I am watching a tutorial I can understand how this aggregate works, What is the use of pings, $$ROOT in it.
client = pymongo.MongoClient(MY_URL)
pings = client['mflix']['watching_pings']
cursor = pings.aggregate([
{
"$sample": { "size": 50000 }
},
{
"$addFields": {
"dayOfWeek": { "$dayOfWeek": "$ts" },
"hourOfDay": { "$hour": "$ts" }
}
},
{
"$group": { "_id": "$dayOfWeek", "pings": { "$push": "$$ROOT" } }
},
{
"$sort": { "_id": 1 }
}
]);
Let's assume that our collection looks like below:
{
"_id" : ObjectId("b9"),
"key" : 1,
"value" : 20,
"history" : ISODate("2020-05-16T00:00:00Z")
},
{
"_id" : ObjectId("ba"),
"key" : 1,
"value" : 10,
"history" : ISODate("2020-05-13T00:00:00Z")
},
{
"_id" : ObjectId("bb"),
"key" : 3,
"value" : 50,
"history" : ISODate("2020-05-12T00:00:00Z")
},
{
"_id" : ObjectId("bc"),
"key" : 2,
"value" : 0,
"history" : ISODate("2020-05-13T00:00:00Z")
},
{
"_id" : ObjectId("bd"),
"key" : 2,
"value" : 10,
"history" : ISODate("2020-05-16T00:00:00Z")
}
Now based on the history field you want to group and insert the whole documents in to an array field 'items'. Here $$ROOT variable will be helpful.
So, the aggregation query to achieve the above will be:
db.collection.aggregate([{
$group: {
_id: '$history',
items: {$push: '$$ROOT'}
}
}])
It will result in following output:
{
"_id" : ISODate("2020-05-12T00:00:00Z"),
"items" : [
{
"_id" : ObjectId("bb"),
"key" : 3,
"value" : 50,
"history" : ISODate("2020-05-12T00:00:00Z")
}
]
},
{
"_id" : ISODate("2020-05-13T00:00:00Z"),
"items" : [
{
"_id" : ObjectId("ba"),
"key" : 1,
"value" : 10,
"history" : ISODate("2020-05-13T00:00:00Z")
},
{
"_id" : ObjectId("bc"),
"key" : 2,
"value" : 0,
"history" : ISODate("2020-05-13T00:00:00Z")
}
]
},
{
"_id" : ISODate("2020-05-16T00:00:00Z"),
"items" : [
{
"_id" : ObjectId("b9"),
"key" : 1,
"value" : 20,
"history" : ISODate("2020-05-16T00:00:00Z")
},
{
"_id" : ObjectId("bd"),
"key" : 2,
"value" : 10,
"history" : ISODate("2020-05-16T00:00:00Z")
}
]
}
I hope it helps.
Related
Need help to sort these documents:
const docs = Docs.find(
{
'publishedOn.profileId': groupProfile._id,
},
{ sort: { ??? }}
);
I need to find documents which has defined 'publishedOn.profileId' and
sort by 'awards.type' = 'challengeWinner' and by its 'awards.score'
Not all document has awards.type = 'challengeWinner'. I need to
take on the top 'awards.score' = 1, then 2, then 3 and then the rest by 'writtenDate'.
I have no idea how to fix it. Is it possible?
