I have json object as following.
{
"_id" : ObjectId("123209sfekjern"),
"Name" : "Test1",
"Orders" : [
{
"Date" : "2020-05-05",
"Total" : "100.00"
},
{
"Date" : "2020-05-10",
"Total" : "110.00"
},
{
"Date" : "2020-05-11",
"Total" : "100.00"
},
{
"Date" : "2020-05-14",
"Total" : "110.00"
},
{
"Date" : "2020-05-20",
"Total" : "100.00"
},
{
"Date" : "2020-05-15",
"Total" : "100.00"
},
{
"Date" : "2020-05-12",
"Total" : "110.00"
},
{
"Date" : "2020-05-18",
"Total" : "100.00"
},
{
"Date" : "2020-05-31",
"Total" : "110.00"
}
]
}
I need customername, orders.Date and Order.Total for all the orders which is greater than 100.00
I tried following query..
db.Customers.aggregate
(
[
{
$match: {
$and: [
{"Orders.Date":{$gte:"2020-05-15"}},//ISODate('2020-05-15 10:00:00.000Z')
{ "Orders.Total": { $gte: "100.00" } },
]
}
},
{ $project: { _id:0, Name: 1, "Orders.Total": 1, "Orders.Date": 1} },
]
)
The above query returns all the records. I m still beginner and learning mongodb.
any help would be appreciated.
thank you.
$match filters on a document level so entire document will be returned if at least one subdocument matches your conditions. In order to filter a nested array you need $filter:
db.Customers.aggregate([
{
$project: {
_id: 0,
Name: 1,
Orders: {
$filter: {
input: "$Orders",
cond: {
$and: [
{ $gte: [ "$$this.Date", "2020-05-15" ] },
{ $gte: [ "$$this.Total", "100.00" ] },
]
}
}
}
}
}
])
Mongo Playground
Related
I want to group by and count follow_user.tags.tag_id per record, so no matter how many times the same tag_id show up on the same record, it only counts as 1.
My database structure looks like this:
{
"external_userid" : "EXID1",
"follow_user" : [
{
"userid" : "USERID1",
"tags" : [
{
"tag_id" : "TAG1"
}
]
},
{
"userid" : "USERID2",
"tags" : [
{
"tag_id" : "TAG1"
},
{
"tag_id" : "TAG2"
}
]
}
]
},
{
"external_userid" : "EXID2",
"follow_user" : [
{
"userid" : "USERID1",
"tags" : [
{
"tag_id" : "TAG2"
}
]
}
]
}
Here's my query:
[
{ "$unwind": "$follow_user" }, { "$unwind": "$follow_user.tags" },
{ "$group" : { "_id" : { "follow_user᎐tags᎐tag_id" : "$follow_user.tags.tag_id" }, "COUNT(_id)" : { "$sum" : 1 } } },
{ "$project" : { "total" : "$COUNT(_id)", "tagId" : "$_id.follow_user᎐tags᎐tag_id", "_id" : 0 } }
]
What I expected:
{
"total" : 1,
"tagId" : "TAG1"
},
{
"total" : 2,
"tagId" : "TAG2"
}
What I get:
{
"total" : 2,
"tagId" : "TAG1"
},
{
"total" : 2,
"tagId" : "TAG2"
}
$set - Create a new field follow_user_tags.
1.1. $setUnion - To distinct the value from the Result 1.1.1.
1.1.1. $reduce - Add the value of follow_user.tags.tag_id into array.
$unwind - Deconstruct follow_user_tags array field to multiple documents.
$group - Group by follow_user_tags and perform total count via $sum.
$project - Decorate output document.
db.collection.aggregate([
{
$set: {
follow_user_tags: {
$setUnion: {
"$reduce": {
"input": "$follow_user.tags",
"initialValue": [],
"in": {
"$concatArrays": [
"$$value",
"$$this.tag_id"
]
}
}
}
}
}
},
{
$unwind: "$follow_user_tags"
},
{
$group: {
_id: "$follow_user_tags",
total: {
$sum: 1
}
}
},
{
$project: {
_id: 0,
tagId: "$_id",
total: 1
}
}
])
Sample Mongo Playground
Below is the document which has an array name datum and I want to filter the records based on StatusCode, group by Year and sum the amount value from the recent record of distinct Types.
