : [
{
"key" : "York",
"uuid" : "80fd18a6-c4eb-4fb9-b591-6cca62319ba7"
},
{
"key" : "Middlesbrough",
"uuid" : "26a277c4-8640-4959-a64a-00f3727975f4"
}
],
},
{
"key" : "Oxfordshire",
"uuid" : "f7b5a570-df42-4520-ba3a-8bdcdd00e7d4",
"city" : [
{
"key" : "Oxford",
"uuid" : "b931865c-a363-4958-b7e7-5503fe674eb0"
},
{
"key" : "Banbury",
"uuid" : "b8d4c63a-75a9-4c3c-a4cd-d315f06a92e0"
}
],
}
]
}
The idea is to look up the country/organization/province/city field value from documents in Users collection and update them based on the uuid value of the Countries collection.
So the result will look like something like this:
{
"_id" : "549120bcf5115900124fb6e1",
"user" : "Tom",
"country" : "d756e167-25ec-4aa9-b231-4dbf6d4bfce4", // uuid of United Kingdom
"province" : "73d07c77-eba4-4dfa-9ada-e0ba8d8a2d55", // uuid of North Yorkshire
"city" : "80fd18a6-c4eb-4fb9-b591-6cca62319ba7", // uuid of York
"state" : ""
},
{
"_id" : "143184fbf5482260184ac6e2",
"user" : "Jack",
"country" : "ca55b53a-ef5b-43ed-90ed-b857f45ddb6d", // uuid of Not Listed
"province" : "",
"city" : "",
"state" : "1c4ae4c6-00c5-405d-98fa-ca7cc9edc72a" // uuid of United Nations
},
{
"_id" : "1234567890123456748979",
"user" : "Sarah",
"country" : "ca55b53a-ef5b-43ed-90ed-b857f45ddb6d", // uuid of Not Listed
"province" : "",
"city" : "",
"state" : ""
},
{
"_id" : "98765432411654987654",
"user" : "Mat"
}
The dependency of the fields are the following:
Country > Province > City
Or:
Country > Organization
It is possible that a parent field exists, but its child field doesn't exist or is empty.
How can I update these multidimensional arrays using mongo script rules?
Here is my attempt, but this is a lot of for loops, and not sure how to do the mongodb find/update/save part.. could somebody help to achieve it?
var usrCountry, uuidcountry, usrProvince, uuidprovince, usrOrg, uuidorg, usrCity, uuidcity;
for (var i = 0; i < users.length; i++) {
usrCountry = users[i].country;
usrProvince = users[i].province;
usrOrg = users[i].organization;
usrCity = users[i].city;
for (var j = 0; j < countries.length; j++) {
if (countries[j].key === usrCountry) {
uuidcountry = countries[j].uuid;
console.log('uuidcountry: ', uuidcountry)
if (countries[j].province.length){
for (var k = 0; k < countries[j].province.length; k++) {
if (countries[j].province[k].key === usrProvince){
uuidprovince = countries[j].province[k].uuid;
console.log('uuidprovince', uuidprovince)
for (var l = 0; l < countries[j].province[k].city.length; l++) {
if (countries[j].province[k].city[l].key === usrCity){
uuidcity = countries[j].province[k].city[l].uuid
console.log('uuidcity: ', uuidcity)
}
}
}
}
}
}
}
}
You can try do this with aggregation pipeline, and use that info to update
db.u.aggregate(
[
{
$lookup: {
from : "c",
localField : "country",
foreignField : "key",
as : "countryInfo"
}
},
{
$project: {
"_id" : 1,
"user" : 1,
"province" : 1,
"country" : 1,
"city" : 1,
"organization" : 1,
"country_uuid" : {$arrayElemAt : ["$countryInfo.uuid",0]},
"province_uuid" : { $arrayElemAt : [{ $map : { input : { $filter : { input : {$arrayElemAt : ["$countryInfo.province" ,0 ]} , as : "pro", cond : { $eq : [ "$$pro.key", "$province" ] } } } , as : "pr", in : "$$pr.uuid" } }, 0 ] },
"city_uuid" : {$arrayElemAt : [{$map : { input : { $arrayElemAt : [ {$filter : { input : { $map : { input : { $arrayElemAt : ["$countryInfo.province.city" ,0 ] }, as : "ct", in : { $filter : { input : "$$ct" , as : "ctyy", cond : { $eq : ["$$ctyy.key", "$city"] } } } } }, as : "o", cond : {$ne : [ {$size : "$$o"} , 0 ] } } } , 0]}, as : "o", in :"$$o.uuid"}}, 0]}
}
}
]
)
result