[
{
"_id" : "5FW9EDW8gi3M8R7XK",
"createdAt" : ISODate("2021-06-13T00:11:48.638Z"),
"title" : "My solution",
"writtenDateType" : 4,
"writtenDate" : ISODate("2021-06-13T00:00:00.000Z"),
"userId" : "dC35hwe6XMRhvqWBv",
"publishedOn" : [
{
"profileId" : "36oPw2zxYCpKxfiu2",
"publishedDate" : ISODate("2021-06-13T00:11:48.787Z"),
"userId" : "dC35hwe6XMRhvqWBv"
},
{
"profileId" : "9y2RwJpzzyk29ApiC",
"userId" : "dC35hwe6XMRhvqWBv",
"publishedDate" : ISODate("2021-06-13T00:16:01.529Z")
}
],
"awards" : [
{
"type" : "topPoem",
"score" : 5,
"addedAt" : ISODate("2021-06-24T23:04:10.454Z"),
"updatedAt" : ISODate("2021-06-25T23:30:00.069Z")
},
{
"type" : "challengeWinner",
"score" : 2,
"challengeId" : "9y2RwJpzzyk29ApiC",
"addedAt" : ISODate("2021-06-24T23:04:10.454Z"),
"updatedAt" : ISODate("2021-06-25T23:30:00.069Z")
}
]
},
{
"_id" : "upzvo8BeHyQ9r9Yfv",
"createdAt" : ISODate("2021-06-19T15:35:13.716Z"),
"title" : "Briches",
"writtenDateType" : 2,
"writtenDate" : ISODate("2003-01-01T00:00:00.000Z"),
"userId" : "A32228XMuZqxFe4Kz",
"publishedOn" : [
{
"profileId" : "MLGkCtNyZ64bGKedG",
"publishedDate" : ISODate("2021-06-19T15:35:13.861Z"),
"userId" : "A32228XMuZqxFe4Kz"
},
{
"profileId" : "9y2RwJpzzyk29ApiC",
"userId" : "A32228XMuZqxFe4Kz",
"publishedDate" : ISODate("2021-06-19T15:35:36.280Z")
}
],
"awards" : [
{
"type" : "challengeWinner",
"score" : 1,
"challengeId" : "9y2RwJpzzyk29ApiC",
"addedAt" : ISODate("2021-06-24T22:59:00.948Z"),
"updatedAt" : ISODate("2021-06-25T23:30:00.067Z"),
"claps" : 19,
"clapsUsers" : 4
},
{
"type" : "suggestedHomepage",
"score" : 1,
"addedAt" : ISODate("2021-06-24T22:59:59.981Z"),
"updatedAt" : ISODate("2021-06-24T22:59:59.981Z")
}
]
}
]
I just learned and tried to solve your problem. I used aggregate to do the filter in your data.
First I selected all the items which $match the `publishedOn.profileId".
Then, I $project(ed) the items that are needed. In this case, I took the writtenDate and the matching awards.
In order to choose the needed value from awards, I $filter (ed) the award type.
Last, I did $sort for the award score first and then writtenDate,
db.collection.aggregate([
{
"$match": {
"publishedOn.profileId": "9y2RwJpzzyk29ApiC"
}
},
{
"$project": {
"writtenDate": 1,
"awards": {
"$filter": {
"input": "$awards",
"as": "award",
"cond": {
"$eq": [
"$$award.type",
"challengeWinner"
]
}
}
}
}
},
{
"$sort": {
"awards.score": 1,
"writtenDate": 1,
}
}
])
Working of above query: https://mongoplayground.net/p/MzWQCR2Gshg
Happy Coding !!!
