The document format of all collections in db is as :
{
"_id": {
"$oid": "5e0983863bcf0dab51f2872b"
},
"word": "never", // get the `word` value for each of below queries
"wordset_id": "a42b50e85e",
"meanings": [{
"id": "1f1bca9d9f",
"def": "not ever",
"speech_part": "adverb",
"synonyms": ["ne'er"]
}, {
"id": "d35f973ed0",
"def": "not at all",
"speech_part": "adverb"
}]
}
I am trying to query for word/words,
1) where word length is 4 and speech_part is noun containing ac (%something% in sql) in it (The result would jack,......)
2) how to add all three starting with , ending with , containing in single query (eg: starting with j , containing ac , ending with k----> would give jack)
I have tried for 1) as:
pipeline = [
{
"$match": {
"meanings.speech_part": "noun",
"word": "/ac/",
"$expr": {"$eq": [{"$strLenCP": "$word"}, 4]}
}
}
]
query=db[collection].aggregate(pipeline)
But I got no result for this, also how to add skip and limit for an aggregate , should i use facet ?
referring SO answer, i found this:
db.Order.aggregate([
{ '$match' : { "company_id" : ObjectId("54c0...") } },
{ '$sort' : { 'order_number' : -1 } },
{ '$facet' : {
metadata: [ { $count: "total" }, { $addFields: { page: NumberInt(3) } } ],
data: [ { $skip: 20 }, { $limit: 10 } ] // As shown here------
} }
] )
For reference Pythonic pipeline would look like this:
pipeline = [
{
'$match': {
"$expr": {"$eq": [{"$strLenCP": "$word"}, 4]},
'word': re.compile('ac'),
'meanings.speech_part': "noun"
}
}
]
Related
Consider a collection client with the following documents:
[
{
"id": 1,
"Name": "Susie",
"ownership" : {
"ownershipContextCode" : "C1"
},
"clientIds": [
{
"clientClusterCode": "clientClusterCode_1",
"clientId": "11"
}
]
},
{
"id": 2,
"Name": "John",
"ownership" : {
"ownershipContextCode" : "C2"
},
"clientIds": [
{
"clientClusterCode": "clientClusterCode_2",
"clientId": "22"
}
]
}
]
I am attempting to set a field (ownershipClientCode) as the first element of the clientIds array.
The result should be like that:
[
{
"id": 1,
"Name": "Susie",
"ownership" : {
"ownershipContextCode" : "C1",
"ownershipClientCode" : "clientClusterCode_1"
},
"clientIds": [
{
"clientClusterCode": "clientClusterCode_1",
"clientId": "11"
}
],
},
{
"id": 2,
"Name": "John",
"ownership" : {
"ownershipContextCode" : "C2",
"ownershipClientCode" : "clientClusterCode_2"
},
"clientIds": [
{
"clientClusterCode": "clientClusterCode_2",
"clientId": "22"
}
],
}
]
I'm using this query but I can't get sub object from the first element in the array
db.collection.aggregate([
{
$addFields: {
"Last Semester": {
"$arrayElemAt": [
"$clientIds",
0
]
}
}
}
])
This query add the all object but I want only the field (clientClusterCode).
Some thing like that
db.collection.aggregate([
{
$addFields: {
"Last Semester": {
"$arrayElemAt": [
"$clientIds",
0
].clientClusterCode
}
}
}
])
I'm using mongodb 4.0.0
You're very close: https://mongoplayground.net/p/HY1Pj0P4z12
db.collection.aggregate([
{
$addFields: {
"ownership.ownershipClientCode": {
"$arrayElemAt": [
"$clientIds.clientClusterCode",
0
]
}
}
}
])
You can use the dot notation within the $arrayElemAt as well as when you defining the field name.
To directly set the field, do something like this (use aggregation in the update): https://mongoplayground.net/p/js-usEJSH_A
db.collection.update({},
[
{
$set: {
"ownership.ownershipClientCode": {
"$arrayElemAt": [
"$clientIds.clientClusterCode",
0
]
}
}
}
],
{
multi: true
})
Note: The second method to update needs to be an array, so that it functions as an pipeline.
