mongoose aggregate time diffrence - node.js

my collections look this
{
"_id": { "$oid": "61e7ed06dd937668b3afa22f" },
"time_duration": {
"count": 2,
"timeArr": [
{
"_id": { "$oid": "61e7edcfdd937668b3afa238" },
"start_time": { "$date": "2022-01-18T07:50:34.000Z" },
"end_time": { "$date": "2022-01-18T09:50:34.000Z" }
},
{
"_id": { "$oid": "61e7ee1faa77f37ceffcec4d" },
"start_time": { "$date": "2022-01-18T07:50:34.000Z" },
"end_time": { "$date": "2022-01-18T09:50:34.000Z" }
},
{
"_id": { "$oid": "61e7ee39aa77f37ceffcec5a" },
"start_time": { "$date": "2022-01-18T07:50:34.000Z" },
"end_time": { "$date": "2022-01-18T09:50:34.000Z" }
}
]
},
"parent_user_id": { "$oid": "61e6643548a14c31cee78ce6" },
"project_id": { "$oid": "61e67053174f50418f9a71b5" },
"name_activity": "",
"timer_status": "stopped",
"client_id": { "$oid": "6192363c027390b0e4d5b15c" },
"createdAt": { "$date": "2022-01-19T10:50:46.985Z" },
"updatedAt": { "$date": "2022-01-19T10:55:53.832Z" },
"__v": 0
}
i want to calculate time diffrence between start_time and end_time
i have tried this code so far
let ar = await ActivityRecord.aggregate([
{
$project: {
duration: {
$divide: [{ $subtract: ["$end_time", "$start_time"] }, 3600000],
},
},
},
]);

Related

How to set up aggregation pipeline for specific use case in MongoDB

`I have two collections in MongoDB. One is users and the other is companies. I need to be able to populate the users.endpoints with the endpoints from companies that match ObjectID's which are in the user.endPoints property. It is a bit hard for me to wrap my head around considering there are two steps.
This is the companies collection.
{
"_id": {
"$oid": "63ed39162bfc2cf8065b76cf"
{
"_id": {
"$oid": "63ed39162bfc2cf8065b76cf"
},
"companyName": "Sowegatel",
"amount": 0,
"signalwireSid": "id",
"numbers": [
{
"number": "+12068133580",
"_id": {
"$oid": "63ed39c72bfc2cf8065b76f0"
},
"createdAt": {
"$date": {
"$numberLong": "1676491207931"
}
},
"updatedAt": {
"$date": {
"$numberLong": "1676491207931"
}
}
}
],
"endPoints": [
{
"userName": "4009",
"_id": "fb1d0ef9-c713-400e-a3c9-cbc6823aaf57"
},
{
"userName": "4019",
"_id": "506e710d-14a6-4345-bc89-8488af4cabe4"
},
{
"userName": "4020",
"_id": "c80bd1ab-ca8d-4649-9d35-56d64ef8fab5",
"type": "sip_endpoint"
}
],
"__v": 6
} },
"companyName": "Sowegatel",
"amount": 0,
"signalwireSid": "id",
"numbers": [
{
"number": "+12068133580",
"_id": {
"$oid": "63ed39c72bfc2cf8065b76f0"
},
"createdAt": {
"$date": {
"$numberLong": "1676491207931"
}
},
"updatedAt": {
"$date": {
"$numberLong": "1676491207931"
}
}
}
],
"endPoints": [
{
"userName": "4009",
"_id": "fb1d0ef9-c713-400e-a3c9-cbc6823aaf57"
},
{
"userName": "4019",
"_id": "506e710d-14a6-4345-bc89-8488af4cabe4"
},
{
"userName": "4020",
"_id": "c80bd1ab-ca8d-4649-9d35-56d64ef8fab5",
"type": "sip_endpoint"
}
],
"__v": 6
}
This is the users collection.
{
"_id": {
"$oid": "63ed39162bfc2cf8065b76d2"
},
"firstName": "mark",
"lastName": "thomas",
"email": "mt#st.com",
"password": "",
"companyId": {
"$oid": "63ed39162bfc2cf8065b76cf"
},
"active": true,
"role": "companyAdmin",
"tokens": [],
"__v": 2,
"endpoints": [
// I need to populate to endpoints here!!!! //
"c80bd1ab-ca8d-4649-9d35-56d64ef8fab5"
]
}
I can do a single step aggregation, but this is a little complicated for me.`