I have a collection called transaction with below documents,
/* 0 */
{
"_id" : ObjectId("5603fad216e90d53d6795131"),
"statusId" : "65c719e6727d",
"relatedWith" : "65c719e67267",
"status" : "A",
"userId" : "100",
"createdTs" : ISODate("2015-09-24T13:15:36.609Z")
}
/* 1 */
{
"_id" : ObjectId("5603fad216e90d53d6795134"),
"statusId" : "65c719e6727d",
"relatedWith" : "65c719e6726d",
"status" : "B",
"userId" : "100",
"createdTs" : ISODate("2015-09-24T13:14:31.609Z")
}
/* 2 */
{
"_id" : ObjectId("5603fad216e90d53d679512e"),
"statusId" : "65c719e6727d",
"relatedWith" : "65c719e6726d",
"status" : "C",
"userId" : "100",
"createdTs" : ISODate("2015-09-24T13:13:36.609Z")
}
/* 3 */
{
"_id" : ObjectId("5603fad216e90d53d6795132"),
"statusId" : "65c719e6727d",
"relatedWith" : "65c719e6726d",
"status" : "D",
"userId" : "100",
"createdTs" : ISODate("2015-09-24T13:16:36.609Z")
}
When I run the below Aggregation query without $group,
db.transaction.aggregate([
{
"$match": {
"userId": "100",
"statusId": "65c719e6727d"
}
},
{
"$sort": {
"createdTs": -1
}
}
])
I get the result in expected sorting order. i.e Sort createdTs in descending order (Minimal result)
/* 0 */
{
"result" : [
{
"_id" : ObjectId("5603fad216e90d53d6795132"),
"createdTs" : ISODate("2015-09-24T13:16:36.609Z")
},
{
"_id" : ObjectId("5603fad216e90d53d6795131"),
"createdTs" : ISODate("2015-09-24T13:15:36.609Z")
},
{
"_id" : ObjectId("5603fad216e90d53d6795134"),
"createdTs" : ISODate("2015-09-24T13:14:31.609Z")
},
{
"_id" : ObjectId("5603fad216e90d53d679512e"),
"createdTs" : ISODate("2015-09-24T13:13:36.609Z")
}
],
"ok" : 1
}
If I apply the below aggregation with $group, the resultant is inversely sorted(i.e Ascending sort)
db.transaction.aggregate([
{
"$match": {
"userId": "100",
"statusId": "65c719e6727d"
}
},
{
"$sort": {
"createdTs": -1
}
},
{
$group: {
"_id": {
"statusId": "$statusId",
"relatedWith": "$relatedWith",
"status": "$status"
},
"status": {$first: "$status"},
"statusId": {$first: "$statusId"},
"relatedWith": {$first: "$relatedWith"},
"createdTs": {$first: "$createdTs"}
}
}
]);
I get the result in inverse Order i.e. ** Sort createdTs in Ascending order**
/* 0 */
{
"result" : [
{
"_id" : ObjectId("5603fad216e90d53d679512e"),
"createdTs" : ISODate("2015-09-24T13:13:36.609Z")
},
{
"_id" : ObjectId("5603fad216e90d53d6795134"),
"createdTs" : ISODate("2015-09-24T13:14:31.609Z")
},
{
"_id" : ObjectId("5603fad216e90d53d6795131"),
"createdTs" : ISODate("2015-09-24T13:15:36.609Z")
},
{
"_id" : ObjectId("5603fad216e90d53d6795132"),
"createdTs" : ISODate("2015-09-24T13:16:36.609Z")
}
],
"ok" : 1
}
Where am I wrong ?
The $group stage doesn't insure the ordering of the results. See here the first paragraph.
If you want the results to be sorted after a $group, you need to add a $sort after the $group stage.
In your case, you should move the $sort after the $group and before you ask the question : No, the $sort won't be able to use an index after the $group like it does before the $group :-).
The internal algorithm of $group seems to keep some sort of ordering (reversed apparently), but I would not count on that and add a $sort.
You are not doing anything wrong here, Its a $group behavior in Mongodb
Lets have a look in this example
Suppose you have following doc in collection
{ "_id" : 1, "item" : "abc", "price" : 10, "quantity" : 2, "date" : ISODate("2014-01-01T08:00:00Z") }
{ "_id" : 2, "item" : "jkl", "price" : 20, "quantity" : 1, "date" : ISODate("2014-02-03T09:00:00Z") }
{ "_id" : 3, "item" : "xyz", "price" : 5, "quantity" : 5, "date" : ISODate("2014-02-03T09:05:00Z") }
{ "_id" : 4, "item" : "abc", "price" : 10, "quantity" : 10, "date" : ISODate("2014-02-15T08:00:00Z") }
{ "_id" : 5, "item" : "xyz", "price" : 5, "quantity" : 10, "date" : ISODate("2014-02-15T09:05:00Z") }
{ "_id" : 6, "item" : "xyz", "price" : 5, "quantity" : 5, "date" : ISODate("2014-02-15T12:05:10Z") }
{ "_id" : 7, "item" : "xyz", "price" : 5, "quantity" : 10, "date" : ISODate("2014-02-15T14:12:12Z") }
Now if you run this
db.collection.aggregate([{ $sort: { item: 1,date:1}} ] )
the output will be in ascending order of item and date.
