MongoDB sum() data - mongodb

I am new to mongoDB and nosql, what is the syntax to get a sum?
In MySQL, I would do something like this:
SELECT SUM(amount) from my_table WHERE member_id = 61;
How would I convert that to MongoDB? Here is what I have tried:
db.bigdata.aggregate({
$group: {
_id: {
memberId: 61,
total: {$sum: "$amount"}
}
}
})

Using http://docs.mongodb.org/manual/tutorial/aggregation-zip-code-data-set/ for reference you want:
db.bigdata.aggregate(
{
$match: {
memberId: 61
}
},
{
$group: {
_id: "$memberId",
total : { $sum : "$amount" }
}
})
From the MongoDB docs:
The aggregation pipeline is a framework for data aggregation modeled on the concept of data processing pipelines. Documents enter a multi-stage pipeline that transforms the documents into an aggregated results.

It would be better to match first and then group, so that you system only perform group operation on filtered records. If you perform group operation first then system will perform group on all records and then selects the records with memberId=61.
db.bigdata.aggregate(
{ $match : {memberId : 61 } },
{ $group : { _id: "$memberId" , total : { $sum : "$amount" } } }
)

db.bigdata.aggregate(
{ $match : {memberId : 61 } },
{ $group : { _id: "$memberId" , total : { $sum : "$amount" } } }
)
would work if you are summing data which is not a part of array, if you want to sum the data present in some array in a document then use
db.collectionName.aggregate(
{$unwind:"$arrayName"}, //unwinds the array element
{
$group:{_id: "$arrayName.arrayField", //id which you want to see in the result
total: { $sum: "$arrayName.value"}} //the field of array over which you want to sum
})
and will get result like this
{
"result" : [
{
"_id" : "someFieldvalue",
"total" : someValue
},
{
"_id" : "someOtherFieldvalue",
"total" : someValue
}
],
"ok" : 1
}

Related

Double aggregation with distinct count in MongoDB

We have a collection which stores log documents.
Is it possible to have multiple aggregations on different attributes?
A document looks like this in it's purest form:
{
_id : int,
agent : string,
username: string,
date : string,
type : int,
subType: int
}
With the following query I can easily count all documents and group them by subtype for a specific type during a specific time period:
db.logs.aggregate([
{
$match: {
$and : [
{"date" : { $gte : new ISODate("2020-11-27T00:00:00.000Z")}}
,{"date" : { $lte : new ISODate("2020-11-27T23:59:59.000Z")}}
,{"type" : 906}
]
}
},
{
$group: {
"_id" : '$subType',
count: { "$sum": 1 }
}
}
])
My output so far is perfect:
{
_id: 4,
count: 5
}
However, what I want to do is to add another counter, which will also add the distinct count as a third attribute.
Let's say I want to append the resultset above with a third attribute as a distinct count of each username, so my resultset would contain the subType as _id, a count for the total amount of documents and a second counter that represents the amount of usernames that has entries. In my case, the number of people that somehow have created documents.
A "pseudo resultset" would look like:
{
_id: 4,
countOfDocumentsOfSubstype4: 5
distinctCountOfUsernamesInDocumentsWithSubtype4: ?
}
Does this makes any sense?
Please help me improve the question as well, since it's difficult to google it when you're not a MongoDB expert.
You can first group at the finest level, then perform a second grouping to achieve what you need:
db.logs.aggregate([
{
$match: {
$and : [
{"date" : { $gte : new ISODate("2020-11-27T00:00:00.000Z")}}
,{"date" : { $lte : new ISODate("2020-11-27T23:59:59.000Z")}}
,{"type" : 906}
]
}
},
{
$group: {
"_id" : {
subType : "$subType",
username : "$username"
},
count: { "$sum": 1 }
}
},
{
$group: {
"_id" : "$_id.subType",
"countOfDocumentsOfSubstype4" : {$sum : "$count"},
"distinctCountOfUsernamesInDocumentsWithSubtype4" : {$sum : 1}
}
}
])
Here is the test cases I used:
And here is the aggregate result:

need me use aggregation mongodb in arrays

I need help in aggregate this query, I need aggregate values of debito
{
"_id" : ObjectId("5a088f6584ccb0a665900726"),
"usuario" : "tamura",
"creditos" : [
{
"nome_do_credito" : "credito inicial",
"credito" : 0
}
],
"debitos" : [
{
"nome_do_debito" : "debito inicial",
"debito" : 0
},
{
"nome_do_debito" : "Faculdade",
"debito" : "150.00"
}
]
}
I need the output
debito : 150
(0+150)
You will first need to turn all your debito fields into a numerical type (as in 150.00) since you cannot do Maths on strings (as in "150.00"). And then the following query should do the trick:
db.collection.aggregate({
$project: {
"debitos": {
$sum: "$debitos.debito"
}
}
})
In case you have more than one document in your collection and you want the total sum over all documents you can run this:
db.collection.aggregate({
$unwind: "$debitos" // flatten the "debitos" array
}, {
$group: {
"_id": null, // do not really group, just throw all documents in the same group
"debitos": {
$sum: "$debitos.debito" // sum up all debito fields
}
}
})

