I have a collection(named menucategories) in MongoDB 3.2.11:
{
"_id" : ...
"menus" : [
{
"code":0
},
{
"code":1
},
{
"code":2
},
{
"code":3
}
]
},
{
"_id" : ...
"menus" : [
{
"code":4
},
{
"code":5
},
{
"code":6
},
{
"code":7
}
]
},
{
"_id" : ...
"menus" : [
{
"code":8
},
{
"code":9
},
{
"code":10
},
{
"code":11
}
]
}
Every menucategory has array named menus. And every menu(element of the array) has code. The 'code' of menus is unique in every menu. I wanna get the maximum value of menu's code(in this case, 11). How can I achieve this?
If you want to find maximum value of code from all menus code then probable query will be as follows:
db.menucategories.aggregate([
{ $unwind: '$menus' },
{ $group: { _id: null, max: { $max: '$menus.code' } } },
{ $project: { max: 1, _id:0 } }
])
Click below links for more information regarding different operators:
$unwind, $group, $project
You don't need to use the $unwind aggregation pipeline operator here because starting from MongoDB 3.2, some accumulator expressions are available in the $project stage.
db.collection.aggregate([
{"$project": {"maxPerDoc": {"$max": "$menus.code"}}},
{"$group": {"_id": null, "maxValue": {"$max": "$maxPerDoc"}}}
])
Responding a previous now deleted comment, you don't need to put your pipeline in an array so the following query will work as well.
db.collection.aggregate(
{"$project": {"maxPerDoc": {"$max": "$menus.code"}}},
{"$group": {"_id": null, "maxValue": {"$max": "$maxPerDoc"}}}
)
Try with aggregation:
db.collection.aggregate({ $group : { _id: 1, max: { $max: {$max : "$menus.code"}}}});
No need of any unwind, if you need find only maximum value.
Related
My document structure looks like this:
{
"_id" : ObjectId("5aeeda07f3a664c55e830a08"),
"profileId" : ObjectId("5ad84c8c0e71892058b6a543"),
"list" : [
{
"content" : "answered your post",
"createdBy" : ObjectId("5ad84c8c0e71892058b6a540")
},
{
"content" : "answered your post",
"createdBy" : ObjectId("5ad84c8c0e71892058b6a540")
},
{
"content" : "answered your post",
"createdBy" : ObjectId("5ad84c8c0e71892058b6a540")
},
],
}
I want to count array of
list field. And apply condition before slicing that
if the list<=10 then slice all the elements of list
else 10 elements.
P.S I used this query but is returning null.
db.getCollection('post').aggregate([
{
$match:{
profileId:ObjectId("5ada84c8c0e718s9258b6a543")}
},
{$project:{notifs:{$size:"$list"}}},
{$project:{notifications:
{$cond:[
{$gte:["$notifs",10]},
{$slice:["$list",10]},
{$slice:["$list","$notifs"]}
]}
}}
])
Your first $project stage effectively wipes out all result fields but the one(s) that it explicitly projects (only notifs in your case). That's why the second $project stage cannot $slice the list field anymore (it has been removed by the first $project stage).
Also, I think your $cond/$slice combination can be more elegantly expressed using the $min operator. So there's at least the following two fixes for your problem:
Using $addFields:
db.getCollection('post').aggregate([
{ $match: { profileId: ObjectId("5ad84c8c0e71892058b6a543") } },
{ $addFields: { notifs: { $size: "$list" } } },
{ $project: {
notifications: {
$slice: [ "$list", { $min: [ "$notifs", 10 ] } ]
}
}}
])
Using a calculation inside the $project - this avoids a stage so should be preferable.