Now if you add group stage in aggregation pipeline it will reverse the order.
db.collection.aggregate([{ $sort: { item: 1,date:1}},{$group:{_id:"$item"}} ] )
Output will be
{ "_id" : "xyz" }
{ "_id" : "jkl" }
{ "_id" : "abc" }
Now the solution for your problem
change "createdTs": -1 to "createdTs": 1 for group
Need to find the difference between two values of attendance,group by ward_id, based on patient id for two dates. The result has dynamic values based on the array. The difference is between two dates. Key would be ward_id, the difference will be between counts of patient's visit to the ward.
Example sample data
{
"_id" : {
"type" : "patient_attendence",
"ts" : ISODate("2015-02-03T21:31:29.902Z"),
"ward_id" : 2561
},
"count" : 4112,
"values" : [
{
"count" : 9,
"patient" : ObjectId("54766f973f35473ffc644618")
},
{
"count" : 19,
"patient" : ObjectId("546680e2d660e2dc5ebfea39")
},
{
"count" : 47,
"patient" : ObjectId("546680e3d660e2dc5ebfea72")
},
{
"count" : 1,
"patient" : ObjectId("546a137bdab5f21e612ea7ef")
},
{
"count" : 93,
"patient" : ObjectId("546680e3d660e2dc5ebfea89")
}
]
}
{
"_id" : {
"type" : "patient_attendence",
"ts" : ISODate("2015-02-03T21:31:29.902Z"),
"ward_id" : 3720
},
"count" : 1,
"values" : [
{
"count" : 1,
"patient" : ObjectId("546a136ddab5f21e612ea6a6")
}
]
}
{
"_id" : {
"type" : "patient_attendence",
"ts" : ISODate("2015-02-04T21:31:29.902Z"),
"ward_id" : 2561
},
"count" : 4112,
"values" : [
{
"count" : 10,
"patient" : ObjectId("54766f973f35473ffc644618")
},
{
"count" : 10,
"patient" : ObjectId("546680e2d660e2dc5ebfea39")
},
{
"count" : 6,
"patient" : ObjectId("5474e9e46606f32570fa48ff")
},
{
"count" : 1,
"patient" : ObjectId("5474e9e36606f32570fa48f2")
},
{
"count" : 1,
"patient" : ObjectId("546680e3d660e2dc5ebfea77")
},
{
"count" : 543,
"patient" : ObjectId("546680e2d660e2dc5ebfea43")
},
{
"count" : 1,
"patient" : ObjectId("5485fdc8d27a9122956b1c66")
}
]
}
{
"_id" : {
"type" : "patient_attendence",
"ts" : ISODate("2015-02-04T21:31:29.902Z"),
"ward_id" : 3720
},
"count" : 1,
"values" : [
{
"count" : 7,
"patient" : ObjectId("546a136ddab5f21e612ea6a6")
}
]
}
Output
{
"ward_id":2561,
"result" : [{"person": ObjectId("54766f973f35473ffc644618"),
"count_1": 9,
"count_1": 10,
"difference":1 },{"person": ObjectId("546680e2d660e2dc5ebfea39"),
"count_1": 19,
"count_1": 10,
"difference":-9 } ....]