How to only update one match of an array filter in mongodb

Problem:
I need to only update one document in the spots available array that has an id of "empty". My previous query was updating all matching sub documents with "empty" as the id; which is no good Example Below. So I decided to use aggregation so that I could add a limit stage so that I could only update one item, but come to find out I cannot update the original document with an aggregation. This leaves the only option to use an array filter that only updates one/first of its matches. Is this possible? I feel like there has to be a way to only update one match on an array filter and if there isn't this is definitely something that should be added.
My code:
This code updates every object with "empty"
const client = await clientPromise;
const db = client.db();
// const query = db.collection('events').aggregate(agg);
const query = await db.collection('events').updateOne({
_id: new ObjectId("6398c34ca67dbe3286452f23"),
createdBy: new ObjectId("636c1778f1d09191074f9690"),
"weights.weight": 12
},
{
$set: {
"weights.$.spotsAvailable.$[el2]": {
"name": "Wayne Wrestler",
"userId": new ObjectId("636c1778f1d09191074f9690")
}
}
},
{
arrayFilters: [{ "el2": { "userId": "empty" } }]
})
Example documents:
Event:
{
"_id": {
"$oid": "6398c34ca67dbe3286452f23"
},
"name": "test",
"createdBy": {
"$oid": "636c1778f1d09191074f9690"
},
"description": "testing",
"date": {
"$date": {
"$numberLong": "1645488000000"
}
},
"location": {
"type": "Point",
"coordinates": [
0,
0
]
},
"weights": [
{
"spotsAvailable": [
{
"name": "empty",
"userId": "empty"
},
{
"name": "empty",
"userId": "empty"
},
{
"name": "empty",
"userId": "empty"
}
],
"weight": 12
},
{
"spotsAvailable": [
{
// only one of these should've been updated, but both were
"name": "Wayne Wrestler",
"userId": {
"$oid": "636c1778f1d09191074f9690"
}
},
{
"name": "Wayne Wrestler",
"userId": {
"$oid": "636c1778f1d09191074f9690"
}
}
],
"weight": 15
}
],
"eventApplicants": [
{
"userId": {
"$oid": "636c1778f1d09191074f9690"
},
"name": "Wayne Wrestler",
"weight": 12
}
]
}
User:
{
"_id": {
"$oid": "636c1778f1d09191074f9690"
},
"name": "Wayne Wrestler",
"email": "wakywayne80#gmail.com",
"image": "https://lh3.googleusercontent.com/a/ALm5wu32gXjDIRxncjjQA9I4Yl-sjFH5EWsTlmvdM_0kiw=s96-c",
"emailVerified": {
"$date": {
"$numberLong": "1670864727212"
}
},
"createdEvents": [
{
"createdEventName": "test",
"createdEventDate": {
"$date": {
"$numberLong": "1645488000000"
}
},
"createdEventDescription": "testing",
"createdEventWeights": [
{
"weight": "12",
"filled": [
false,
false,
false
]
},
{
"weight": "15",
"filled": [
false,
false
]
}
],
"createdEventId": {
"$oid": "6398c34ca67dbe3286452f23"
}
}
],
"userSignedUpEvents": [],
"availableWeights": [
1,
123
],
"signedUpEvents": [
{
"eventId": {
"$oid": "636c722f67642c30dc5ffc30"
},
"eventName": "Utah",
"eventDate": {
"$date": {
"$numberLong": "1667913330000"
}
},
"accepted": false
},
{
"eventId": {
"$oid": "636c722f67642c30dc5ffc30"
},
"eventName": "Utah",
"eventDate": {
"$date": {
"$numberLong": "1667913330000"
}
},
"accepted": false
},
{
"eventId": {
"$oid": "637ec484ac2d675b30590b47"
},
"eventName": "Maybe?",
"eventDate": {
"$date": {
"$numberLong": "1672272000000"
}
},
"accepted": false
},
{
"eventId": {
"$oid": "636c722f67642c30dc5ffc30"
},
"eventName": "Utah",
"eventDate": {
"$date": {
"$numberLong": "1667913330000"
}
},
"accepted": false
},
{
"eventId": {
"$oid": "638d5274628db2a7bf61df49"
},
"eventName": "Eva's",
"eventDate": {
"$date": {
"$numberLong": "1698019200000"
}
},
"accepted": false
},
{
"eventId": {
"$oid": "636c722f67642c30dc5ffc30"
},
"eventName": "Utah",
"eventDate": {
"$date": {
"$numberLong": "1667913330000"
}
},
"accepted": false
},
{
"eventId": {
"$oid": "6398a922abb5c168ede595fb"
},
"eventName": "Nikko's event",
"eventDate": {
"$date": {
"$numberLong": "1670976000000"
}
},
"accepted": false
},
{
"eventId": {
"$oid": "6398a922abb5c168ede595fb"
},
"eventName": "Nikko's event",
"eventDate": {
"$date": {
"$numberLong": "1670976000000"
}
},
"accepted": false
},
{
"eventId": {
"$oid": "6398c34ca67dbe3286452f23"
},
"eventName": "test",
"eventDate": {
"$date": {
"$numberLong": "1645488000000"
}
},
"accepted": false
},
{
"eventId": {
"$oid": "6398c34ca67dbe3286452f23"
},
"eventName": "test",
"eventDate": {
"$date": {
"$numberLong": "1645488000000"
}
},
"accepted": false
},
{
"eventId": {
"$oid": "6398c34ca67dbe3286452f23"
},
"eventName": "test",
"eventDate": {
"$date": {
"$numberLong": "1645488000000"
}
},
"accepted": false
},
{
"eventId": {
"$oid": "6398c34ca67dbe3286452f23"
},
"eventName": "test",
"eventDate": {
"$date": {
"$numberLong": "1645488000000"
}
},
"accepted": false
}
]
}
I have tried:
Pluging in variables without the new ObjectId syntax
Plugin in variables with the new ObjectId syntax
Using the exact same hardcoded values that I got from copying the aggregation code from compass for the node driver
All of these either don't work or result in every subdocument with "empty" getting filled

