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",
"$$value"
]
}
}
}
}
},
{
$group: {
_id: "$year",
RecentValue: { $sum: "$datum.Amount" }
}
}
])
You can first $unwind the datum array. Do the filtering and sort by the date. Then get the record with latest datum by a $group. Finally do another $group to calculate the sum.
Here is a mongo playground for your reference.
Related
[{
"_id" : ObjectId("5f3d0f13fd6fd6667f8f56d6"),
"name" : "A",
"prices" : [
{
"_id" : ObjectId("5f3d0f16fd6fd6667f8f57fb"),
"d" : ISODate("2019-08-19T00:00:00.000Z"),
"h" : 182.1,
},
{
"_id" : ObjectId("5f3d0f16fd6fd6667f8f57fc"),
"d" : ISODate("2019-08-20T00:00:00.000Z"),
"h" : 182.1,
},
{
"_id" : ObjectId("5f3d0f16fd6fd6667f81f57fc"),
"d" : ISODate("2019-08-21T00:00:00.000Z"),
"h" : 182.1,
}
]
}]
Input:
from: '2019-08-20'
to: '2019-08-21'
Exepected output
[{
"_id" : ObjectId("5f3d0f13fd6fd6667f8f56d6"),
"name" : "A",
"prices" : [
{
"_id" : ObjectId("5f3d0f16fd6fd6667f8f57fc"),
"d" : ISODate("2019-08-20T00:00:00.000Z"),
"h" : 182.1,
},
{
"_id" : ObjectId("5f3d0f16fd6fd6667f81f57fc"),
"d" : ISODate("2019-08-21T00:00:00.000Z"),
"h" : 182.1,
}
]
}]
So I want to filter prices array so it only returns items within the given date range based on variable d
So some form of aggregation.
mongoose.model("stock").aggregate(...)
Some combination of $unwind $filter, $gte, $gle
You can do as below
db.collection.aggregate([
{
$project: {
items: {
$filter: {
input: "$prices",
as: "price",
cond: {
"$and": [//only date conditions
{
$gte: [
"$$price.d",
new Date("2019-08-20")
]
},
{
$lte: [
"$$price.d",
new Date("2019-08-21")
]
}
]
}
}
}
}
}
])
play
I have json object as following.
{
"_id" : ObjectId("123209sfekjern"),
"Name" : "Test1",
"Orders" : [
{
"Date" : "2020-05-05",
"Total" : "100.00"
},
{
"Date" : "2020-05-10",
"Total" : "110.00"
},
{
"Date" : "2020-05-11",
"Total" : "100.00"
},
{
"Date" : "2020-05-14",
"Total" : "110.00"
},
{
"Date" : "2020-05-20",
"Total" : "100.00"
},
{
"Date" : "2020-05-15",
"Total" : "100.00"
},
{
"Date" : "2020-05-12",
"Total" : "110.00"
},
{
"Date" : "2020-05-18",
"Total" : "100.00"
},
{
"Date" : "2020-05-31",
"Total" : "110.00"
}
]
}
I need customername, orders.Date and Order.Total for all the orders which is greater than 100.00
I tried following query..
db.Customers.aggregate
(
[
{
$match: {
$and: [
{"Orders.Date":{$gte:"2020-05-15"}},//ISODate('2020-05-15 10:00:00.000Z')
{ "Orders.Total": { $gte: "100.00" } },
]
}
},
{ $project: { _id:0, Name: 1, "Orders.Total": 1, "Orders.Date": 1} },
]
)
The above query returns all the records. I m still beginner and learning mongodb.
any help would be appreciated.
thank you.
$match filters on a document level so entire document will be returned if at least one subdocument matches your conditions. In order to filter a nested array you need $filter:
db.Customers.aggregate([
{
$project: {
_id: 0,
Name: 1,
Orders: {
$filter: {
input: "$Orders",
cond: {
$and: [
{ $gte: [ "$$this.Date", "2020-05-15" ] },
{ $gte: [ "$$this.Total", "100.00" ] },
]
}
}
}
}
}
])
Mongo Playground
I have a bunch of docs that look like below:
{
"_id" : ObjectId("8f30b453c2ece001364dc04d"),
"SessionId" : "awkuTQjj53kgqAZ4J",
"StartDate" : ISODate("2020-02-24T11:51:36.918+0000"),
"EndDate" : ISODate("2020-02-24T11:51:36.918+0000"),
"List1" : "X",
"List2" : "Y",
"rating" : [
{
"ObjectId" : "5d09e98380c5d5eb89ac5069",
"List" : "List 2",
"Rate" : NumberInt(5),
"RatedDate" : ISODate("2020-02-24T11:55:47.774+0000")
},
{
"ObjectId" : "5d09e98380c5d5eb89ac5069",
"List" : "List 2",
"Rate" : NumberInt(4),
"RatedDate" : ISODate("2020-02-24T11:55:48.408+0000")
},
{
"ObjectId" : "5d09e98380c5d5eb89ac505b",
"List" : "List 2",
"Rate" : NumberInt(3),
"RatedDate" : ISODate("2020-02-24T11:55:49.520+0000")
},
{
"ObjectId" : "5d09e98380c5d5eb89ac505c",
"List" : "List 2",
"Rate" : NumberInt(3),
"RatedDate" : ISODate("2020-02-24T11:55:51.787+0000")
},
{
"ObjectId" : "5d09e98380c5d5eb89ac5057",
"List" : "List 1",
"Rate" : NumberInt(4),
"RatedDate" : ISODate("2020-02-24T11:55:53.865+0000")
},
{
"ObjectId" : "5d09e98380c5d5eb89ac5058",
"List" : "List 1",
"Rate" : NumberInt(4),
"RatedDate" : ISODate("2020-02-24T11:55:53.865+0000")
},
],
"Answers" : {
"SelectedList" : "1",
},
}
I need to sum up all the rating.Rate where rating.List:'List 1' and respectively sum up all rating.Rate where rating.List:'List 2', also exclude duplicate records (by rating.ObjectId) and count only the ones with latest rating.RatedDate. I suppose this is a group aggregation.