This question already has answers here:
How to return just the nested documents of an array from all documents
(2 answers)
Closed 3 years ago.
I'm trying to deep query and retrieve specific fields from MongoDB, but unfortunately couldn't able to figure out the correct solution.
Document data:
[ {
"_id": 39127198,
"name": "Mike",
"details": {
"age": 25,
"vehicles":[
{"brand":"Chevrolet","model":"Silverado","plate":"AB11"},
{"brand":"Jeep","model":"Cherokee","plate":"CG678"}
]
}
}, {
"_id": 39127198,
"name": "Taylor",
"details": {
"age": 25,
"vehicles": [
{"brand":"GMC","model":"Sierra","plate":"748397"}
]
}
} ]
My requirement: Return "vehicles" array alone for a specific player. Let's say for user "Mike" in this case.
Here is what I tried;
collection.find( {"name":"Mike"} )
.project( {"details.vehicles" : 1, "_id": 0, "name": 0} )
.toArray(function(err, result) { ... } )
collection.aggregate([
{ $match: { "name":"Mike" } },
{ $project: {"details.vehicles" : 1, "_id": 0, "name": 0} }
]).toArray(function(err, result) { ... } )
Here is what I get for the above code:
[
{
"details": {
"vehicles": [
{"brand":"Chevrolet","model":"Silverado","plate":"AB11"},
{"brand":"Jeep","model":"Cherokee","plate":"CG678"}
]
}
}
]
Expected:
[
{"brand":"Chevrolet","model":"Silverado","plate":"AB11"},
{"brand":"Jeep","model":"Cherokee","plate":"CG678"}
]
I am using MongoClient. MongoDB shell version v4.2.1
You can use $unwind and $replaceRoot stages to achieve this :
db.collection.aggregate([
{
$match: {
"name": "Mike"
}
},
{
$unwind: "$details.vehicles"
},
{
$replaceRoot: {
newRoot: "$details.vehicles"
}
}
])
Will output exactly what you need.
Hope it helps
The query:
db.vehi.aggregate( [
{ $match: { "name":"Mike" } },
{ $project: { "vehicles": "$details.vehicles", "_id": 0 } }
] ).next().vehicles
The exact output:
[
{
"brand" : "Chevrolet",
"model" : "Silverado",
"plate" : "AB11"
},
{
"brand" : "Jeep",
"model" : "Cherokee",
"plate" : "CG678"
}
]
- OR -
This also gets the same result:
db.vehi.find(
{ "name" : "Mike" },
{ "details.vehicles" : 1, _id : 0 }
).next().details.vehicles
A bit odd but this is what I am looking for.
I have an array as follow:
Document 1:
Items: [
{
"ZipCode": "11111",
"ZipCode4" "1234"
}
Document 2:
Items: [
{
"ZipCode": "11111",
"ZipCode4" "0000"
}
I would like to use a single query, and send a filter on ZipCode = 1111 && ZipCode4 = 4321, if this fails, the query should look for ZipCode = 1111 && ZipCode4: 0000
Is there a way to do this in a single query ? or do I need to make 2 calls to my database ?
For matching both data set (11111/4321) and (11111/0000), you can use $or and $and with $elemMatch like the following :
db.test.find({
$or: [{
$and: [{
"Items": {
$elemMatch: { "ZipCode": "11111" }
}
}, {
"Items": {
$elemMatch: { "ZipCode4": "4321" }
}
}]
}, {
$and: [{
"Items": {
$elemMatch: { "ZipCode": "11111" }
}
}, {
"Items": {
$elemMatch: { "ZipCode4": "0000" }
}
}]
}]
})
As you want conditional staging, this is not possible but we can get closer to it like this :
db.test.aggregate([{
$match: {
$or: [{
$and: [{ "Items.ZipCode": "11111" }, { "Items.ZipCode4": "4321" }]
}, {
$and: [{ "Items.ZipCode": "11111" }, { "Items.ZipCode4": "0000" }]
}]
}
}, {
$project: {
Items: 1,
match: {
"$map": {
"input": "$Items",
"as": "val",
"in": {
"$cond": [
{ $and: [{ "$eq": ["$$val.ZipCode", "11111"] }, { "$eq": ["$$val.ZipCode4", "4321"] }] },
true,
false
]
}
}
}
}
}, {
$unwind: "$match"
}, {
$group: {
_id: "$match",
data: {
$push: {
_id: "$_id",
Items: "$Items"
}
}
}
}])
The first $match is for selecting only the items we need
The $project will build a new field that check if this items is from the 1st set of data (11111/4321) or the 2nd set of data (11111/0000).