{
"_id" : ObjectId("5fce46ca6ac9808276dfeb8c"),
"year" : 2018,
"datum" : [
{
"StatusCode" : "A",
"Type" : "1",
"Amount" : NumberDecimal("100"),
"Date" : ISODate("2018-05-30T00:46:12.784Z")
},
{
"StatusCode" : "A",
"Type" : "1",
"Amount" : NumberDecimal("300"),
"Date" : ISODate("2023-05-30T00:46:12.784Z")
},
{
"StatusCode" : "A",
"Type" : "2",
"Amount" : NumberDecimal("420"),
"Date" : ISODate("2032-05-30T00:46:12.784Z")
},
{
"StatusCode" : "B",
"Type" : "2",
"Amount" : NumberDecimal("420"),
"Date" : ISODate("2032-05-30T00:46:12.784Z")
}
]
}
In my case following is the expected result :
{
Total : 720
}
I want to achieve the result in the following aggregate Query pattern
db.collection.aggregate([
{
$addFields: {
datum: {
$reduce: {
input: "$datum",
initialValue: {},
"in": {
$cond: [
{
$and: [
{ $in: ["$$this.StatusCode", ["A"]] }
]
},
"$$this",
"$$value"
]
}
}
}
}
},
{
$group: {
_id: "$year",
RecentValue: { $sum: "$datum.Amount" }
}
}
])
You can first $unwind the datum array. Do the filtering and sort by the date. Then get the record with latest datum by a $group. Finally do another $group to calculate the sum.
Here is a mongo playground for your reference.
I am new in mongodb ,Please help me out
I have more than 500 students details like this..
{
"_id" : 7,
"name" : "Salena Olmos",
"scores" : [
{
"score" : 90.37826509157176,
"type" : "exam"
},
{
"score" : 42.48780666956811,
"type" : "quiz"
},
{
"score" : 96.52986171633331,
"type" : "homework"
}
]
},
/* 2 */
{
"_id" : 8,
"name" : "Daphne Zheng",
"scores" : [
{
"score" : 22.13583712862635,
"type" : "exam"
},
{
"score" : 14.63969941335069,
"type" : "quiz"
},
{
"score" : 75.94123677556644,
"type" : "homework"
}
]
}
Need to find one student details who got highest marks in "type" exam
Output as follows...
{
"_id" : 7,
"name" : "Salena Olmos",
"scores" : [
{
"score" : 90.37826509157176,
"type" : "exam"
},
{
"score" : 42.48780666956811,
"type" : "quiz"
},
{
"score" : 96.52986171633331,
"type" : "homework"
}
]
}
I need one student details from whole collection. The problem I am facing that need to search in embedded array "score" as well as "type".
Someone please help me
Try this
db.collection.aggregate([
{
$group: {
_id: "$_id",
scores: {
$first: "$scores"
},
data: {
$push: "$$ROOT"
}
}
},
{
$unwind: "$data"
},
{
$match: {
"data.scores.type": "exam"
}
},
{
$sort: {
"data.scores.score": -1
}
},
{
$project: {
_id: 1,
name: "$data.name",
scores: "$scores"
}
},
{
$limit: 1
}
])
Sample Playground
While this doesn't answer the question, it is related. This one filters out all the subdocuments which match the conditions "greater or equal 90" and type "exam"
db.collection.aggregate([
{
$match: {
"scores.score": {
$gte: 90
},
"scores.type": "exam"
}
},
{
$project: {
name: true,
list: {
$filter: {
input: "$scores",
as: "list",
cond: {
$and: [
{
$gt: [
"$$list.score",
90
]
},
{
$eq: [
"$$list.type",
"exam"
]
}
]
}
}
}
}
}
])
which returns
[
{
"_id": 7,
"list": [
{
"score": 90.37826509157176,
"type": "exam"
}
],
"name": "Salena Olmos"
}
]
https://mongoplayground.net/p/hYnVzZbuNFI
If you want the entire document, then add doc: "$$ROOT", to the projection.
How to get percentage total of data with group by date in MongoDB ?