One option is to use update with pipeline:
Since this is a double nested array, it is easier to do it in two steps - internal and external
First create the "external" item to replace in weights array and call it newItem. It is calculated using $reduce which allow us to manipulate the internal array while looping on it.
Replace the relevant item on weights array with our newItem using $map with $cond
db.collection.update(
{_id: ObjectId("6398c34ca67dbe3286452f23"), "weights.weight": 12},
[
{$set: {
newItem: {$reduce: {
input: {$getField: {
input: {$first: {
$filter: {
input: "$weights",
as: "item",
cond: {$eq: ["$$item.weight", 12]}
}
}},
field: "spotsAvailable"
}},
initialValue: [],
in: {$concatArrays: [
"$$value",
{$cond: [
{$and: [
{$eq: ["$$this.userId", "empty"]},
{$not: {$in: [ObjectId("636c1778f1d09191074f9690"), "$$value.userId"]}}
]},
[{
name: "Wayne Wrestler",
userId: ObjectId("636c1778f1d09191074f9690")
}],
["$$this"]
]}
]}
}}
}},
{$set: {
weights: {$map: {
input: "$weights",
in: {$cond: [
{$eq: ["$$this.weight", 12]},
{$mergeObjects: [
"$$this",
{spotsAvailable: "$newItem"}
]},
"$$this"
]}
}},
newItem: "$$REMOVE"
}}
])
See how it works on the playground example

