I have a db Data as follows
{
"_id" : ObjectId("5a2109572222085be93ef10d"),
"name" : "data1",
"date" : "2017-12-01T00:00.0Z",
"status" : "COMPLETED"},{
"_id" : ObjectId("5a2109572222085be93ef10d"),
"name" : "data1",
"date" : "2017-12-01T00:00.0Z",
"status" : "FAILED"}
and I want an aggreagate output as follows
{ date:"2017-12-01T00:00:0Z", total:"2", completed:1, failed:1 }
I have tried this code but didn't produce the result as above
db.test.aggregate([
{$group: {_id : {date : '$date',status:'$status'}, total:{$sum :1}}},
{$project : {date : '$_id.date', status : '$_id.status', total : '$total', _id : 0}}
])
db.test.aggregate(
// Pipeline
[
// Stage 1
{
$group: {
_id:"$date",
total:{$sum:1},
failed:{$sum:{$cond:[{$eq:["$status","FAILED"]},1,0]}},
completed:{$sum:{$cond:[{$eq:["$status","COMPLETED"]},1,0]}}
}
},
// Stage 2
{
$project: {
date : '$_id',
total : 1,
failed : 1,
completed : 1,
_id : 0,
}
},
]
);
Related
I have records in my collection
{
"_id" : ObjectId("5c37a71c54956d08afb590ef"),
"user_id" : 45,
"result" : 9,
}
{
"_id" : ObjectId("5c37a7ad54956d08afb590f0"),
"user_id" : 1,
"result" : 3,
}
{
"_id" : ObjectId("5c37a80254956d08afb590f1"),
"user_id" : 45,
"result" : 10,
}
How to get distinct records with max values (result) for each user (user_id field is unique) ?
I expect result like this:
{
"_id" : ObjectId("5c37a80254956d08afb590f1"),
"user_id" : 45, //distinct user_id
"result" : 10, //max result for user
}
{
"_id" : ObjectId("5c37a7ad54956d08afb590f0"),
"user_id" : 1, //distinct user_id
"result" : 3, //max result for user
}
You can use below aggregation:
db.col.aggregate([
{
$sort: { result: -1 }
},
{
$group: {
_id: "$user_id",
result: { $first: "$result" },
o_id: { $first: "$_id" }
}
},
{
$project: {
_id: "$o_id",
user_id: "$_id",
result: 1
}
}
])
You need to use $sort first to be able to capture both _id and result from highest result document using $group and $first operators. Output:
{ "result" : 3, "_id" : ObjectId("5c37a7ad54956d08afb590f0"), "user_id" : 1 }
{ "result" : 10, "_id" : ObjectId("5c37a80254956d08afb590f1"), "user_id" : 45 }
I have a schema in which it has some fields..
i am not able to find query for this, i tried $group but was not able to find results
collection: tasks
{
"_id" : ObjectId("5a475ee4b342fa03e71192bd"),
"title" : "Some Title",
"assignedUsers" : [
{
"_id" : ObjectId("5a47386ee4788102e530f60d"),
"name" : "Sam",
"status" : "Unconfirmed"
},
{
"_id" : ObjectId("5a473878e4788102e530f60f"),
"name" : "Ricky",
"status" : "Rejected"
}
{
"_id" : ObjectId("5a47388be4788102e530f611"),
"name" : "Niel",
"status" : "Unconfirmed"
},
{
"_id" : ObjectId("5a47388be4788102e530f611"),
"name" : "ABC",
"status" : "Unconfirmed"
},
{
"_id" : ObjectId("5a473892e4788102e530f612"),
"name" : "Rocky",
"status" : "Rejected"
}
]
}
Result should contain
Unconfirmed=3
Rejected=2
Thanks
Use below query,
db.coll3.aggregate([{
$unwind: '$assignedUsers'
}, {
$group: {
_id: '$assignedUsers.status',
'count': {
$sum: 1
}
}
}
])
If you want to query against a particular document make sure, you use a $match as first stage and then use the other 2 $unwind and $group.
You would get result as
{ "_id" : "Rejected", "count" : 2 }
{ "_id" : "Unconfirmed", "count" : 3 }
Hope this helps.
I am newbie. But I try to learn the most logical ways to write the queries.