Also they should match the criteria
List1:'X' ,
Answers.selectedList:1
What I have written looks like below so far:
[
{
"$match" : {
"List1" : "X",
"Answers.SelectedList" : "1"
}
},
{
"$unwind" : {
"path" : "$rating"
}
},
{
"$group" : {
"_id" : null,
"sum" : {
"$sum" : "$Rate"
}
}
}
]
can you please help me?
I was a little confused around the List1/List2 however I think this will get you most of the way to your required aggregation query.
db.test.aggregate([
{
$match: {
"List1": "X",
"Answers.SelectedList": "1"
}
},
{
"$unwind" : "$rating"
},
{
$group:{
_id: {
id: "$rating.ObjectId",
list: "$rating.List"
},
maxRatedDate: { $max: "$rating.RatedDate" },
ratings: { $push: "$rating" }
}
},{
$addFields: {
ratings: {
$filter: {
input: "$ratings",
as: "item",
cond: { $eq: [ "$$item.RatedDate", "$maxRatedDate" ] }
}
}
}
},
{
$unwind: "$ratings"
},
{
$group:{
_id: "$ratings.List",
sum : {
$sum : "$ratings.Rate"
}
}
}
])
This will output the following
{ "_id" : "List 1", "sum" : 8 }
{ "_id" : "List 2", "sum" : 10 }
However, let's try to break it down.
To start with we've got a simple match, the same as yours in your question. this just limits the number of documents we pass back
$match: {
"List1": "X",
"Answers.SelectedList": "1"
}
Then we unwind all the array items so we get a document for each rating, this allows us to do some extra querying on the data.
{
"$unwind" : "$rating"
}
Next, we've got a group by, here we're a group on the ObjectId of the rating so we can later remove duplicates, we're also finding out in the group which rating we've group has the highest date so we can take that one later in a projection. we're then pushing all the rating back in the array for later.
$group:{
_id: {
id: "$rating.ObjectId",
list: "$rating.List"
},
maxRatedDate: { $max: "$rating.RatedDate" },
ratings: { $push: "$rating" }
}
Next we want to project the ratings array in to a single element in which it only contains the latest rating, for this we use a $filter on the array and filter them all out that don't match our max date we calculated in our previous step.
$addFields: {
ratings: {
$filter: {
input: "$ratings",
as: "item",
cond: { $eq: [ "$$item.RatedDate", "$maxRatedDate" ] }
}
}
}
The next two steps are fairly simple and are just unwinding the array again (we've only got one element, then grouping them to get the total sum for the lists.
{
$unwind: "$ratings"
},
{
$group:{
_id: "$ratings.List",
sum : {
$sum : "$ratings.Rate"
}
}
}
At this point you only need to provide the $group stage with the field that you're actually grouping on as the _id field and reference the fields properly as they are still inside of the rating array:
"$group" : {
"_id" : "$rating.List",
"sum" : {
"$sum" : "$rating.Rate"
}
}
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: [ "$$this.count", "$total" ] }, 100 ] } } }, '%' ] }
}
}
}
}
},
{
$unwind: "$docs"
},
{
$replaceRoot: { newRoot: "$docs" }
}
])
Mongo Playground
I have a customers collection such as;
{
"_id" : ObjectId("5de8c07dc035532b489b2e23"),
"name" : "sam",
"orders" : [{"ordername" : "cola"},{"ordername" : "cheesecake"}]
}
And waiters collection such as;
{
"_id" : ObjectId("5de8bc24c035532b489b2e20"),
"waiter" : "jack",
"products" : [{"name" : "cola", "price" : "4"},
{"name" : "water", "price" : "2"},
{"name" : "coffee", "price" : "8" }]
}
{
"_id" : ObjectId("5de8bdc7c035532b489b2e21"),
"waiter" : "susan",
"products" : [{"name" : "cheesecake", "price" : "12" },
{"name" : "apple pie", "price" : "14" }]
}
I want to join the objects from waiters collection into the customers collection by matching "products.name" and "orders.ordername". But, the result includes the whole document from the waiters collection, however, I want only the matched objects inside the document. Here is what I want;
ordered:[
{"name" : "cola", "price" : "4"},
{"name" : "cheesecake", "price" : "12" },
]
I tried $lookup with and without pipeline, and filter but could not get this result. Thanks in advance.
You had the right idea, we just have to "massage" the data a bit due to its structure like so:
db.collection.aggregate([
{
$addFields: {
"orderNames":
{
$reduce: {
input: "$orders",
initialValue: [],
in: {$concatArrays: [["$$this.ordername"], "$$value"]}
}
}
}
},
{
$lookup:
{
from: "waiters",
let: {orders: "$orderNames"},
pipeline: [
{
$unwind: "$products"
},
{
$match:
{
$expr:{$in: ["$products.name", "$$orders"]},
}
},
{
$group: {
_id: "$products.name",
price: {$first: "$products.price"}
}
},
{
$project: {
_id: 0,
price: 1,
name: "$_id"
}
}
],
as: "ordered"
}
}
])
It feels like you could benefit from a new collection of mapping items to prices. Could potentially save you a lot of time.