Let's say my MongoDB schema looks like this:
{car_id: "...", owner_id: "..."}
This is a many-to-many relationship. For example, the data might look like this:
+-----+----------+--------+
| _id | owner_id | car_id |
+-----+----------+--------+
| 1 | 1 | 1 |
| 2 | 1 | 2 |
| 3 | 1 | 3 |
| 4 | 2 | 1 |
| 5 | 2 | 2 |
| 6 | 3 | 4 |
| 7 | 3 | 5 |
| 8 | 3 | 6 |
| 9 | 3 | 7 |
| 10 | 1 | 1 | <-- not unique
+-----+----------+--------+
I want to get the number of cars owned by each owner. In SQL, this might look like:
SELECT owner_id, COUNT(*) AS cars_owned
FROM (SELECT owner_id FROM car_owners GROUP BY owner_id, car_id) AS t
GROUP BY owner_id;
In this case, the result would look like this:
+----------+------------+
| owner_id | cars_owned |
+----------+------------+
| 1 | 3 |
| 2 | 2 |
| 3 | 4 |
+----------+------------+
How can I accomplish this same thing using MongoDB using the aggregation framework?
To accommodate the potential duplicates, you need to use two $group operations:
db.test.aggregate([
{ $group: {
_id: { owner_id: '$owner_id', car_id: '$car_id' }
}},
{ $group: {
_id: '$_id.owner_id',
cars_owned: { $sum: 1 }
}},
{ $project: {
_id: 0,
owner_id: '$_id',
cars_owned: 1
}}]
, function(err, result){
console.log(result);
}
);
Gives a result with a format of:
[ { cars_owned: 2, owner_id: 10 },
{ cars_owned: 1, owner_id: 11 } ]
$group is similar to SQL Group by command. In the below example, we're going to aggregate companies on the basis of the year in which they were founded. And calculate the average number of employees for each company.
db.companies.aggregate([{
$group: {
_id: {
founded_year: "$founded_year"
},
average_number_of_employees: {
$avg: "$number_of_employees"
}
}
}, {
$sort: {
average_number_of_employees: -1
}
}
])
This aggregation pipeline has 2 stages
$group
$sort
Now, fundamental to the $group stage is the _id field that we specify as the part of the document. That is the value of the $group operator itself using a very strict interpretation of the arrogation framework syntax. _id is how we define, how we control, how we tune what the group stage uses to organize the documents that it sees.
The below query find the relationships of the people with companies using $sum operator:
db.companies.aggregate([{
$match: {
"relationships.person": {
$ne: null
}
}
}, {
$project: {
relationships: 1,
_id: 0
}
}, {
$unwind: "$relationships"
}, {
$group: {
_id: "$relationships.person",
count: {
$sum: 1
}
}
}, {
$sort: {
count: -1
}
}])
Related
I have tree records in mongodb but there could be many more, I'm getting shops by an ID coming from frontend
I need to get 20 records and group them by itemId and colorId, and get counts for every shop. the count of shops can be 1,2,3,....10etc..
this is output I need:
+--------+----------+-------+-------+-------+
| itemId | colorId | shop1 | shop2 | shop3 |
+========+==========+=======+=======+=======+
| 1 | colorId1 | 5 | 0 | 3 |
+--------+----------+-------+-------+-------+
| 2 | colorId2 | 3 | 0 | 0 |
+--------+----------+-------+-------+-------+
| 3 | colorId2 | 0 | 3 | 0 |
+--------+----------+-------+-------+-------+
| 2 | colorId1 | 0 | 5 | 0 |
+--------+----------+-------+-------+-------+
| 3 | colorId1 | 0 | 0 | 5 |
+--------+----------+-------+-------+-------+
here is my data and query - here shopId is string and it's work good.
but when I use this query on my local mashine, I'm getting this error:
MongoError: PlanExecutor error during aggregation :: caused by :: $arrayToObject requires an object with keys 'k' and 'v', where the value of 'k' must be of type string. Found type: objectId
but when I change shopId to the ObjectId I'm getting error.
ObjectId versoin
Per your request in the comments (if I got it right):
db.collection.aggregate([
{
"$match": {}// <-- Highly recommend you to use match due to the complexity of this query
},
{
$group: {
_id: 0,
data: {
$push: {
shopId: "$shopId",
shopItems: "$shopItems"
}
},
shopIds: {
"$push": {
shopId: "$shopId",
"count": 0
}
}
}
},
{
$unwind: "$data"
},
{
$unwind: "$data.shopItems"
},
{
$group: {
_id: {
itemId: "$data.shopItems.itemId",
colorId: "$data.shopItems.colorId"
},
data: {
$push: {
shopId: "$data.shopId",
count: "$data.shopItems.itemCount"
}
},
existing: {
$push: {
shopId: "$data.shopId",
"count": 0
}
},
shopIds: {
$first: "$shopIds"
}
}
},
{
"$addFields": {
"missing": {
"$setDifference": [
"$shopIds",
"$existing"
]
}
}
},
{
$project: {
data: {
$concatArrays: [
"$data",
"$missing"
]
}
}
},
{
$unwind: "$data"
},
{
$sort: {
"data.shopId": 1
}
},
{
$group: {
_id: "$_id",
counts: { // here you can change this key
$push: "$data"
},
totalCount: {
$sum: "$data.count" // if you want it
}
}
}
])
After the first $match, we $group in order to get all shopIds in each document.
Next we $unwind and $group by the group you wanted: by colorId and itemId. Then we are adding all the shops with count 0 and removing the ones that do have actual count. Last three steps are just for sorting, summing and formating.
You can play with it here.