},
{
"ward_id":3720,
"result" : [{"person": ObjectId("546a136ddab5f21e612ea6a6"),
"count_1": 9,
"count_1": 10,
"difference":1 },{"person": ObjectId("546680e2d660e2dc5ebfea39"),
"count_1": 1,
"count_1": 7,
"difference":-6 }]
}
you can use the aggregation framework's $subtract operator outlined here: http://docs.mongodb.org/manual/reference/operator/aggregation-arithmetic/
db.wards.aggregate([
{
$match: {id: {$elemMatch: {ward_id: my_ward_id, ts: my_desired_ts}}},
},
{
$limit: 2
},
{
$project: {values: 1}
},
{
$unwind: '$values'
},
{
$match: {patient: my_patient_id}
},
{
$group: {
_id: null,
'count1': {$first: '$values.count'},
'count2': {$last: '$values.count'}
}
},
{
$subtract: ['$count1', '$count2']
}
])
i haven't tested this but it would probably look like something above
I have a collection named 'Dealer' with following fields.
1) userId
2) dealerId
3) code
4) origin (having values 'UUM', 'MMT', 'TTC')
In the above collection, I need to get unique dealer records with unique combination of (userId + dealerId). If two records are having same 'userId' and 'dealerId' then I need to check the origin field and the record with value not equal to 'UUM' needs to be returned in resultset.
This is what I reached up to, as of now:
db.dealer.aggregate(
[
{
$sort: { origin: 1 }
},
{
$group:
{
_id: {
dealerId:"$dealerId",
recordId:"$recordId"
},
origin: {
$first: "$origin"
}
}
}
])
How can I make an aggregation query for the above scenario.Any help is appreciated.
Thanks in advance.
To reduce memory usage, I would filter the docs that have don't have a UUM origin.
Then the group by dealers and users.
I'm not sure why you're sorting and grouping by dealer + record.
Setup
> db.dealerTest.find()
{ "_id" : 1, "userId" : "u1", "dealerId" : "d1", "code" : 1, "origin" : "UUM" }
{ "_id" : 2, "userId" : "u1", "dealerId" : "d1", "code" : 2, "origin" : "UUM" }
{ "_id" : 3, "userId" : "u1", "dealerId" : "d1", "code" : 3, "origin" : "TTC" }
{ "_id" : 4, "userId" : "u2", "dealerId" : "d1", "code" : 4, "origin" : "TTC" }
{ "_id" : 5, "userId" : "u2", "dealerId" : "d1", "code" : 5, "origin" : "MMT" }
{ "_id" : 6, "userId" : "u2", "dealerId" : "d2", "code" : 6, "origin" : "UUM" }
Code:
db.dealerTest.aggregate([{
$match: {
origin: {
$ne: "UUM"
}
}
}, {
$group: {
_id: {
dealerId: "$dealerId",
userId: "$userId"
},
docIds: { $addToSet : "$_id" },
origins: { $addToSet : "$origin" }
}
}]);
Output:
{ "_id" : { "dealerId" : "d1", "userId" : "u2" }, "docIds" : [ 5, 4 ], "origins" : [ "MMT", "TTC" ] }
{ "_id" : { "dealerId" : "d1", "userId" : "u1" }, "docIds" : [ 3 ], "origins" : [ "TTC" ] }
Is it possible to use the aggregation framework to group by a specific element of an array?
Such that with documents like this:
{
name: 'Russell',
favourite_foods: [
{ name: 'Pizza', type: 'Four Cheeses' },
{ name: 'Burger', type: 'Veggie'}
],
height: 6
}
I could get a distinct list of top favourite foods (ie. foods at index 0) along with the height of the tallest person who's top favourite food that is?
Something like this (although it doesn't work as the array index access dot notation doesn't seem to work in the aggregation framework):
db.people.aggregate([
{ $group : { _id: "$favourite_foods.0.name", max_height: { $max : "$height" } } }
])
Seems like you are relying on the favorite food for each person being first in the array. If so, there is an aggregation framework operator you can take advantage of.