db.getCollection('post').aggregate([
{ $match: { profileId: ObjectId("5ad84c8c0e71892058b6a543") } },
{ $project: {
notifications: {
$slice: [ "$list", { $min: [ { $size: "$list" }, 10 ] } ]
}
}}
])
I am trying to calculate total value if that value exits. But query is not working 100%. So can somebody help me to solve this problem. Here my sample document. I have attached two documents. Please these documents & find out best solution
Document : 1
{
"_id" : 1"),
"message_count" : 4,
"messages" : {
"data" : [
{
"id" : "11",
"saleValue": 1000
},
{
"id" : "112",
"saleValue": 1400
},
{
"id" : "22",
},
{
"id" : "234",
"saleValue": 111
}
],
},
"createdTime" : ISODate("2018-03-18T10:18:48.000Z")
}
Document : 2
{
"_id" : 444,
"message_count" : 4,
"messages" : {
"data" : [
{
"id" : "444",
"saleValue" : 2060
},
{
"id" : "444",
},
{
"id" : 234,
"saleValue" : 260
},
{
"id" : "34534",
}
]
},
"createdTime" : ISODate("2018-03-18T03:11:50.000Z")
}
Needed Output:
{
total : 4831
}
My query :
db.getCollection('myCollection').aggregate([
{
"$group": {
"_id": "$Id",
"totalValue": {
$sum: {
$sum: "$messages.data.saleValue"
}
}
}
}
])
So please if possible help me to solve this problem. Thanks in advance
It's not working correctly because it is aggregating all the documents in the collection; you are grouping on a constant "_id": "tempId", you just need to reference the correct key by adding the $ as:
db.getCollection('myCollection').aggregate([
{ "$group": {
"_id": "$tempId",
"totalValue": {
"$sum": { "$sum": "$messages.data.saleValue" }
}
} }
])
which in essence is a single stage pipeline version of an aggregate operation with an extra field that holds the sum expression before the group pipeline then calling that field as the $sum operator in the group.
The above works since $sum from MongoDB 3.2+ is available in both the $project and $group stages and when used in the $project stage, $sum returns the sum of the list of expressions. The expression "$messages.data.value" returns a list of numbers [120, 1200] which are then used as the $sum expression:
db.getCollection('myCollection').aggregate([
{ "$project": {
"values": { "$sum": "$messages.data.value" },
"tempId": 1,
} },
{ "$group": {
"_id": "$tempId",
"totalValue": { "$sum": "$values" }
} }
])
You can add a $unwind before your $group, in that way you will deconstructs the data array, and then you can group properly:
db.myCollection.aggregate([
{
"$unwind": "$messages.data"
},
{
"$group": {
"_id": "tempId",
"totalValue": {
$sum: {
$sum: "$messages.data.value"
}
}
}
}
])
Output:
{ "_id" : "tempId", "totalValue" : 1320 }
db.getCollection('myCollection').aggregate([
{
$unwind: "$messages.data",
$group: {
"_id": "tempId",
"totalValue": { $sum: "$messages.data.value" }
}
}
])
$unwind
According to description as mentioned into above question, as a solution please try executing following aggregate query
db.myCollection.aggregate(
// Pipeline
[
// Stage 1
{
$unwind: {
path: '$messages.data'
}
},
// Stage 2
{
$group: {
_id: {
pageId: '$pageId'
},
total: {
$sum: '$messages.data.saleValue'
}
}
},
// Stage 3
{
$project: {
pageId: '$_id.pageId',
total: 1,
_id: 0
}
}
]
);
You can do it without using $group. Grouping made other data to be managed and addressed. So, I prefer using $sum and $map as shown below:
db.getCollection('myCollection').aggregate([
{
$addFields: {
total: {
$sum: {
$map: {
input: "$messages.data",
as: "message",
in: "$$message.saleValue",
},
},
},
},
},
}
])
This is my document i want to sort array documents by ascending order to get so for that my queries are in following code.but i am not getting the docs in sorted way.