You can first $unwind the weights for easier processing first. Use $reduce to iterate through the weights.spotsAvailable array and use a compound object to store the result and a flag to indicate whether it is updated or not. Finally use the result to $merge back to the original document.
db.collection.aggregate([
{
$match: {
"_id": ObjectId("6398c34ca67dbe3286452f23"),
createdBy: ObjectId("636c1778f1d09191074f9690"),
"weights.weight": 12,
"weights.spotsAvailable.userId": "empty"
}
},
{
"$unwind": "$weights"
},
{
"$addFields": {
"results": {
"$reduce": {
"input": "$weights.spotsAvailable",
"initialValue": {
result: [],
updated: false
},
"in": {
"$cond": {
"if": {
$and: [
{
$eq: [
false,
"$$value.updated"
]
},
{
$eq: [
"empty",
"$$this.userId"
]
}
]
},
"then": {
result: {
"$concatArrays": [
"$$value.result",
[
{
"name": "Wayne Wrestler",
"userId": ObjectId("636c1778f1d09191074f9690")
}
]
]
},
updated: true
},
"else": {
result: {
"$concatArrays": [
"$$value.result",
[
"$$this"
]
]
},
updated: "$$value.updated"
}
}
}
}
}
}
},
{
$set: {
"weights.spotsAvailable": "$results.result",
"results": "$$REMOVE"
}
},
{
$group: {
_id: "$_id",
"name": {
$first: "$name"
},
"createdBy": {
$first: "$createdBy"
},
"description": {
$first: "$description"
},
"date": {
$first: "$date"
},
"location": {
$first: "$location"
},
"weights": {
$push: "$weights"
},
"eventApplicants": {
$first: "$eventApplicants"
}
}
},
{
"$merge": {
"into": "collection",
"on": "_id"
}
}
])
Mongo Playground

