{
"_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'
}
}
])
Related
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" }
I have a database of teachers details as given
{ "_id" : ObjectId("5bcc0a44f2752576a8545d99"), "Teacher_id" : "Pic002", "Teacher_Name" : "Ravi Kumar", "Dept_Name" : "IT", "Salary" : 40000, "Status" : "A" }
{ "_id" : ObjectId("5bcc0a5af2752576a8545d9a"), "Teacher_id" : "Pic003", "Teacher_Name" : "Akshay", "Dept_Name" : "Comp", "Salary" : 25500, "Status" : "N" }
{ "_id" : ObjectId("5bcc0a85f2752576a8545d9b"), "Teacher_id" : "Pic003", "Teacher_Name" : "Akshay", "Dept_Name" : "Comp", "Salary" : 25500, "Status" : "N" }
{ "_id" : ObjectId("5bcc0a9af2752576a8545d9c"), "Teacher_id" : "Pic004", "Teacher_Name" : "Sumit", "Dept_Name" : "Mech", "Salary" : 35000, "Status" : "N" }
How would I list down complete details of a teacher whose Department Name is distinct?
Basically, I want to display the details of the first first and last document in this collection.
You can achieve this via this aggregation:
db.collection.aggregate([{
$group: {
_id: "$Dept_Name",
docs: {
$addToSet: "$$CURRENT"
},
count: {
$sum: 1
}
}
},
{
$match: {
"count": {
"$eq": 1
}
}
},
{
$unwind: "$docs"
},
{
$replaceRoot: {
newRoot: "$docs"
}
}
])
The idea is first to $group and at the same time keep the objects via $addToSet.
Then filter (via $match) on those which count is 1 and then $unwind & $replaceRoot.
See it working here
(Mongo newbie here, sorry) I have a mongodb collection, result of a mapreduce with this schema :
{
"_id" : "John Snow",
"value" : {
"countTot" : 500,
"countCall" : 30,
"comment" : [
{
"text" : "this is a text",
"date" : 2016-11-17 00:00:00.000Z,
"type" : "call"
},
{
"text" : "this is a text",
"date" : 2016-11-12 00:00:00.000Z,
"type" : "visit"
},
...
]
}
}
My goal is to have a document containing all the comments of a certain type. For example, a document John snow with all the calls.
I manage to have all the comments for a certain type using this :
db.general_stats.aggregate(
{ $unwind: '$value.comment' },
{ $match: {
'value.comment.type': 'call'
}}
)
However, I can't find a way to group the data received by the ID (for example john snow) even using the $group property. Any idea ?
Thanks for reading.
Here is the solution for your query.
db.getCollection('calls').aggregate([
{ $unwind: '$value.comment' },
{ $match: {
'value.comment.type': 'call'
}},
{
$group : {
_id : "$_id",
comment : { $push : "$value.comment"},
countTot : {$first : "$value.countTot"},
countCall : {$first : "$value.countCall"},
}
},
{
$project : {
_id : 1,
value : {"countTot":"$countTot","countCall":"$countCall","comment":"$comment"}
}
}
])
or either you can go with $project with $filter option
db.getCollection('calls').aggregate([
{
$project: {
"value.comment": {
$filter: {
input: "$value.comment",
as: "comment",
cond: { $eq: [ "$$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've the following structure of docs:
{
"_id" : ObjectId("5786458371d24d924d8b4575"),
"uniqueNumber" : "3899822714",
"lastUpdatedAt" : ISODate("2016-07-13T20:11:11.000Z"),
"new" : [
{
"price" : 8.4,
"created" : ISODate("2016-07-13T13:11:28.000Z")
},
{
"price" : 10.0,
"created" : ISODate("2016-07-13T14:50:56.000Z")
}
],
"used" : [
{
"price" : 10.99,
"created" : ISODate("2016-07-08T13:46:31.000Z")
},
{
"price" : 8.59,
"created" : ISODate("2016-07-13T13:11:28.000Z")
}
]
}
Now I need to get a list that gives me the lowest price of each array per date.
So, as example:
{
"uniqueNumber" : 1234,
"prices" : {
"created" : 2016-07-08,
"minNew" : 123,
"minUsed" : 22
}
}
By now I've built the following query
db.getCollection('col').aggregate([
{
$match : {
"uniqueNumber" : "3899822714"
}
},
{
$unwind : "$used"
},
{
$project : {
"uniqueNumber" : "$uniqueNumber",
"price" : "$used.price",
"ts" : "$used.created"
}
},
{
$sort : { "ts" : 1 }
},
{
$group : {_id: "$uniqueNumber", priceOfMaxTS : { $min: "$price" }, ts : { $last: "$ts" }}
}
]);
But this one will only give me the lowest price for the highest date. I couldn't really find anything that pushes me to the right direction to get the desired result.
UPDATE
I've found a way to get the lowest price of the used array grouped by day with this query:
db.getCollection('col').aggregate([
{
$match : {
"uniqueNumber" : "3899822714"
}
},
{
$unwind : "$used"
},
{
$project : {
"asin" : "$uniqueNumber",
"price" : "$used.price",
"ts" : "$used.created",
"y" : { "$year" : "$used.created" },
"m" : { "$month" : "$used.created" },
"d" : { "$dayOfMonth" : "$used.created" }
}
},
{
$group : { _id : { "year" : "$y", "month" : "$m", "day" : "$d" }, minPriceOfDay : { $min: "$price" }}
}
]);
No I only need to find a way to do this also to the new array in the same query.
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" }
} }
])