Here is a sample document. I need to count the number of Players with the name "ACDFGH". Can anyone guide me please?
{ "_id" : ObjectId("5f040b9dd956a3109ec7d839"),
"Name" : "ACDFGH",
"Publisher" : "adasdhd Co., Ltd.",
"Released" : "April 5,1920",
"Ratting" : 99,
"Country" : "UK",
"Address" : "694 Hewes Street",
"Player" : [
{
"Name" : "Derrick",
"Goal" : 705
},
{
"Name" : "Tim",
"Goal" : 379
},
{
"Name" : "Bryan",
"Goal" : 810
}
]
}
You can do this with Aggregation. The pipeline would look like this in the mongo shell:
db.collection.aggregate([
{ $match: { "Name": "ACDFGH" }},
{ $project: { "playerCount" : { $size: "$Player" }}}
])
This will give you the document with just the _id field and a playerCount field. If you want all the other fields and the playerCount, you can replace the $project with $set.
Related
I am starting MongoDB and have problems about how to create a query to filter documents by last date of every distinct name and retrieve the whole document.
I have some data into my collection (students):
{ "_id" : ObjectId("61479d4bc146b1663a8f2b7d"), "city" : "SAO PAULO", "name" : "ANA", "status" : "ACTIVE", "date1" : ISODate("2020-09-01T08:14:30.000Z") }
{ "_id" : ObjectId("61479d88c146b1663a8f2b7e"), "city" : "SAO PAULO", "name" : "MARIA", "status" : "ACTIVE", "date1" : ISODate("2020-08-01T04:16:00.000Z") }
{ "_id" : ObjectId("61479dc2c146b1663a8f2b7f"), "city" : "RIO DE JANEIRO", "name" : "MARIA", "status" : "ACTIVE", "date1" : ISODate("2021-02-01T11:10:00.000Z") }
{ "_id" : ObjectId("61479df1c146b1663a8f2b80"), "city" : "SAO PAULO", "name" : "MARIA", "status" : "INACTIVE", "date1" : ISODate("2021-02-01T11:15:00.000Z") }
{ "_id" : ObjectId("61479e60c146b1663a8f2b81"), "city" : "BRASILIA", "name" : "JOHH", "status" : "ACTIVE", "date1" : ISODate("2021-06-01T01:18:00.000Z") }
I'm creating a query to filter status "ACTIVE" and show only most recent data for each student, showing only "city", "name", "date" and I'm trying this one using $MAX or $LAST into the GROUP:
db.getCollection('students').aggregate([
{ $match: { status: "ACTIVE" } },
{ $group: { _id: { name : "$name"},
date1 : { $max : "$date1" } ,
city : { $max : "$city" } } }
])
The wanted result:
{ "city" : "SAO PAULO", "name" : "ANA", "date1" : ISODate("2020-09-01T08:14:30.000Z") }
{ "city" : "RIO DE JANEIRO", "name" : "MARIA", "date1" : ISODate("2021-02-01T11:10:00.000Z") }
{ "city" : "BRASILIA", "name" : "JOHH", "date1" : ISODate("2021-06-01T01:18:00.000Z") }
But the result is this:
{ "city" : "SAO PAULO", "name" : "ANA", "date1" : ISODate("2020-09-01T08:14:30.000Z") }
{ "city" : "SAO PAULO", "name" : "MARIA", "date1" : ISODate("2021-02-01T11:10:00.000Z") }
{ "city" : "BRASILIA", "name" : "JOHH", "date1" : ISODate("2021-06-01T01:18:00.000Z") }
It is retrieving wrong data. For ANA and JOHN (only one document each) it's ok. But MARIA has three documents and I need to retrieve all data from her document with the $max date and I'm retrieving "city" : "SAO PAULO" rather than "city" : "RIO DE JANEIRO" because operator $MAX is applied for this field too. That is applied for all fields and the GROUP operator does not allow removing the MAX operator.
I don't know to fix it.
How to get whole document, filtering by "last date of every distinct name" ?
You can use this aggregation pipeline:
First $match as you have.
Then $sort to get desired values in first position. This is used by next stage.
Into $group aggregation you get the $first value (as the document is sorted, the first value will be the desired one).
And last $project to get desired output.
db.collection.aggregate([
{
"$match": {
"status": "ACTIVE"
}
},
{
"$sort": {
"date1": -1
}
},
{
"$group": {
"_id": {
"name": "$name"
},
"date1": {
"$first": "$date1"
},
"city": {
"$first": "$city"
}
}
},
{
"$project": {
"_id": 0,
"name": "$_id.name",
"city": 1,
"date1": 1
}
}
])
Example here
The problem: I'm trying to make a query on MongoDB, but I'm using the DocumentDb from amazon, where some operations are no supported. I wanted to find an alternative to get the same result, if possible. Basically I want to change the root of the result, instead of being the first entity, I need it to be some merging of some values in different levels of the document.