Assume I have collection which is as;
{
"id" : NumberInt(1),
"school" : [
{
"name" : "george",
"code" : "01"
},
{
"name" : "michelangelo",
"code" : "01"
}
],
"enrolledStudents" : [
{
"userName" : "elisabeth",
"code" : NumberInt(21)
}
]
}
{
"id" : NumberInt(2),
"school" : [
{
"name" : "leonarda da vinci",
"code" : "01"
}
],
"enrolledStudents" : [
{
"userName" : "michelangelo",
"code" : NumberInt(25)
}
]
}
I want to list occurence of a key with their corresponding code values.
As an example key : michelangelo
To find the occurence of the key, I wrote two differen aggregation queries as;
db.test.aggregate([
{$unwind: "$school"},
{$match : {"school.name" : "michelangelo"}},
{$project: {_id: "$id", "key" : "$school.name", "code" : "$school.code"}}
])
and
db.test.aggregate([
{$unwind: "$enrolledStudents"},
{$match : {"enrolledStudents.userName" : "michelangelo"}},
{$project: {_id: "$id", "key" : "$enrolledStudents.userName", "code" : "$enrolledStudents.code"}}
])
the result of these 2 queries return what I want as;
{ "_id" : 1, "key" : "michelangelo", "code" : "01" }
{ "_id" : 2, "key" : "michelangelo", "code" : 25 }
One of them to search in enrolledStudents, the other one is searching in school field.
Can these 2 queries reduced into more logical query? Or is this the only way to do it?
ps: I am aware that database structure is not logical, but I tried to simulate.
edit
I try to write a query with find.
db.test.find({$or: [{"enrolledStudents.userName" : "michelangelo"} , {"school.name" : "michelangelo"}]}).pretty()
but this returns the whole documents as;
{
"id" : 1,
"school" : [
{
"name" : "george",
"code" : "01"
},
{
"name" : "michelangelo",
"code" : "01"
}
],
"enrolledStudents" : [
{
"userName" : "elisabeth",
"code" : 21
}
]
}
{
"id" : 2,
"school" : [
{
"name" : "leonarda da vinci",
"code" : "01"
}
],
"enrolledStudents" : [
{
"userName" : "michelangelo",
"code" : 25
}
]
}
Mongo 3.4
$match - This stage will keep all the school array and enrolledStudents where there is atleast one embedded document matching both the query condition
$group - This stage will combine all the school and enrolledStudents array to 2d array for each _id in a group.
$project - This stage will $filter the merge array for matching query condition and $map the array to with new labels values array.
$unwind - This stage will flatten the array.
$addFields & $replaceRoot - This stages will add the id field and promote the values array to the top.
db.collection.aggregate([
{$match : {$or: [{"enrolledStudents.userName" : "michelangelo"} , {"school.name" : "michelangelo"}]}},
{$group: {_id: "$id", merge : {$push:{$setUnion:["$school", "$enrolledStudents"]}}}},
{$project: {
values: {
$map:
{
input: {
$filter: {
input: {"$arrayElemAt":["$merge",0]},
as: "onef",
cond: {
$or: [{
$eq: ["$$onef.userName", "michelangelo"]
}, {
$eq: ["$$onef.name", "michelangelo"]
}]
}
}
},
as: "onem",
in: {
key : { $ifNull: [ "$$onem.userName", "$$onem.name" ] },
code : "$$onem.code"}
}
}
}
},
{$unwind: "$values"},
{$addFields:{"values.id":"$_id"}},
{$replaceRoot: { newRoot:"$values"}}
])
Sample Response
{ "_id" : 2, "key" : "michelangelo", "code" : 25 }
{ "_id" : 1, "key" : "michelangelo", "code" : "01" }
Mongo <= 3.2
Replace last two stages of above aggregation with $project to format the response.
{$project: {"_id": 0 , id:"$_id", key:"$values.key", code:"$values.code"}}
Sample Response
{ "_id" : 2, "key" : "michelangelo", "code" : 25 }
{ "_id" : 1, "key" : "michelangelo", "code" : "01" }
You can use $redact instead of $group & match and add $project with $map to format the response.
$redact to go through a document level at a time and perform $$DESCEND and $$PRUNE on the matching criteria.