The $unwind is used to remove the array generated by $map.
The $group group by set of data
So in the end you will have an output like the following :
{ "_id" : true, "data" : [ { "_id" : ObjectId("58af69ac594b51730a394972"), "Items" : [ { "ZipCode" : "11111", "ZipCode4" : "4321" } ] }, { "_id" : ObjectId("58af69ac594b51730a394974"), "Items" : [ { "ZipCode" : "11111", "ZipCode4" : "4321" } ] } ] }
{ "_id" : false, "data" : [ { "_id" : ObjectId("58af69ac594b51730a394971"), "Items" : [ { "ZipCode" : "11111", "ZipCode4" : "0000" } ] } ] }
Your application logic can check if there is _id:true in this output array, just take the corresponding data field for _id:true. If there is _id:false in this object take the corresponding data field for _id:false.
In the last $group, you can also use $addToSet to builds 2 field data1 & data2 for both type of data set but this will be painful to use as it will add null object to the array for each one of the opposite type :
"$addToSet": {
"$cond": [
{ "$eq": ["$_id", true] },
"$data",
null
]
}
Here is a gist
I have a product collection which looks like that:
products = [
{
"ref": "1",
"facets": [
{
"type":"category",
"val":"kitchen"
},
{
"type":"category",
"val":"bedroom"
},
{
"type":"material",
"val":"wood"
}
]
},
{
"ref": "2",
"facets": [
{
"type":"category",
"val":"kitchen"
},
{
"type":"category",
"val":"livingroom"
},
{
"type":"material",
"val":"plastic"
}
]
}
]
I would like to select and count the distinct categories and the number of products that have the category (Note that a product can have more than one category). Something like that:
[
{
"category": "kitchen",
"numberOfProducts": 2
},
{
"category": "bedroom",
"numberOfProducts": 1
},
{
"category": "livingroom",
"numberOfProducts": 1
}
]
And it would be better if I could get the same result for each different facet type, something like that:
[
{
"facetType": "category",
"distinctValues":
[
{
"val": "kitchen",
"numberOfProducts": 2
},
{
"val": "livingroom",
"numberOfProducts": 1
},
{
"val": "bedroom",
"numberOfProducts": 1
}
]
},
{
"facetType": "material",
"distinctValues":
[
{
"val": "wood",
"numberOfProducts": 1
},
{
"val": "plastic",
"numberOfProducts": 1
}
]
}
]
I am doing tests with distinct, aggregate and mapReduce. But can't achieve the results needed. Can anybody tell me the good way?