The query is
db.sample.find({_id: ObjectId("55b32f5957e47fabd30c5d2e")}).sort({'naresh.ts':1}).pretty();
This is the result I am getting
{
"_id" : ObjectId("55b32f5957e47fabd30c5d2e"),
"naresh" : [
{
"ts" : "hi",
"created_by" : 1437806425105
},
{
"ts" : "hello",
"created_by" : 1437806425105
},
{
"ts" : "waht",
"created_by" : 1437807757261
},
{
"ts" : "lefo",
"created_by" : 1437807768514
},
{
"ts" : "lefow",
"created_by" : 1437807775719
}
]
}
You can use $aggregation like following query:
db.collection.aggregate({
"$match": {
"_id": ObjectId("55b32f5957e47fabd30c5d2e")
}
}, {
$unwind: "$naresh"
}, {
$sort: {
"naresh.ts": 1
}
}, {
"$group": {
_id: "$_id",
"naresh": {
$push: "$naresh"
}
}
})
The cursor .sort() only looks at the values in the array to decide to use the "smallest" value of the specified field ( in ascending order ) to determine how to "sort" the documents in the response. This does not "sort" the array content itself.
In order to sort the array, you need to use the aggregation framework to manipulate the document:
db.sample.aggregate([
{ "$match": { "_id": ObjectId("55b32f5957e47fabd30c5d2e") },
{ "$unwind": "$naresh" },
{ "$sort": { "$naresh.ts": 1 } },
{ "$group": {
"_id": "$_id",
"naresh": { "$push": "$naresh" }
}}
])
That sorts the array.
Better yet, if you "always" want then results sorted then do it as you update the document:
db.sample.update({},{ "$push": { "$each": [], "$sort": { "ts": 1 } } },{ "multi": true })
And use those same, $each and $sort modifiers when adding new elements to the array and the content will remain sorted.
If you want just query the collection and get the output sorted, then Blackes Seven's answer will work perfectly for you.
However if you want to update the documents in the sorted order, go with this update query:
update(
{
_id: ObjectId("55b32f5957e47fabd30c5d2e")
},
{
$push: {
naresh: {
$each: [],
$sort: {created_by: 1}
}
}
}
)
I'm trying to sum some values in an array of documents, with no luck.
This is the Document
db.Cuentas.find().pretty()
{
"Agno": "2013",
"Egresos": [
{
"Fecha": "28-01-2013",
"Monto": 150000,
"Detalle": "Pago Nokia Lumia a #josellop"
},
{
"Fecha": "29-01-2013",
"Monto": 4000,
"Detalle": "Cine, Pelicula fome"
}
],
"Ingresos": [],
"Mes": "Enero",
"Monto": 450000,
"Usuario": "MarioCares"
"_id": ObjectId(....)
}
So, i need the sum of all the "Monto" in "Egresos" for the "Usuario": "MarioCares". In this example 154000
Using aggregation i use this:
db.Cuentas.aggregate(
[
{ $match: {"Usuario": "MarioCares"} },
{ $group:
{
_id: null,
"suma": { $sum: "$Egresos.Monto" }
}
}
]
)
But i always get
{ "result" : [{ "_id" : null, "suma" : 0 }], "ok" : 1 }
What am i doing wrong ?
P.D. already see this and this
As Sammaye indicated, you need to $unwind the Egresos array to duplicate the matched doc per array element so you can $sum over each element:
db.Cuentas.aggregate([
{$match: {"Usuario": "MarioCares"} },
{$unwind: '$Egresos'},
{$group: {
_id: null,
"suma": {$sum: "$Egresos.Monto" }
}}
])
You can do also by this way. don't need to group just project your fields.