Aggregation query

Node js using mongoose as ORM. I have set of documents like below
I want to calculate the average time for createdAt in ISO String(format) field in duration of hours on
grouping the category field. I have tried many ways to use aggregate but couldn't get the result.
[{
"_id": {
"$oid": "62dfc2cf25735e8b1b475ff1"
},
"numLikes": 0,
"numViews": 0,
"numShares": 0,
"hasUserLiked": false,
"title": "sample-broadcast",
"description": "broadcast-dewscription",
"projectId": {
"$oid": "62d903a5dade1714382b27af"
},
"content": [
{
"_id": {
"$oid": "62dfc2cf25735ee18d475ff2"
},
"downloadLink": "https://builder-broadcast-media.s3.ap-south-1.amazonaws.com/builder-broadcast-media/51daead4-1134-4921-a544-fea845f03d1c/uploadbroadcast/1658831544",
"label": "lance-anderson-QdAAasrZhdk-unsplash (1).jpg",
"contentType": "jpeg"
}
],
"delivery": "scheduleBroadcast",
"category": "GENERAL_UPDATES",
"groupId": "51daead4-1134-4921-a544-fea845f03d1c",
"author": {
"userId": "83314517-9326-430f-9c4e-8fedb050e6b0",
"profilePic": "https://builder-broadcast-media.s3.ap-south-1.amazonaws.com/builder-broadcast-media/4f670832-dfd7-43ee-a6ad-e2f43f48df6a/uploadprofilepic/1658239806",
"name": "Biswajit Rout"
},
"projectLogo": "https://builder-broadcast-media.s3.ap-south-1.amazonaws.com/builder-broadcast-media/4f670832-dfd7-43ee-a6ad-e2f43f48df6a/uploadcompanylogo%2A/1658239764",
"createdAt": {
"$date": {
"$numberLong": "1658831567577"
}
},
"updatedAt": {
"$date": {
"$numberLong": "1658831567577"
}
},
"__v": 0
},{
"_id": {
"$oid": "62dfebae25735e015f476dfb"
},
"numLikes": 0,
"numViews": 0,
"numShares": 0,
"hasUserLiked": false,
"title": "testing-broadcast",
"description": "testing-description",
"projectId": {
"$oid": "62d903a5dade1714382b27af"
},
"content": [
{
"_id": {
"$oid": "62dfebae25735e291c476dfc"
},
"downloadLink": "https://builder-broadcast-media.s3.ap-south-1.amazonaws.com/builder-broadcast-media/51daead4-1134-4921-a544-fea845f03d1c/projectimages0/1658842001",
"label": "lance-anderson-QdAAasrZhdk-unsplash (1).jpg",
"contentType": "jpeg"
},
{
"_id": {
"$oid": "62dfebae25735e0321476dfd"
},
"downloadLink": "https://builder-broadcast-media.s3.ap-south-1.amazonaws.com/builder-broadcast-media/51daead4-1134-4921-a544-fea845f03d1c/projectimages1/1658842024",
"label": "Get_Started_With_Smallpdf.pdf",
"contentType": "pdf"
}
],
"delivery": "immediate",
"link": "http://localhost:3000",
"category": "GENERAL_UPDATES",
"groupId": "51daead4-1134-4921-a544-fea845f03d1c",
"author": {
"userId": "83314517-9326-430f-9c4e-8fedb050e6b0",
"profilePic": "https://builder-broadcast-media.s3.ap-south-1.amazonaws.com/builder-broadcast-media/4f670832-dfd7-43ee-a6ad-e2f43f48df6a/uploadprofilepic/1658239806",
"name": "Biswajit Rout"
},
"projectLogo": "https://builder-broadcast-media.s3.ap-south-1.amazonaws.com/builder-broadcast-media/4f670832-dfd7-43ee-a6ad-e2f43f48df6a/uploadcompanylogo%2A/1658239764",
"createdAt": {
"$date": {
"$numberLong": "1658842030827"
}
},
"updatedAt": {
"$date": {
"$numberLong": "1658842030827"
}
},
"__v": 0
},{
"_id": {
"$oid": "62e144677fc76b0373f40152"
},
"numLikes": 0,
"numViews": 0,
"numShares": 0,
"hasUserLiked": false,
"title": "Broker Offer-1",
"description": "50% off on the membership for early birds. \n\nOffer Applied to first fifty users only",
"projectId": {
"$oid": "62d903a5dade1714382b27af"
},
"content": [
{
"_id": {
"$oid": "62e144677fc76b2b79f40153"
},
"downloadLink": "https://builder-broadcast-media.s3.ap-south-1.amazonaws.com/builder-broadcast-media/51daead4-1134-4921-a544-fea845f03d1c/projectimages0/1658930275",
"label": "50-off-PNG-Picture.png",
"contentType": "png"
}
],
"delivery": "immediate",
"link": "",
"category": "OFFER_BROKERS",
"groupId": "51daead4-1134-4921-a544-fea845f03d1c",
"author": {
"userId": "83314517-9326-430f-9c4e-8fedb050e6b0",
"profilePic": "https://builder-broadcast-media.s3.ap-south-1.amazonaws.com/builder-broadcast-media/4f670832-dfd7-43ee-a6ad-e2f43f48df6a/uploadprofilepic/1658239806",
"name": "Biswajit Rout"
},
"projectLogo": "https://builder-broadcast-media.s3.ap-south-1.amazonaws.com/builder-broadcast-media/4f670832-dfd7-43ee-a6ad-e2f43f48df6a/uploadcompanylogo%2A/1658239764",
"createdAt": {
"$date": {
"$numberLong": "1658930279871"
}
},
"updatedAt": {
"$date": {
"$numberLong": "1658930279871"
}
},
"__v": 0
}]
My expected result should be like this
{
OFFER_BROKERS: 5 <hrs>,
GENERAL_UPDATES : 4 <hrs>
}