UPDATE:
With aggregate, this give me the different facet categories that a product have, but not the values nor the count of different values:
db.products.aggregate([
{$match:{'content.facets.type':'category'}},
{$group:{ _id: '$content.facets.type'} }
]).pretty();
The following aggregation pipeline will give you the desired result. In the first pipeline step, you need to do an $unwind operation on the facets array so that it's deconstructed to output a document for each element. After the $unwind stage is the first of the $group operations which groups the documents from the previous stream by category and type and calculates the number of products in each group using $sum. The next $group operation in the next pipeline stage then creates the array that holds the aggregated values by using $addToSet operator. The final pipeline stage is the $project operation which then transforms the document in the stream by modifying existing fields:
var pipeline = [
{ "$unwind": "$facets" },
{
"$group": {
"_id": {
"facetType": "$facets.type",
"value": "$facets.val"
},
"count": { "$sum": 1 }
}
},
{
"$group": {
"_id": "$_id.facetType",
"distinctValues": {
"$addToSet": {
"val": "$_id.value",
"numberOfProducts": "$count"
}
}
}
},
{
"$project": {
"_id": 0,
"facetType": "$_id",
"distinctValues": 1
}
}
];
db.product.aggregate(pipeline);
Output
/* 0 */
{
"result" : [
{
"distinctValues" : [
{
"val" : "kitchen",
"numberOfProducts" : 2
},
{
"val" : "bedroom",
"numberOfProducts" : 1
},
{
"val" : "livingroom",
"numberOfProducts" : 1
}
],
"facetType" : "category"
},
{
"distinctValues" : [
{
"val" : "wood",
"numberOfProducts" : 1
},
{
"val" : "plastic",
"numberOfProducts" : 1
}
],
"facetType" : "material"
}
],
"ok" : 1
}
This is my test collection:
>db.test.find()
{
"_id": ObjectId("54906479e89cdf95f5fb2351"),
"reports": [
{
"desc": "xxx",
"order": {"$id": ObjectId("53fbede62827b89e4f86c12e")}
}
]
},
{
"_id": ObjectId("54906515e89cdf95f5fb2352"),
"reports": [
{
"desc": "xxx"
}
]
},
{
"_id": ObjectId("549067d3e89cdf95f5fb2353"),
"reports": [
{
"desc": "xxx"
}
]
}
I want to count all documents and documents with order, so:
>db.test.aggregate({
$group: {
_id: null,
all: {
$sum: 1
},
order: {
$sum: {
"$cond": [
{
"$ifNull": ["$reports.order", false]
},
1,
0
]
}
}
}
})
and my results:
{
"result" : [
{
"_id" : null,
"all" : 3,
"order" : 3
}
],
"ok" : 1
}
but expected:
{
"result" : [
{
"_id" : null,
"all" : 3,
"order" : 1
}
],
"ok" : 1
}
It makes no difference what I'll put - "$reports.order", "$reports.xxx", etc, aggregation framework check only if the field reports exists, ignores embed.
$ifNull and $eq dosn't work with embeded documents?
Is any way to do something like this
db.test.find({"reports.order": {$exists: 1}})
in aggregation framework?
Sorry for my english and I hope that you understood what I want to show you :)
I think it doesn't work because the field "reports" contain an array, not an object.
I mean, your aggregation works as you expect in this collection:
>db.test.find()
{
"_id": ObjectId("54906479e89cdf95f5fb2351"),
"reports":
{
"desc": "xxx",
"order": {"$id": ObjectId("53fbede62827b89e4f86c12e")}
}
},
{
"_id": ObjectId("54906515e89cdf95f5fb2352"),
"reports":
{
"desc": "xxx"
}
},
{
"_id": ObjectId("549067d3e89cdf95f5fb2353"),
"reports":
{
"desc": "xxx"
}
}
Note that I removed the "[" and "]", so now it's an object, not an array (one-to-one relation).
Because you have array inside the "report" field, you need to unwind the array to output one document for each element. I suppose that if you have two "order" fields inside the "reports" array, you only wants to count it once. I mean:
"reports": [
{
"desc": "xxx",
"order": {"$id": ObjectId("53fbede62827b89e4f86c12e")},
"order": "yyy",
}
]
Should only count as one for the object final "order" sum.
In this case, you need to unwind, group by _id (because the previous example outputs two documents for the same _id) and then group again to count all documents:
db.test.aggregate([
{$unwind: '$reports'},
{$group:{
_id:"$_id",
order:{$sum:{"$cond": [
{
"$ifNull": ["$reports.order", false]
},
1,
0
]
}
}
}},
{$group:{
_id:null,
all:{$sum:1},
order: {
$sum:{
"$cond": [{$eq: ['$order', 0]}, 0, 1]
}
}
}}])
Maybe there is a shorter solution, but this works.