Here is the pipeline you can use:
db.people.aggregate(
[
{
"$unwind" : "$favourite_foods"
},
{
"$group" : {
"_id" : {
"name" : "$name",
"height" : "$height"
},
"faveFood" : {
"$first" : "$favourite_foods"
}
}
},
{
"$group" : {
"_id" : "$faveFood.name",
"height" : {
"$max" : "$_id.height"
}
}
}
])
On this sample dataset:
> db.people.find().pretty()
{
"_id" : ObjectId("508894efd4197aa2b9490741"),
"name" : "Russell",
"favourite_foods" : [
{
"name" : "Pizza",
"type" : "Four Cheeses"
},
{
"name" : "Burger",
"type" : "Veggie"
}
],
"height" : 6
}
{
"_id" : ObjectId("5088950bd4197aa2b9490742"),
"name" : "Lucy",
"favourite_foods" : [
{
"name" : "Pasta",
"type" : "Four Cheeses"
},
{
"name" : "Burger",
"type" : "Veggie"
}
],
"height" : 5.5
}
{
"_id" : ObjectId("5088951dd4197aa2b9490743"),
"name" : "Landy",
"favourite_foods" : [
{
"name" : "Pizza",
"type" : "Four Cheeses"
},
{
"name" : "Pizza",
"type" : "Veggie"
}
],
"height" : 5
}
{
"_id" : ObjectId("50889541d4197aa2b9490744"),
"name" : "Augie",
"favourite_foods" : [
{
"name" : "Sushi",
"type" : "Four Cheeses"
},
{
"name" : "Pizza",
"type" : "Veggie"
}
],
"height" : 6.2
}
You get these results:
{
"result" : [
{
"_id" : "Pasta",
"height" : 5.5
},
{
"_id" : "Pizza",
"height" : 6
},
{
"_id" : "Sushi",
"height" : 6.2
}
],
"ok" : 1
}
Looks like it isn't currently possible to extract a specific element from an array in aggregation:
https://jira.mongodb.org/browse/SERVER-4589
JUST add more information about the result after using "$wind":
DOCUMENT :
> db.people.find().pretty()
{
"_id" : ObjectId("508894efd4197aa2b9490741"),
"name" : "Russell",
"favourite_foods" : [
{
"name" : "Pizza",
"type" : "Four Cheeses"
},
{
"name" : "Burger",
"type" : "Veggie"
}
],
"height" : 6
},
...
AGGREAGATION :
db.people.aggregate([{
$unwind: "$favourite_foods"
}]);
RESULT :
{
"_id" : ObjectId("508894efd4197aa2b9490741"),
"name" : "Russell",
"favourite_foods" :{
"name" : "Pizza",
"type" : "Four Cheeses"
},
"height" : 6
},
{
"_id" : ObjectId("508894efd4197aa2b9490741"),
"name" : "Russell",
"favourite_foods" : {
"name" : "Burger",
"type" : "Veggie"
},
"height" : 6
}
In Addition:
If there are more than two array fields in one collection record,
we can use "$project" stage to specify the array field.
db.people.aggregate([
{
$project:{
"favourite_foods": 1
}
},
{
$unwind: "$favourite_foods"
}
]);
I think you can make use of the $project and $unwind operators (let me know if this isn't what you're trying to accomplish):
> db.people.aggregate(
{$unwind: "$favourite_foods"},
{$project: {food : "$favourite_foods", height: 1}},
{$group : { _id: "$food", max_height: { $max : "$height" } } })
{
"result" : [
{
"_id" : {
"name" : "Burger",
"type" : "Veggie"
},
"max_height" : 6
},
{
"_id" : {
"name" : "Pizza",
"type" : "Four Cheeses"
},
"max_height" : 6
}
],
"ok" : 1
}
http://docs.mongodb.org/manual/applications/aggregation/
Since mongoDB version 3.2 You can simply use $arrayElemAt and $max:
db.collection.aggregate([
{
$set: {favourite_foods: {$arrayElemAt: ["$favourite_foods", 0]}}
},
{
$group: {
_id: "$favourite_foods.name",
maxHeight: {$max: "$height"}
}
}
])
Playground example