Link example : https://mongoplayground.net/p/aNND4EPQhcb
I have some collection structure like this
{
"_id" : ObjectId("5ccbb96706d1d47a4b2ced4b"),
"date" : "2019-05-03T10:39:53.108Z",
"id" : 166,
"update_at" : "2019-05-03T10:45:36.208Z",
"type" : "image"
}
{
"_id" : ObjectId("5ccbb96706d1d47a4b2ced4c"),
"date" : "2019-05-03T10:39:53.133Z",
"id" : 166,
"update_at" : "2019-05-03T10:45:36.208Z",
"type" : "image"
}
{
"_id" : ObjectId("5ccbb96706d1d47a4b2ced4d"),
"date" : "2019-05-03T10:39:53.180Z",
"id" : 166,
"update_at" : "2019-05-03T10:45:36.208Z",
"type" : "image"
}
{
"_id" : ObjectId("5ccbb96706d1d47a4b2ced4e"),
"date" : "2019-05-03T10:39:53.218Z",
"id" : 166,
"update_at" : "2019-05-03T10:45:36.208Z",
"type" : "image"
}
And I have query in mongodb to get data of collection, how to get percentage of total data. in bellow example query to get data :
db.name_collection.aggregate(
[
{ "$match": {
"update_at": { "$gte": "2019-11-04T00:00:00.0Z", "$lt": "2019-11-06T00:00:00.0Z"},
"id": { "$in": [166] }
} },
{
"$group" : {
"_id": {
$substr: [ '$update_at', 0, 10 ]
},
"count" : {
"$sum" : 1
}
}
},
{
"$project" : {
"_id" : 0,
"date" : "$_id",
"count" : "$count"
}
},
{
"$sort" : {
"date" : 1
}
}
]
)
and this response :
{
"date" : "2019-11-04",
"count" : 39
},
{
"date" : "2019-11-05",
"count" : 135
}
how to get percentage data total from key count ? example response to this :
{
"date" : "2019-11-04",
"count" : 39,
"percentage" : "22%"
},
{
"date" : "2019-11-05",
"count" : 135,
"percentage" : "78%"
}
You have to group by null to get total count and then use $map to calculate the percentage. $round will be a useful operator in such case. Finally you can $unwind and $replaceRoot to get back the same number of documents:
db.collection.aggregate([
// previous aggregation steps
{
$group: {
_id: null,
total: { $sum: "$count" },
docs: { $push: "$$ROOT" }
}
},
{
$project: {
docs: {
$map: {
input: "$docs",
in: {
date: "$$this.date",
count: "$$this.count",
percentage: { $concat: [ { $toString: { $round: { $multiply: [ { $divide: [ "$$this.count", "$total" ] }, 100 ] } } }, '%' ] }
}
}
}
}
},
{
$unwind: "$docs"
},
{
$replaceRoot: { newRoot: "$docs" }
}
])
Mongo Playground
Pretty new to mongo and haven't been able to figure out how to perform a query.
I have an accounts collection that looks like this:
{
"_id" : ObjectId("1"),
"time" : ISODate("2018-10-20T05:57:15.372Z"),
"profileId" : "1",
"totalUSD" : "1015.5513030613",
"accounts" : [
{
"_id" : ObjectId("2"),
"accountId" : "1",
"currency" : "USD",
"balance" : "530.7934159683763000",
"available" : "530.7934159683763",
"hold" : "0.0000000000000000",
"exchangeRateUSD" : "1"
},
{
"_id" : ObjectId("5"),
"accountId" : "4",
"currency" : "BTC",
"balance" : "0.0759214200000000",
"available" : "0.07592142",
"hold" : "0.0000000000000000",
"exchangeRateUSD" : "6384.995"
},
],
}
I store only exchangeRateUSD for each currency, and not exchangeRateXXX where XXX is currency name, because there can be an arbitrary number of currencies and currency pairs. But when I query the accounts collection it will always be queried by a currency pair, eg: BTC-USD. Keeping it simple for now, I can assume the currency pair will always be XXX-USD.
When I query the accounts collection I'd like to add a 'virtual' field to each account object: exchangeRateCrypto and then on the top-level accounts document I'd like to add totalCrypto which would just be the total account value in the given crypto. Eg: USD account balance * exchangeRateCrypto + crypto account balance * exchangeRateCrypto (which would equal 1).