The only thing to note is usage of $ifNull in the first document level for id so that you can $$DESCEND to embedded document level for further processing.
db.collection.aggregate([
{
$redact: {
$cond: [{
$or: [{
$eq: ["$userName", "michelangelo"]
}, {
$eq: ["$name", "michelangelo"]
}, {
$ifNull: ["$id", false]
}]
}, "$$DESCEND", "$$PRUNE"]
}
},
{
$project: {
id:1,
values: {
$map:
{
input: {$setUnion:["$school", "$enrolledStudents"]},
as: "onem",
in: {
key : { $ifNull: [ "$$onem.userName", "$$onem.name" ] },
code : "$$onem.code"}
}
}
}
},
{$unwind: "$values"},
{$project: {_id:0,id:"$id", key:"$values.key", code:"$values.code"}}
])
i have simple schema like this
{
"productName": "pppppp"
"sku" : {
"carted" : [
{
"_id" : ObjectId("56c6d606c0987668109a21f7"),
"timestamp" : ISODate("2016-02-19T08:44:54.043+0000"),
"cartId" : "56c6c1fd60c4491c157e433d",
"qty" : NumberInt(2)
},
{
"_id" : ObjectId("56c6d653172fb54817ec2356"),
"timestamp" : ISODate("2016-02-19T08:46:11.902+0000"),
"cartId" : "56c6c1fd60c4491c157e433d",
"qty" : NumberInt(2)
},
{
"_id" : ObjectId("56c6d6a7172fb54817ec2358"),
"timestamp" : ISODate("2016-02-19T08:47:35.652+0000"),
"cartId" : "56c6c1fd60c4491c157e433d",
"qty" : NumberInt(2)
}
],
"qty" : NumberInt(14)
}
}
how the way to view the product "pppppp" and show the quantity to 20? the sku.quantity added with all available sku.carted.qty.
i want it looks like this
{
"productName": "pppppp"
"qty" : 20
}
Please try this one with $group, $sum and $add
> db.collection.aggregate([
{$unwind: '$sku.carted'},
// sum the `qty` in the carted array, put this result to `qt`
{$group: {
_id: {productName: '$productName', q: '$sku.qty'},
qt: {$sum: '$sku.carted.qty'}
}},
// add the `qt` and `sku.qty`
// and reshape the output result.
{$project: {
_id: 0,
productName: '$_id.productName',
qty: {$add: ['$_id.q', '$qt']}
}}
]);
I have a collection named votes:
{
"_id" : ObjectId("54a3cb59b2b8ded51693074d"),
"Pseudo" : "Cacaboy",
"Type" : "down",
"postvote" : ObjectId("54a2f05bedbe1109145b06b6"),
"CreatedDate" : ISODate("2014-12-31T10:02:34.209Z"),
"__v" : 0
}
{
"_id" : ObjectId("54a3d776ecbf63c61a91d396"),
"Pseudo" : "CosmicJB",
"Type" : "up",
"postvote" : ObjectId("54a2f05bedbe1109145b06b6"),
"CreatedDate" : ISODate("2014-12-31T11:01:10.715Z"),
"__v" : 0
}
{
"_id" : ObjectId("54a3dca5b2b8ded51693074e"),
"Pseudo" : "hateman",
"Type" : "down",
"postvote" : ObjectId("54a2f05bedbe1109145b06b6"),
"CreatedDate" : ISODate("2014-12-31T10:02:34.209Z"),
"__v" : 0
}
Implemented Aggregation pipeline:
Vote.aggregate({$match: {postvote: pvote}},
{$group: {_id: '$Type',
n: { $sum: 1 }
}},
function(err, cb){
console.log(cb);
});
Obtained o/p:
[ { _id: 'up', n: 1 }, { _id: 'down', n: 2 } ]
Desired Result, for a postvote:
If up and down votes, both are present then result:up-down.
If just down votes are present then, result: -down.
If just up votes are present then result:up.
Is it possible using aggregation?
You need to modify your aggregation pipeline to perform the below operations:
Match the records with the desired postvote id(s).
For each record, project an extra field named weight, for the records of Type - up, the
weight would be 1, for the other -1.
Group based on the postvote field, to project the sum of the weight field for the
postvote as result.
Code:
Vote.aggregate(
{$match:{"postvote":pvote}},
{$project:{"postvote":1,"weight":{$cond:[{$eq:["$Type","up"]},1,-1]}}},
{$group:{"_id":"$postvote","result":{$sum:"$weight"}}},
function(err,data){
// handle response.
}
)
Sample o/p:
{ "_id" : ObjectId("54a2f05bedbe1109145b06b6"), "result" : -1 }