Mongodb aggregate add all fields

I have a collection recording impressions (views) of certain tags. I want to see the count of each tag value. In the response I also want to see the whole of the record, in the same way that mysql would.
I'm doing a group using the aggregate pipeline which looks like this
db.tag_impressions.aggregate( [
{ $group : { _id : "$tag_value" , count:{$sum:1} } },
{ $sort : { count: 1 } }
] )
I want to return all of the matched document in tag_impressions.
and I've had some success using $first
db.tag_impressions.aggregate( [
{ $group : { _id : "$tag_value" , "tag_type" : {$first : "Tag_type"} , count:{$sum:1} } },
{ $sort : { count: 1 } }
] )
But I would have to specify each field and it would take away the benefit from mongo being schema-less.
How can I return all of the document in the results?

Excluding data in mongo aggregation

I'm working with a mongodb query. Each document in the collection looks like this:
{
"_id": "12345",
"name": "Trinity Force",
"price": 3702,
"comp": [
"Zeal",
"Phage",
"Sheen",
]
}
I was working on a query that returns the 5 cheapest items (lowest price), with prices equal to 0 excluded (those trinkets though). I wrote this (sorry for poor formatting)
db.league.aggregate( { $project : { _id : 1, name: 1, price: 1, comp: 0 } },
{ $match : {price : { $gt : 0 } } },
{ $sort: { price : 1 } }).limit(5)
I ran into two problems, though; the limit function doesn't seem to work with this aggregation, and neither does the $project. The output I'm looking for should exclude the item components (hence comp: 0) and limit it to 5 outputs. Could I get some assistance, please?
db.league.aggregate(
{ $project : { _id : "$_id", name: "$name", price: "$price"} },
{ $match : { "price" : { $gt : 0 } } },
{ $sort: { "price" : 1 } },
{ $limit : 5 })
This is aggregation query to return the 5 cheapest items
imo, this is not aggregating but sorting results.
db.league.find({ price: { $gt :0} }, {comp: 0}).sort({price: 1}).limit(5)
nevertheless, i would test both for performance

MongoDB query using aggregation not returning expected results

I have a few documents that look like this example:
{
"_id": ObjectId("540f4b6496f35c16af001dc4"),
"groups": [
1,
46105,
46106,
53241,
55397,
55406,
62840
],
"vehicleid": 123,
"vehiclename": "123 - CAN BC",
"totaldistancetraveled": 472.0,
"date_num": 20140901
}
I need to find the total distance driven by all vehicles that belong to group 46105 and where theie date_num matches with 20140901.
I tried the following aggregation query:
db.vehicle_performance_monthly.aggregate(
{ $unwind : "$groups"},
{$group:
{_id: "$groups",
totalMiles: { $sum: "$totaldistancetraveled"}}},
{$match:{_id: {$in:[46106]}},{"$date_num":{$in:20140901}}}
)
But multiple matches are not being returned. Any help is appreciated.
This should work.
db.vehicle_performance_monthly.aggregate([ {
$match : {
groups : 46106,
date_num : 20140901
}
}, {
$unwind : "$groups"
}, {
$match : {
groups : 46106
}
}, {
$group : {
_id : "$groups",
totalMiles : {
$sum : "$totaldistancetraveled"
}
}
} ]);
Analysis for your original answer:
db.vehicle_performance_monthly.aggregate(
{ $unwind : "$groups"},
{$group:
{_id: "$groups",
totalMiles: { $sum: "$totaldistancetraveled"}}}, // $group doesn't map "date_name" then it will lost.
{$match:{_id: {$in:[46106]}},{"$date_num":{$in:20140901}}} // syntax error: {$match:{_id: {$in:[46106]}},{"$date_num":{$in:20140901}}} should be {$match:{_id: {$in:[46106]},"$date_num":{$in:[20140901]}}}
)
$match first to improve performance