I have collection like this.
[{
"_id" : ObjectId("62bae0858e4132ca723f00d4"),
"appliedDate" : ISODate("2022-06-28T00:00:00Z"),
"status" : "Approved"
},
{
"_id" : ObjectId("62bae0858e4132ca723f00d4"),
"appliedDate" : ISODate("2022-06-24T00:00:00Z"),
"status" : "Applied"
},
{
"_id" : ObjectId("62bae0858e4132ca723f00d4"),
"appliedDate" : ISODate("2022-06-25T00:00:00Z"),
"status" : "Applied"
},
{
"_id" : ObjectId("62bae0858e4132ca723f00d4"),
"appliedDate" : ISODate("2022-06-25T00:00:00Z"),
"status" : "Absent"
}]
I need to sort the status by Applied 1st and then by appliedDate
db.leaverequest.aggregate([
{ $match: { $text: { $search: "Applied" } } },
{ $sort: { score: { $meta: "textScore" } } }
]).pretty()
I tried the above aggregate query but its not working as expected
You can do like this
db.collection.aggregate([
{
"$sort": {
"status": 1, //sort by status
"appliedDate": 1 //if same, use appliedDate for collision resolution
}
}
])
Related
I have a collection in mongoDB that looks like this :
db.mycollection.find({})
{
"_id" : ObjectId("5deb4ce4bbe1b67e6e5611e4"),
"site" : "MDC",
"label" : "407",
"status" : "removed"
}
{
"_id" : ObjectId("5def36379ca17632de773d7e"),
"site" : "MDC",
"label" : "407",
"status" : "new"
}
{
"_id" : ObjectId("5df4740eab0d76657c19a7d2"),
"site" : "MDC",
"label" : "408",
"status" : "new"
}
I would like to regroup my documents that have the same value for the field "label" in one document with subdocument of the status, to have something like this :
{
"_id" : ObjectId("5deb4ce4bbe1b67e6e5611e4"),
"site" : "MDC",
"label" : "407",
"status" : [
{
"label" : "new"
},
{
"label" : "removed"
}
]
}
I tried different ways (aggregate, update,..) to do this but it's a complete fail...
You need to $group by label or site in order to $push your statuses:
db.collection.aggregate([
{
$group: {
_id: "$label",
old_id: { $first: "$_id" },
site: { $first: "$site" },
status: { $push: { label: "$status" } }
}
},
{
$project: {
_id: "$old_id",
site: 1,
label: "$_id",
status: 1
}
}
])
Mongo Playground
We have nested document and trying to group by array element. Our document structure looks like
/* 1 */
{
"_id" : ObjectId("5a690a4287e0e50010af1432"),
"slug" : [
"true-crime-the-10-most-infamous-american-murder-mysteries",
"10-most-infamous-american-murder-mysteries"
],
"tags" : [
{
"id" : "59244aa6b1be5055278e9b5b",
"name" : "true crime",
"_id" : "59244aa6b1be5055278e9b5b"
},
{
"id" : "5924524db1be5055278ebd6e",
"name" : "Occult Museum",
"_id" : "5924524db1be5055278ebd6e"
},
{
"id" : "5a690f0fc1a72100110c2656",
"_id" : "5a690f0fc1a72100110c2656",
"name" : "murder mysteries"
},
{
"id" : "59244d71b1be5055278ea654",
"name" : "unsolved murders",
"_id" : "59244d71b1be5055278ea654"
}
]
}
We want to find list of all slugs group by tag name. I am trying with following and it gets result but it isn't accurate. We have hundreds of records with each tag but i only get few with my query. I am not sure what i am doing wrong here.
Thanks in advance.