So, I have the following structure in my collection:
{
"_id" : ObjectId("5e598bf4d98f7c70f9aa3b58"),
"status" : "active",
"invoices" : [
{
"_id" : ObjectId("5e598bf13b24713f50600375"),
"value" : 1157.52,
"receivables" : [
{
"situation" : {
"status" : "active",
"reason" : []
},
"rec_code" : "001",
"_id" : ObjectId("5e598bf13b24713f50600374"),
"expiration_date" : ISODate("2020-03-25T00:00:00.000Z"),
"value" : 1157.52
}
],
"invoice_code" : 9773,
"buyer" : {
"legal_name" : "test name",
"buyer_code" : "223132165498797"
}
},
],
"seller" : {
"code" : "321654897986",
"name" : "test name 2"
}
}
What I want to achieve is to list all "receivables" like this, where the _id is the _id of the receivable:
[{
"_id" : ObjectId("5e598bf13b24713f50600374"),
"situation" : {
"status" : "active",
"reason" : []
},
"rec_code" : "001",
"expiration_date" : ISODate("2020-03-25T00:00:00.000Z"),
"value" : 1157.52,
"status" : "active",
"seller" : {
"cnpj" : "321654897986",
"name" : "test name 2"
},
"invoice_code" : 9773.0,
"buyer" : {
"legal_name" : "test name",
"cnpj" : "223132165498797"
}
}]
This I can do with $replaceRoot in with the query below on MongoDB, but using documentDB I can't use $replaceRoot or $mergeObjects. Do you know how can I get the same result with other operators?:
db.testCollection.aggregate([
{ $unwind: "$invoices" },
{ $replaceRoot: {
newRoot: {
$mergeObjects: ["$$ROOT","$invoices"]}
}
},
{$project: {"_id": 0, "value": 0, "created_at": 0, "situation": 0}},
{ $unwind: "$receivables" },
{ $replaceRoot: {
newRoot: {
$mergeObjects: ["$receivables", "$$ROOT"]
}
}
},
{$project:{"created_at": 0, "receivables": 0, "invoices": 0}}
])
After going through mongodb operations, I could get a similar result fro what I wanted with the following query without $replaceRoot. It turns out it was a better query, I think:
db.testCollection.aggregate([
{$unwind: "$invoices"},
{$project : {
created_at: 1,
seller: "$seller",
buyer: "$invoices.buyer",
nnf: "$invoices.nnf",
receivable: '$invoices.receivables'
}
},
{$unwind: "$receivable"},
{$project : {
_id: '$receivable._id',
seller: 1,
buyer: 1,
invoice_code: 1,
receivable: 1,
created_at: 1,
}
},
{$sort: {"created_at": -1}},
])
This query resulted in the following structure list:
[{
"created_at" : ISODate("2020-03-06T09:47:26.161Z"),
"seller" : {
"name" : "Test name",
"cnpj" : "21231232131232"
},
"buyer" : {
"cnpj" : "21322132164654",
"legal_name" : "Test name 2"
},
"invoice_code" : 66119,
"receivable" : {
"rec_code" : "001",
"_id" : ObjectId("5e601bb5efff82b92935bad4"),
"expiration_date" : ISODate("2020-03-17T00:00:00.000Z"),
"value" : 6540.7,
"situation" : {
"status" : "active",
"reason" : []
}
},
"_id" : ObjectId("5e601bb5efff82b92935bad4")
}]
Support for $replaceRoot was added to Amazon DocumentDB in January 2021.
(Mongo newbie here, sorry) I have a mongodb collection, result of a mapreduce with this schema :
{
"_id" : "John Snow",
"value" : {
"countTot" : 500,
"countCall" : 30,
"comment" : [
{
"text" : "this is a text",
"date" : 2016-11-17 00:00:00.000Z,
"type" : "call"
},
{
"text" : "this is a text",
"date" : 2016-11-12 00:00:00.000Z,
"type" : "visit"
},
...
]
}
}
My goal is to have a document containing all the comments of a certain type. For example, a document John snow with all the calls.
I manage to have all the comments for a certain type using this :
db.general_stats.aggregate(
{ $unwind: '$value.comment' },
{ $match: {
'value.comment.type': 'call'
}}
)
However, I can't find a way to group the data received by the ID (for example john snow) even using the $group property. Any idea ?
Thanks for reading.
Here is the solution for your query.
db.getCollection('calls').aggregate([
{ $unwind: '$value.comment' },
{ $match: {
'value.comment.type': 'call'
}},
{
$group : {
_id : "$_id",
comment : { $push : "$value.comment"},
countTot : {$first : "$value.countTot"},
countCall : {$first : "$value.countCall"},
}
},
{
$project : {
_id : 1,
value : {"countTot":"$countTot","countCall":"$countCall","comment":"$comment"}
}
}
])
or either you can go with $project with $filter option
db.getCollection('calls').aggregate([
{
$project: {
"value.comment": {
$filter: {
input: "$value.comment",
as: "comment",
cond: { $eq: [ "$$comment.type", 'call' ] }
}
},
"value.countTot":"$value.countTot",
"value.countCall":"$value.countCall",
}
}
])
In both case below is my output.