My current query without the exchangeRateCrypto and totalCrypto looks like:
db.accounts.aggregate([
{ $unwind: '$accounts' },
{ $match: { 'accounts.currency': { $in: [ 'USD', 'BTC' ] }}},
{
$group: {
_id: '$_id',
time: { $first: '$time' },
profileId: { $first: '$profileId' },
accounts: { $push: '$accounts' },
totalUSD: { $sum: { $multiply: [ { $toDouble: '$accounts.balance' }, { $toDouble: '$accounts.exchangeRateUSD' } ] } }
}
}
]);
I'm trying to figure out how to 'reach' into the BTC row and calculate the exchangeRateCrypto by simply doing 1 / exchangeRateUSD and then projecting/returning the accounts document and subdocument as:
{
"_id" : ObjectId("1"),
"time" : ISODate("2018-10-20T05:57:15.372Z"),
"profileId" : "1",
"totalUSD" : "1015.5513030613",
"totalCrypto" : "0.1590527953", // 530.7934159683763 * 0.0001566171939 + 0.07592142 * 1
"accounts" : [
{
"_id" : ObjectId("2"),
"accountId" : "1",
"currency" : "USD",
"balance" : "530.7934159683763000",
"available" : "530.7934159683763",
"hold" : "0.0000000000000000",
"exchangeRateUSD" : "1",
"exchangeRateCrypto" : "0.0001566171939", // 1 / 6384.995
},
{
"_id" : ObjectId("5"),
"accountId" : "4",
"currency" : "BTC",
"balance" : "0.0759214200000000",
"available" : "0.07592142",
"hold" : "0.0000000000000000",
"exchangeRateUSD" : "6384.995",
"exchangeRateCrypto" : "1"
},
],
}
but haven't been able to figure out a good way of doing this.
It seems it should be pretty straightforward, but still learning Mongo.
Any tips?
Thanks!
The solution might be a bit long and probably it can be shortened however I want you to understand proposed way of thinking step by step.
var secondCurrency = "BTC";
var secondCurrencyFieldName = "exchangeRate" + secondCurrency;
var secondCurrencyFieldNameRef = "$" + secondCurrencyFieldName;
var totalFieldName = "total" + secondCurrency;
db.accounts.aggregate([
{ $unwind: "$accounts" },
{ $match: { "accounts.currency": { $in: [ "USD", secondCurrency ] }}},
{
$group: {
_id: "$_id",
time: { $first: "$time" },
profileId: { $first: "$profileId" },
accounts: { $push: "$accounts" },
totalUSD: { $sum: { $multiply: [ { $toDouble: "$accounts.balance" }, { $toDouble: "$accounts.exchangeRateUSD" } ] } }
}
},
{
$addFields: {
[secondCurrencyFieldName]: {
$filter: {
input: "$accounts",
as: "account",
cond: { $eq: [ "$$account.currency", secondCurrency ] }
}
}
}
},
{
$addFields: {
[secondCurrencyFieldName]: {
$let: {
vars: { first: { $arrayElemAt: [ secondCurrencyFieldNameRef, 0 ] } },
in: { $toDouble: "$$first.exchangeRateUSD" }
}
}
}
},
{
$addFields: {
accounts: {
$map: {
input: "$accounts",
as: "account",
in: {
$mergeObjects: [
"$$account",
{
[secondCurrencyFieldName]: {
$cond: [ { $eq: [ "$$account.currency", secondCurrency ] }, 1, { $divide: [ 1, secondCurrencyFieldNameRef ] } ]
}
}
]
}
}
}
}
},
{
$addFields: {
[totalFieldName]: {
$reduce: {
input: "$accounts",
initialValue: 0,
in: {
$add: [
"$$value",
{ $multiply: [ { $toDouble: "$$this.balance" }, "$$this." + secondCurrencyFieldName ] }
]
}
}
}
}
}
]).pretty()
So we can start with $addFields which can either add new field to existing document or repace existing field. After the $group stage you have to find the USD-XXX exchange rate (using $filter and $let + $arrayElemAt in the next pipeline stage). Having this value you can use $addFields again combined with $map and $mergeObjects to add new field to nested array and that field will represent the ratio between USD and XXX currency. Then you can use $addFields again with $reduce to get the total of all accounts for XXX currency.
Output:
{
"_id" : ObjectId("5beeec9fef99bb86541abf7f"),
"time" : ISODate("2018-10-20T05:57:15.372Z"),
"profileId" : "1",
"accounts" : [
{
"_id" : ObjectId("5beeec9fef99bb86541abf7d"),
"accountId" : "1",
"currency" : "USD",
"balance" : "530.7934159683763000",
"available" : "530.7934159683763",
"hold" : "0.0000000000000000",
"exchangeRateUSD" : "1",
"exchangeRateBTC" : 0.00015661719390539853
},
{
"_id" : ObjectId("5beeec9fef99bb86541abf7e"),
"accountId" : "4",
"currency" : "BTC",
"balance" : "0.0759214200000000",
"available" : "0.07592142",
"hold" : "0.0000000000000000",
"exchangeRateUSD" : "6384.995",
"exchangeRateBTC" : 1
}
],
"totalUSD" : 1015.5513030612763,
"exchangeRateBTC" : 6384.995,
"totalexchangeRateBTC" : 0.15905279535242806
}