Do you want to convert milliseconds to real time and give it to orm

Why don't store properly on nested object MongoDB

I need to update a document with an object, but my approach looks like don't apply the changes on DB, can someone explain me what I'm doing wrong, please?
let dishes = await this.dishesModel.find({});
let dishesPromise = dishes.map((dish, i) => {
dish.ingredients.forEach((item) => {
if (item?.item) {
if (item['item']['unit']['_id'].toString() === payload._id) {
item['item']['unit'] = unit;
}
}
});
return dish.save();
});
await Promise.all(dishesPromise)
In the above code I get unit previously and the objective is to use this unit in: item['item']['unit']
A dish document looks like:
{
"_id": { "$oid": "62cc00bfad995c0e7d8bbb7d" },
"name": "Bologne pasta",
"price": 6.99,
"ingredients": [
{
"quantity": 3,
"item": {
"_id": { "$oid": "62cbe92821464145f0eb280e" },
"name": "Cow beef",
"code": "meat-01",
"price": 9.99,
"value": 100,
"internal": true,
"categories": [
{
"_id": { "$oid": "62cbe83221464145f0eb27ea" },
"name": "Meat",
"disabled": false
}
],
"unit": {
"name": "GRAMASO 2",
"abbr": "gr.",
"_id": { "$oid": "62befe5ff6f95cf46a4cfe5b" }
},
"disabled": false,
"__v": 0,
"translation": { "es": { "name": "Carne de vaca" } }
}
},
{
"quantity": 2,
"item": {
"_id": { "$oid": "62cbea3121464145f0eb283a" },
"name": "Tomato",
"code": "vegetable-02",
"price": 1.5,
"value": 20,
"internal": true,
"categories": [
{
"_id": { "$oid": "62cbe82921464145f0eb27e6" },
"name": "Vegetables",
"disabled": false
}
],
"unit": {
"name": "GRAMASO 2",
"abbr": "gr.",
"_id": { "$oid": "62befe5ff6f95cf46a4cfe5b" }
},
"disabled": false,
"__v": 0,
"translation": { "es": { "name": "Tomate" } }
}
},
{
"quantity": 1,
"item": {
"_id": { "$oid": "62cbee5621464145f0eb2865" },
"name": "Spagetti",
"code": "pasta-01",
"price": 1.5,
"value": 100,
"internal": true,
"categories": [
{
"_id": { "$oid": "62cbee3e21464145f0eb285f" },
"name": "Pasta",
"disabled": false
}
],
"unit": {
"name": "GRAMASO 2",
"abbr": "gr.",
"_id": { "$oid": "62befe5ff6f95cf46a4cfe5b" }
},
"disabled": false,
"__v": 0,
"translation": { "es": { "name": "Espaguetti" } }
}
}
],
"categories": [
{
"_id": { "$oid": "62cbe84721464145f0eb27f6" },
"name": "Italian",
"disabled": false,
"translation": { "en": { "name": "Italiana" } }
}
],
"__v": 0,
"translation": { "es": { "name": "Pasta con salsa boloñesa" } }
}
At last, the changes are not reflecting on DB, but I don't figure out what's wrong.

how to fetch data group by day, week or month in mongodb?