> db.u.aggregate( [ { $lookup: { from : "c", localField : "country", foreignField : "key", as : "countryInfo" } }, { $project: { "_id" : 1, "user" : 1, "province" : 1, "country" : 1, "city" : 1, "organization" : 1, "country_uuid" : {$arrayElemAt : ["$countryInfo.uuid",0]}, "province_uuid" : { $arrayElemAt : [{ $map : { input : { $filter : { input : {$arrayElemAt : ["$countryInfo.province" ,0 ]} , as : "pro", cond : { $eq : [ "$$pro.key", "$province" ] } } } , as : "pr", in : "$$pr.uuid" } }, 0 ] }, "city_uuid" : {$arrayElemAt : [{$map : { input : { $arrayElemAt : [ {$filter : { input : { $map : { input : { $arrayElemAt : ["$countryInfo.province.city" ,0 ] }, as : "ct", in : { $filter : { input : "$$ct" , as : "ctyy", cond : { $eq : ["$$ctyy.key", "$city"] } } } } }, as : "o", cond : {$ne : [ {$size : "$$o"} , 0 ] } } } , 0]}, as : "o", in :"$$o.uuid"}}, 0]} } } ] ).pretty()
{
"_id" : "549120bcf5115900124fb6e1",
"user" : "Tom",
"country" : "United Kingdom",
"province" : "North Yorkshire",
"city" : "York",
"organization" : "",
"country_uuid" : "d756e167-25ec-4aa9-b231-4dbf6d4bfce4",
"province_uuid" : "73d07c77-eba4-4dfa-9ada-e0ba8d8a2d55",
"city_uuid" : "80fd18a6-c4eb-4fb9-b591-6cca62319ba7"
}
I have a simple document, which has 3 location objects in an array.
Data:
{
"_id" : ObjectId("57c3c479a306b3613cf1ee5b"),
"location_history" : [
{
"location_name" : "Area 1",
"date" : 1472447609,
"_id" : ObjectId("57c3c479ac5a69612f0e0899"),
"location" : [
24.9532107, 67.1790576
]
},
{
"location_name" : "Area 2",
"date" : 1472448059,
"_id" : ObjectId("57c3c63bac5a69612f0e089c"),
"location" : [
24.9663937, 67.1462044
]
},
{
"location_name" : "Area 3",
"date" : 1472448987,
"_id" : ObjectId("57c3c9dbac5a69612f0e08a0"),
"location" : [
-24.987325, 115.1862298
]
}
}
Question: I need to fetch closest locations in this array.
Query I have tried:
db.getCollection('consumers_locations').aggregate([
{"$unwind": "$location_history"},
{"$match":{"_id":ObjectId("57c3c479a306b3613cf1ee5b")}},
{"$project" : { "abc" : "$location_history.location"} },
{ $geoNear: {
near: { type: "Point", coordinates: [ 24.942785, 67.157855 ] },
distanceField: "distance",
query : {"_id" : "_id"},
uniqueDocs: true,
includeLocs: "search_history.location",
maxDistance : 10000
}
}
])
But I get an error:
"ok" : 0,
"errmsg" : "$geoNear is only valid as the first stage in a pipeline.",
"code" : 2,
"codeName" : "BadValue"
Expected Output:
{
"_id" : ObjectId("57c3c479a306b3613cf1ee5b"),
"location_history" : [
{
"location_name" : "Area 1",
"date" : 1472447609,
"_id" : ObjectId("57c3c479ac5a69612f0e0899"),
"location" : [
24.9532107, 67.1790576
]
},
{
"location_name" : "Area 2",
"date" : 1472448059,
"_id" : ObjectId("57c3c63bac5a69612f0e089c"),
"location" : [
24.9663937, 67.1462044
]
}
}
It is not doable with your schema. Indexes are used to order documents in a collection, not sorting subdocuments within a document.
Consider to create a separate location_history collection with references to the parent document in consumers_locations. E.g. for your object, the collection may look like:
db.getCollection('location_history').insert([
{
"consumer_location": ObjectId("57c3c479a306b3613cf1ee5b"),
"location_name" : "Area 1",
"date" : 1472447609,
"_id" : ObjectId("57c3c479ac5a69612f0e0899"),
"location" : [
24.9532107, 67.1790576
]
},
{
"consumer_location": ObjectId("57c3c479a306b3613cf1ee5b"),
"location_name" : "Area 2",
"date" : 1472448059,
"_id" : ObjectId("57c3c63bac5a69612f0e089c"),
"location" : [
24.9663937, 67.1462044
]
},
{
"consumer_location": ObjectId("57c3c479a306b3613cf1ee5b"),
"location_name" : "Area 3",
"date" : 1472448987,
"_id" : ObjectId("57c3c9dbac5a69612f0e08a0"),
"location" : [
-24.987325, 115.1862298
]
}
]);
Regarding to the error, the docs read:
You can only use $geoNear as the first stage of a pipeline.
since only the first stage can benefit from indexes.