{
"_id" : "John Snow",
"value" : {
"countTot" : 500,
"countCall" : 30,
"comment" : [
{
"text" : "this is a text",
"date" : "2016-11-17 00:00:00.000Z",
"type" : "call"
},
{
"text" : "this is a text 2",
"date" : "2016-11-17 00:00:00.000Z",
"type" : "call"
}
]
}
}
Here is the query which is the extension of the one present in OP.
db.general_stats.aggregate(
{ $unwind: '$value.comment' },
{ $match: {
'value.comment.type': 'call'
}},
{$group : {_id : "$_id", allValues : {"$push" : "$$ROOT"}}},
{$project : {"allValues" : 1, _id : 0} },
{$unwind : "$allValues" }
);
Output:-
{
"allValues" : {
"_id" : "John Snow",
"value" : {
"countTot" : 500,
"countCall" : 30,
"comment" : {
"text" : "this is a text",
"date" : ISODate("2016-11-25T10:46:49.258Z"),
"type" : "call"
}
}
}
}
Got my answer looking at this :
How to retrieve all matching elements present inside array in Mongo DB?
using the $addToSet property in the $group one.
I have a collection that has records looking like this:
"_id" : ObjectId("550424ef2f44472856286d56"), "accountId" : "123",
"contactOperations" :
[
{ "contactId" : "1", "operation" : 1, "date" : 500 },
{ "contactId" : "1", "operation" : 2, "date" : 501 },
{ "contactId" : "2", "operation" : 1, "date" : 502 }
]
}
I want to know the latest operation number that has been applied on a certain contact.
I'm using the aggregation framework to first unwind the contactOperations and then grouping by accountId and contactOperations.contactId and max contactOperations.date.
aggregate([{$unwind : "$contactOperations"}, {$group : {"_id":{"accountId":"$accountId", "contactId":"$contactOperations.contactId"}, "date":{$max:"$contactOperations.date"} }}])
The result I get is:
"_id" : { "accountId" : "123", "contactId" : "2" }, "time" : 502 }
"_id" : { "accountId" : "123", "contactId" : "1" }, "time" : 501 }
Which seems correct so far, but I also need the contactOperations.operation field that was recorded with $max date. How can I select that?
You have to sort the unwind values then apply $last operator to get operation for max date. Hope this query will solve your problem.
aggregate([
{
$unwind: "$contactOperations"
},
{
$sort: {
"date": 1
}
},
{
$group: {
"_id": {
"accountId": "$accountId",
"contactId": "$contactOperations.contactId"
},
"date": {
$max: "$contactOperations.date"
},
"operationId": {
$last: "$contactOperations.operation"
}
}
}
])
Expanded from How to average the summed up values in mongodb?
Using MongoDB 2.4.8,
I have the following records
{
"category" : "TOYS",
"price" : 12,
"status" : "online",
"_id" : "35043"
}
{
"category" : "TOYS",
"price" : 13,
"status" : "offline",
"_id" : "35044"
}
{
"category" : "TOYS",
"price" : 22,
"status" : "online",
"_id" : "35045"
}
{
"category" : "BOOKS",
"price" : 13,
"status" : "offline",
"_id" : "35046"
}
{
"category" : "BOOKS",
"price" : 17,
"status" : "online",
"_id" : "35047"
}
{
"category" : "TOYS",
"price" : 19,
"status" : "unavailable",
"_id" : "35048"
}
{
"category" : "BOOKS",
"price" : 10,
"status" : "unavailable",
"_id" : "35049"
}
{
"category" : "BOOKS",
"price" : 17,
"status" : "unavailable",
"_id" : "35050"
}
I want to find the average price of all categories whose status is online OR offline and total price within a category is more than 50.
Toys offline and Toys online are considered two separate categories.
I adapted the answer given.
db.items.aggregate([
{$match:
{
$or: [
{status:"online"},
{status:"offline"}
]
}
},
{$group :
{
_id: "$category",
total_price: {$sum:"$price"},
}
},
{$match:
{
total_price:{$gt:50}
}
},
{$group :
{
_id: "1",
avg_price: {$avg:"$total_price"},
}
},
]);
But I believe this query I adapted grouped categories of the same name together which is not what I am looking for.
If online and offline are the only values for status, you can remove the initial $match step. If it is needed, it would be more appropriate to use the $in operator as these values could be found in the same index (if one existed).
I think the only step you are missing is that you can $group by multiple fields (i.e. category and status):
db.items.aggregate(
// If 'online' and 'offline' are the only possible status values, this may be unnecessary
{ $match: {
'status' : { $in: [ 'online', 'offline' ] }
}},
// Group by category & status
{ $group: {
_id: { category: "$category", status: "$status" },
total_price: { $sum: "$price" },
}},
// Only find groups where total_price is > 50
{ $match: {
total_price: { $gt:50 }
}},
// Find the average price for the group
{ $group : {
_id: null,
avg_price: {$avg:"$total_price"},
}}
)