In the pipeline stage before the $group stage computed the document like bellow
cycle_id | entity1 | entity 2
1 | 0 | 1
1 | 1 | 5
2 | 0 | 3
I am able to group them using bellow script
{
"$group" : {
"_id" : "$cycle_id",
"entity1" : {
"$sum" : "$entity1"
},
"entity2" : {
"$sum" : "$entity3"
},
"entity3" : {
"$sum" : "$entity3"
}
}
}
This generated output like bellow:
cycle_id | entity1 | entity 2
1 | 1 | 6
2 | 0 | 3
but what I am looking for is something where I can project it like an array of key-value pair
{
1:{
entity1: 1,
entiry2: 6
},
2:{
entity1: 3,
entiry2: 4
}
}
Is there a way I can achieve the above result. I tried to look around $arrayToObject but wasn't quite successful with that yet.
Thanks,
Nixit
Query :
db.collection.aggregate([
/** Group without any condition and merge all documents (Converted objects) into an object */
{
$group: {
_id: "",
data: {
$mergeObjects: {
$arrayToObject: [ [ { k: { $toString: "$_id" }, v: { "entity1": "$entity1", "entity2": "$entity2" } } ] ]
}
}
}
},
/** Replace `data` field as a root of the document */
{
$replaceRoot: { newRoot: "$data" }
}
])
Test : mongoplayground
Ref : aggregation-pipeline
I am trying to do an INNER JOIN with a GROUP BY in MongoDB. I am not getting any errors but no results either.
TableOne:
|Site|Starts|date |
| Google| 900 |2019-10-13|
| FB | 300 |2019-10-10|
| Yahoo | 100 |2019-10-11|
TableTWO:
|Finishes |date |
| 5 |2019-10-13|
| 4 |2019-10-10|
| 3 |2019-10-11|
Desired Output:
|Site|Starts|date | Finishes |
| Google| 900 |2019-10-13| 5 |
| FB | 300 |2019-10-10| 4 |
| Yahoo | 100 |2019-10-11| 3 |
SQL:
SELECT a.site, r.date, SUM(a.starts), SUM(r.finishes) FROM tableONE a INNER JOIN tableTWO r
ON a.site = r.site
GROUP BY a.site, r.date
ORDER BY 1
My MongoDB query:
db.tableONEaggregate([
{
'$match': { 'date': {
'$gte': '2019-09-19',
'$lte': '2019-10-19'
} }
},
{ '$lookup': {
'localField': 'site',
'from': 'tableTWO',
'foreignField': 'site',
'as': 'site_yo'
} },
{ '$unwind': '$site_yo' },
{
'$group': {
'_id': {
'site': '$site',
'date': '$site_yo.date',
},
'starts': {
'$sum': '$starts'
},
'finishes': {
'$sum': '$finishes'
}
}
}, {
'$project': {
'_id': 0,
'site': '$_id.site',
'date': '$_id.date',
'starts': '$starts',
'finishes': '$starts'
}
}, {
'$sort': {
'starts': -1
}
}, {
'$limit': 100
}
])
I am not getting any results. What us wrong with my Mongo Query?
I guess you're using a false foreign key within your Join. If you wanna join two tables you have to use ON primarykeyOfTable1 = ForeignkeyOfTable2
In your case this would be
SELECT a.site, r.date, SUM(a.starts), SUM(r.finishes) FROM tableONE a INNER JOIN tableTWO r
ON a.date = r.date
GROUP BY a.site, r.date
ORDER BY 1
Consider i have data like this:
| id | property | score | remark |
-------------------------------------------
| aaaa | alpha | 1 | alpha lowest |
| bbbb | beta | 2 | beta highest |
| cccc | alpha | 2 | alpha highest |
Given data above, i want to select distinct by field property and sort it by score highest value, so the expected results will be
| id | property | score | remark |
-------------------------------------------
| bbbb | beta | 2 | beta highest |
| cccc | alpha | 2 | alpha highest |
How to do this with mongodb?
You can easily do this by running the following aggregation pipeline operation:
db.collection.aggregate([
{ "$sort": { "score": -1 } },
{
"$group": {
"_id": "$property",
"id": { "$first": "$_id" },
"score": { "$first": "$score" },
"remark": { "$first": "$remark" }
}
},
{
"$project": {
"_id": 0,
"property": "$_id",
"score": 1,
"remark": 1,
"id": 1
}
}
])
Sample Output
{ "id" : "bbbb", "score" : 2, "remark" : "beta highest ", "property" : "beta" }
{ "id" : "cccc", "score" : 2, "remark" : "alpha highest ", "property" : "alpha" }
MongoDB has a distinct operator. However, it only returns one "column". You'd need to do multiple queries.
The best option is to use MongoDB Aggregation Framework. It works using a pipeline of operations.
I don't know the data, but it could be someting like:
db.collection.aggregate([
{ '$group' : { _id : '$property' , score: { '$max': '$score' } } }
])
You can use Robomongo client to experiment with this method.
This is a simplified version of my source data:
Cars | Manual | Petrol
1 | true | true
2 | true | false
3 | true | true
4 | true | true
5 | false | true
6 | false | true
I am trying to obtain this output:
Total cars: 6
Manual cars: 4
Petrol cars: 5
Is this possible in MongoDB using a single aggregation pipeline?
Yes, you can do this with the $group aggregation step and the $sum operator combined with $cond.
db.collection.aggregate([
$group: {
_id: null, // we want to group into a single document
"Total Cars": { $sum: 1 }, // all documents
"Manual Cars": {
$sum : {
// add a "1" when Manual is true, otherwise add a "0"
$cond: [ { $eq: [ "$Manual", true ] }
1,
0
]
}
},
"Petrol Cars": {
$sum : {
$cond: [ { $eq: [ "$Petrol", true ] }
1,
0
]
}
}
}
]);