I have a field "time" in my trade collection, it has thousand of entries from 2018 to 2021. I need to fetch data based on day, week and month.
Following query is working fine for minutes -
groupBy = {
"_id": {
"$subtract": [
{ "$subtract": [ "$time", new Date("1970-01-01") ] },
{ "$mod": [
{ "$subtract": [ "$time", new Date() ] },
1000 * 60 * 15 //15 minutes interval
]}
]
},
"count": { "$sum": 1 }
}
but when I am trying to do the same for 1 day or 1 week or a month, it is not working. I tried following query to get group by day -
groupBy = {
"year": {
"$year": "$time"
},
"month": {
"$month": "$time"
},
"day": {
"$dayOfMonth": "$time"
}
}
but it is returning only 2 records between 1 day interval. I want to fetch all records between 1 day interval.
Update - Here is my codes
try {
const pair = req.query.symbol;
const sDate = new Date(req.query.from*1000);
const eDate = new Date(req.query.to*1000);
let groupBy = {};
let whereCond = {
pairName: pair,
time: { $gte: sDate, $lte: eDate }
}
if(req.query.resolution == 1 ||
req.query.resolution == 3 ||
req.query.resolution == 5 ||
req.query.resolution == 15 ||
req.query.resolution == 30 ||
req.query.resolution == 60) {
groupBy = {
"_id": {
"$subtract": [
{ "$subtract": [ "$time", new Date("1970-01-01") ] },
{ "$mod": [
{ "$subtract": [ "$time", new Date() ] },
1000 * 60 * req.query.resolution
]}
]
},
"count": { "$sum": 1 }
}
} else if (req.query.resolution == 'D') {
groupBy = {
"year": {
"$year": "$time"
},
"month": {
"$month": "$time"
},
"day": {
"$dayOfMonth": "$time"
}
}
} else if (req.query.resolution == 'W') {
groupBy = {
"year": {
"$year": "$time"
},
"week": {
"$week": "$time"
}
}
} else if (req.query.resolution == 'M') {
groupBy = {
"year": {
"$year": "$time"
},
"month": {
"$month": "$time"
}
}
}
const project = { _id: 0, Date: "$Date", pair: { $literal: pair }, low: "$low", high: "$high", open: "$open", close: "$close", volume: "$volume", exchange: { $literal: "ABC" } };
tradeChartDB.aggregate([
{
$match: whereCond
},
{
"$group": {
"_id": groupBy,
count: {
"$sum": 1
},
Date: { $first: "$time" },
pairName: { $first: '$pairName' },
low: { $min: '$low' },
high: { $max: '$high' },
open: { $first: '$open' },
close: { $last: '$close' },
volume: { $sum: '$volume' }
}
},
{
$project: project,
},
{
$sort: {
"Date": -1,
}
}
]).exec(async function (err, result) {
//returning result from here
});
} catch (err) {
res.json(err);
}
Sample JSON -
[{
"_id": {
"$oid": "61b72505804d9a54a0074794"
},
"price": 0.070991,
"open": 0.070991,
"high": 0.076999,
"low": 0.069128,
"close": 0.074985,
"volume": 2242934.0216,
"total": 159228.1291274056,
"type": "sell",
"chartType": "Chart",
"pair": {
"$oid": "6161a094440a61740d591137"
},
"pairName": "ETH_BTC",
"time": {
"$date": "2021-10-30T00:00:00Z"
},
"__v": 0
},{
"_id": {
"$oid": "61b72505804d9a54a0074795"
},
"price": 0.068637,
"open": 0.068637,
"high": 0.07195,
"low": 0.059323,
"close": 0.070991,
"volume": 3135993.3945,
"total": 215245.17861829652,
"type": "sell",
"chartType": "Chart",
"pair": {
"$oid": "6161a094440a61740d591137"
},
"pairName": "ETH_BTC",
"time": {
"$date": "2021-09-30T00:00:00Z"
},
"__v": 0
},{
"_id": {
"$oid": "61b72505804d9a54a0074796"
},
"price": 0.06873,
"open": 0.06873,
"high": 0.07955,
"low": 0.066525,
"close": 0.068637,
"volume": 3610633.5753,
"total": 248158.845630369,
"type": "sell",
"chartType": "Chart",
"pair": {
"$oid": "6161a094440a61740d591137"
},
"pairName": "ETH_BTC",
"time": {
"$date": "2021-08-31T00:00:00Z"
},
"__v": 0
},{
"_id": {
"$oid": "61b72505804d9a54a0074797"
},
"price": 0.06104,
"open": 0.06104,
"high": 0.073242,
"low": 0.061035,
"close": 0.068734,
"volume": 3912567.58,
"total": 238823.1250832,
"type": "sell",
"chartType": "Chart",
"pair": {
"$oid": "6161a094440a61740d591137"
},
"pairName": "ETH_BTC",
"time": {
"$date": "2021-08-01T00:00:00Z"
},
"__v": 0
},{
"_id": {
"$oid": "61b72505804d9a54a0074798"
},
"price": 0.062875,
"open": 0.062875,
"high": 0.069138,
"low": 0.057031,
"close": 0.06104,
"volume": 3599095.838,
"total": 226293.15081425,
"type": "sell",
"chartType": "Chart",
"pair": {
"$oid": "6161a094440a61740d591137"
},
"pairName": "ETH_BTC",
"time": {
"$date": "2021-07-02T00:00:00Z"
},
"__v": 0
}]
Thanks!

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