// Requires official MongoShell 3.6+
db.getCollection("test").aggregate(
[
{
"$match" : {
"item_type" : "Post",
"site_id" : NumberLong(2),
"status" : NumberLong(1)
}
},
{$unwind: "$tags" },
{
"$group" : {
"_id" : {
"tags᎐name" : "$tags.name",
"slug" : "$slug"
}
}
},
{
"$project" : {
"tags.name" : "$_id.tags᎐name",
"slug" : "$_id.slug",
"_id" : NumberInt(0)
}
}
],
{
"allowDiskUse" : true
}
);
Expected output is
TagName Slug
----------
true crime "true-crime-the-10-most-infamous-american-murder-mysteries",
"10-most-infamous-american-murder-mysteries"
"All records where tags true crime"
Instead of using slug as a part of _id you should use $push or $addToSet to accumulate them, try:
db.test.aggregate([
{
$unwind: "$tags"
},
{
$unwind: "$slug"
},
{
$group: {
_id: "$tags.name",
slugs: { $addToSet: "$slug" }
}
},
{
$project: {
_id: 1,
slugs: {
$reduce: {
input: "$slugs",
initialValue: "",
in: {
$concat: [ "$$value", ",", "$$this" ]
}
}
}
}
}
])
EDIT: to get comma separated string for slugs you can use $reduce with $concat
Output:
{ "_id" : "murder mysteries", "slugs" : ",10-most-infamous-american-murder-mysteries,true-crime-the-10-most-infamous-american-murder-mysteries" }
{ "_id" : "Occult Museum", "slugs" : ",10-most-infamous-american-murder-mysteries,true-crime-the-10-most-infamous-american-murder-mysteries" }
{ "_id" : "unsolved murders", "slugs" : ",10-most-infamous-american-murder-mysteries,true-crime-the-10-most-infamous-american-murder-mysteries" }
{ "_id" : "true crime", "slugs" : ",10-most-infamous-american-murder- mysteries,true-crime-the-10-most-infamous-american-murder-mysteries" }
{
"_id" : ObjectId("5763e4d6c0140edcb8731485"),
"_class" : "net.microservice.product.domain.Product",,
"createdAt" : ISODate("2016-06-17T11:53:58.228Z"),
"createdBy" : "user-0",
"modifiedAt" : ISODate("2016-06-21T06:21:47.524Z"),
"modifiedBy" : "user-0",
"merchant" : "a746f24safa5-e96f-4281-9759-a4a02b306d77",
"type" : DBRef("productTypes", ObjectId("575fd99236623f70c959247f")),
"fields" : {
"Image4" : {
"value" : "http://i.hizliresim.com/ZdELXa.jpg",
"detail" : {
"revisedBy" : "CTA",
"revisionDate" : ISODate("2016-06-21T06:21:47.204Z")
}
},
"Image3" : {
"value" : "http://i.hizliresim.com/l1WkqX.jpg",
"detail" : {
"revisedBy" : "CTA",
"revisionDate" : ISODate("2016-06-21T06:21:47.204Z")
}
},
"Image2" : {
"value" : "http://i.hizliresim.com/VYMl9n.jpg",
"detail" : {
"revisedBy" : "CTA",
"revisionDate" : ISODate("2016-06-21T06:21:47.204Z")
}
},
"Kur" : {
"value" : "TL",
"detail" : {
"revisedBy" : "CTA",
"revisionDate" : ISODate("2016-06-21T06:21:47.204Z")
}
},
"Image1" : {
"value" : "http://i.hizliresim.com/nrWAQ0.jpg",
"detail" : {
"revisedBy" : "CTA",
"revisionDate" : ISODate("2016-06-21T06:21:47.204Z")
}
},
"uploadDate" : ISODate("2016-06-17T11:53:00Z"),
"tasks" : [ ]
}
this is sample of database. I want to get data in which:
- modifiedAt is before "modifiedAt" : ISODate("2016-07-21T06:21:47.524Z"),
so i do this and this works:
db.products.find({
'modifiedAt':
{$lte: ISODate("2016-10-18T13:05:18.961Z"
)} }).
count()
14999
But i need to find for each merchant. Beause 14999 result is not true because a merchant have lots of product so 14999 includes multiple products.
I need to group by merchant and distinct. I couldnot do it.
i do this but
db.products.
aggregate([ {
$group: {
_id: '$merchant', } }, {
$match: {
modifiedAt:
{$lte: ISODate("2016-06-18T13:05:18.961Z")} }} ])
brings nothing and no error.
you can try something like this. This gives you the number of products by merchant.
db.products.aggregate([
{$match: {modifiedAt:{$lte: ISODate("2016-06-21T06:21:47.524Z")}}},
{$group: { _id: "$merchant",count: { $sum: 1 }}}
])
Output:
{ "_id" : "a89846f24safa5-e96f-4281-9759-a4a02b306d77", "count" : 1 }
Always place the $match as early in the aggregation pipeline as possible. Because $match limits the total number of documents in the aggregation pipeline, earlier $match operations minimize the amount of processing down the pipe.