db.Cuentas.aggregate([
{ $match: { "Usuario": "MarioCares" } },
{
$project: {
'MontoSum': { $sum: "$Egresos.Monto" }
}
}
])
Since mongoDB version 3.4 you can use $reduce to sum array items:
db.collection.aggregate([
{
$match: {Usuario: "MarioCares"}
},
{
$project: {
suma: {
$reduce: {
input: "$Egresos",
initialValue: 0,
in: {$add: ["$$value", "$$this.Monto"]}
}
}
}
}
])
Playground example
I have a collection with documents that look like the following:
{
ipAddr: '1.2.3.4',
"results" : [
{
"Test" : "Sight",
"Score" : "FAIL",
"Reason" : "S1002"
},
{
"Test" : "Speed",
"Score" : "FAIL",
"Reason" : "85"
},
{
"Test" : "Sound",
"Score" : "FAIL",
"Reason" : "A1001"
}
],
"finalGrade" : "FAILED"
}
Here's the aggregation query I'm trying to write, what I want to do (see commented out piece), is to create a grouped field, per ipAddr, of the
'Reason / Error' code, but only if the Reason code begins with a specific letter, and only add the code in once, I tried the following:
db.aggregate([
{$group:
{ _id: "$ipAddr",
attempts: {$sum:1},
results: {$push: "$finalGrade"},
// errorCodes: {$addToSet: {$cond: ["$results.Reason": /[A|B|S|N.*/, "$results.Reason", ""]}},
finalResult: {$last: "$finalGrade"} }
}
]);
Everything works, excluding the commented out 'errorCodes' line. The logic I'm attempting to create is:
"Add the the errorCodes set the value of the results.Reason code IF it begins with an A, B, S, or N, otherwise there is nothing to add".
For the Record above, the errorCodes set should contain:
...
errorCodes: [S1002,A1001],
...
$group cannot take conditional expressions, which is why that line is not working. $project is the phase where you can transform the original document based on $conditional expressions (among other things).
You need two steps in the aggregation pipeline before you can $group - first you need to $unwind the results array, and next you need to $match to filter out the results you don't care about.
That would do the simple thing of just throwing out the results with error codes you don't care about keeping, but it sounds like you want to count the total number of failures including all error codes, but then only add particular ones to the output array? There isn't a straight-forward way to do that, you would have to make two $group $unwind passes in the pipeline.
Something similar to this will do it:
db.aggregate([
{$unwind : "$results"},
{$group:
{ _id: "$ipAddr",
attempts: {$sum:1},
results: {$push : "$results"},
finalGrade: {$last : "$finalGrade" }
}
},
{$unwind: "$results"},
{$match: {"results.Reason":/yourMatchExpression/} },
{$group:
{ _id: "$ipAddr",
attempts: {$last:"$attempts"},
errorCodes: {$addToSet: "$results.Reason"},
finalResult: {$last: "$finalGrade"}
}
]);
If you only want to count attempts that have the matching error code then you can do that with a single $group - you will need to do $unwind, $match and $group. You could use $project with $cond as you had it, but then your array of errorCodes will have an empty string entry along with all the proper error codes.
As of Mongo 2.4, $regex can be used for pattern matching, but not as an expression returning a boolean, which is what's required by $cond
Then, you can either use a $match operator to use the $regex keyword:
http://mongotry.herokuapp.com/#?bookmarkId=52fb39e207fc4c02006fcfed
[
{
"$unwind": "$results"
},
{
"$match": {
"results.Reason": {
"$regex": "[SA].*"
}
}
},
{
"$group": {
"_id": "$ipAddr",
"attempts": {
"$sum": 1
},
"results": {
"$push": "$finalGrade"
},
"undefined": {
"$last": "$finalGrade"
},
"errorCodes": {
"$addToSet": "$results.Reason"
}
}
}
]
or you can use $substr as your pattern matching is very simple
http://mongotry.herokuapp.com/index.html#?bookmarkId=52fb47bc7f295802001baa38
[
{
"$unwind": "$results"
},
{
"$group": {
"_id": "$ipAddr",
"errorCodes": {
"$addToSet": {
"$cond": [
{
"$or": [
{
"$eq": [
{
"$substr": [
"$results.Reason",
0,
1
]
},
"A"
]
},
{
"$eq": [
{
"$substr": [
"$results.Reason",
0,
1
]
},
"S"
]
}
]
},
"$results.Reason",
"null"
]
}
}
}
}
]