So your query would be like
db.products.aggregate([
{
$match: {
modifiedAt: {
$lte: ISODate("2016-06-18T13:05:18.961Z")
}
}
},
{
$group: {
_id: '$merchant'
}
}
])
I'm using mongodb with the following collection sample
{
"_id" : ObjectId("5703750ca9c436386c4814c9"),
"user_id" : NumberLong(17),
"activitytype_id" : NumberLong(1),
"created_date" : ISODate("2015-10-03T03:52:03.000Z")
},
{
"_id" : ObjectId("5703750ca9c436386c4814ca"),
"s_id" : NumberLong(132919),
"user_id" : NumberLong(17),
"activitytype_id" : NumberLong(4),
"created_date" : ISODate("2016-03-18T17:13:43.000Z")
},
{
"_id" : ObjectId("5703750ca9c436386c4814cb"),
"s_id" : NumberLong(215283),
"user_id" : NumberLong(17),
"activitytype_id" : NumberLong(4),
"created_date" : ISODate("2015-10-03T04:12:33.000Z")
}
,
{
"_id" : ObjectId("5703750ca9c436386c4814cc"),
"s_id" : NumberLong(360888),
"user_id" : NumberLong(17),
"activitytype_id" : NumberLong(4),
"created_date" : ISODate("2015-10-03T04:12:41.000Z")
}
This is my aggregation pipeline
db.activitylogs.aggregate([
{ $group: {
_id: {
user_id: "$user_id",
activitytype_id: "$activitytype_id"
},
activity_log_docs: {
$addToSet: {
s_id: "$s_id",
friend_id: "$friend_id",
playlist_id: "$playlist_id",
created_date:"$created_date"
}
}
}},
])
I need to get distinct s_id in activity_log_docs.
here is a screenshot for the result,
screen shot for the result
i need to avoid duplicated s_id in activity_log_docs array, so i will get distinct s_id
I think something like this should do :
db.activitylogs.aggregate([
{ $group: {
_id: {
user_id: "$user_id",
activitytype_id: "$activitytype_id" ,
s_id:"$s_id"
},
friend_id: {$first:"$friend_id"}}},
playlist_id: {$first:"$playlist_id"}}},
created_date: {$first:"$created_date"}}},
{ $group: {
_id: {
user_id: "$_id.user_id",
activitytype_id: "$_id.activitytype_id"
},
activity_log_docs: {
$addToSet: {
s_id: "$_id.s_id",
friend_id: "$friend_id",
playlist_id: "$playlist_id",
created_date:"$created_date"
}
}
}},
])
But please double check your own field's name.
I am trying to do to the equivalent of the following query in mongodb:
select count(*), count(category), sum(price) from sales group by usergender
Here is what the documents in my collection look like:
{
"_id" : ObjectId("54da8b0aa7c80aed4a9f9f33"),
"userincome" : "$100,000 - $200,000",
"county" : "Los Angeles",
"userstate" : "California",
"usercity" : "Los Angeles",
"price" : 100,
"category" : "Swimwear",
"usergender" : "Male"
}
Here is my aggregation which returns count(*) and sum(price) but I am not sure how to add in count(category).
db['stream.sales'].aggregate([
{
$group:{
_id:"$usergender",
price:{
$sum:"$price"
},
_count:{
$sum:1
}
}
}
])
I know I can run a separate aggregation to get count(category) but I would like to do it in aggregation, because I don't want all my results filtered where category exists = true.
db['stream.sales'].aggregate([
{
$match:{
'category':{
"$exists":true
}
}
},
{
$group:{
_id:"$usergender",
count:{
$sum:1
}
}
}
]);
Edit:
Was able to find the solution with the help of wdberkleys response:
db['stream.sales'].aggregate([
{ "$group" : {
"_id" : "$usergender",
"count" : { "$sum" : 1 },
"price" : { "$sum" : "$price" },
"category" : { "$push" : "$category" }
} },
{ "$project" : {
"count" : 1,
"size" : 1,
"categories" : { "$size" : "$category" }
} }
])
Push the categories to a set during the $group, then $project the size of the resulting set of categories:
db.stream.sales.aggregate([
{ "$group" : {
"_id" : "$usergender",
"count" : { "$sum" : 1 },
"price" : { "$sum" : "$price" },
"categories" : { "$addToSet" : "$category" }
} },
{ "$project" : {
"count" : 1,
"size" : 1,
"categories" : { "$size" : "$category" }
} }
])