I am working on a MERN project. I have created a collection in MongoDB having different types of document. Is it an accepted practice to have different structure documents in a single collection? Secondly i need to fetch only a single document from the collection using the key name. My documents are
[{
"_id": {
"$oid": "6333f72822dc0acc4bea17bd"
},
"designation": [
{
"name": "Chairman",
"level": 17
},
{
"name": "Director",
"level": 13
},
{
"name": "Secretary ",
"level": 13
},
{
"name": "Account Officer",
"level": 9
},
{
"name": "Data Entry Operator-GR B",
"level": 5
}
]
},
{
"_id": {
"$oid": "6334313b22dc0acc4bea17c2"
},
"storeRole": ["manager", "approver", "accepter", "firstsignatory"]
},
{
"_id": {
"$oid": "63369d2083a7cc2e818990dd"
},
"designationSuffix": ["I","II", "III"]
}]
How do I get any of the three documents if I only know the key name i.e(designation, storeRole, designationSuffix). I dont want to use ID value.
Welcome to SO.
First, yes it is an accepted practice and indeed, a powerful feature of MongoDB to have different shapes of data in a single collection.
There are two important things to remember when querying for data:
Matching on fields that don't even exist in a document is OK; the document will simply be skipped. This permits you, for example, to query for storeRole and ignore the other documents with designation, etc. -- unless of course you wish to look for those too using an $or expression.
Matching (using $match) for elements in an array will return the whole array, not just the elements that match.
To illustrate this point, let's expand your input data slightly:
{"designation": [
{"name": "Chairman","level": 17},
{"name": "Director", "level": 13}
]
},
{"designation": [
{"name": "Secretary","level": 13}
]
},
We will use dot notation to reach into the structures in the designation array to find those docs where at least one of the name fields is Chairman:
db.foo.aggregate([
{$match: {"designation.name": "Chairman"}}
]);
{
"_id" : 0,
"designation" : [
{
"name" : "Chairman",
"level" : 17
},
{
"name" : "Director",
"level" : 13
}
]
}
The query eliminated the document with name = Secretary as expected but properly returned the whole document (and the whole array) where name = Chairman. Very often the goal is to fetch only the matching items in the array; this is accomplished with the $filter operator:
db.foo.aggregate([
{$match: {"designation.name": "Chairman"}},
{$project: {
// Assigning the output of $filter to the same name as input:
designation: {$filter: {
input: "$designation",
as: "zz",
cond: {$eq: ['$$zz.name','Chairman']}
}}
}}
]);
{
"_id" : 0,
"designation" : [
{
"name" : "Chairman",
"level" : 17
}
]
}
An alternative approach which is useful when query conditions yield null or empty arrays instead of eliminating the document altogether is to $filter first, then match only on results where the array has a length > 1. We must use the $ifNull function to protect $size from being passed a null by turning it into an empty (but not null) array:
db.foo.aggregate([
{$project: {
// Assigning the output of $filter to the same name as input:
designation: {$filter: {
input: "$designation",
as: "zz",
cond: {$eq: ['$$zz.name','Chairman']}
}}
}},
{$match: {$expr: {$gt:[{$size: {$ifNull:["$designation",[] ]}}, 0]}} }
]);
Try commenting out the $match to see what $filter returns when a document has the target array field but no matches vs. when the document does not have the field.
Suppose you have the following documents in my collection:
{
"_id":ObjectId("562e7c594c12942f08fe4192"),
"shapes":[
{
"shape":"square",
"color":"blue"
},
{
"shape":"circle",
"color":"red"
}
]
},
{
"_id":ObjectId("562e7c594c12942f08fe4193"),
"shapes":[
{
"shape":"square",
"color":"black"
},
{
"shape":"circle",
"color":"green"
}
]
}
Do query:
db.test.find({"shapes.color": "red"}, {"shapes.color": 1})
Or
db.test.find({shapes: {"$elemMatch": {color: "red"}}}, {"shapes.color": 1})
Returns matched document (Document 1), but always with ALL array items in shapes:
{ "shapes":
[
{"shape": "square", "color": "blue"},
{"shape": "circle", "color": "red"}
]
}
However, I'd like to get the document (Document 1) only with the array that contains color=red:
{ "shapes":
[
{"shape": "circle", "color": "red"}
]
}
How can I do this?
MongoDB 2.2's new $elemMatch projection operator provides another way to alter the returned document to contain only the first matched shapes element:
db.test.find(
{"shapes.color": "red"},
{_id: 0, shapes: {$elemMatch: {color: "red"}}});
Returns:
{"shapes" : [{"shape": "circle", "color": "red"}]}
In 2.2 you can also do this using the $ projection operator, where the $ in a projection object field name represents the index of the field's first matching array element from the query. The following returns the same results as above:
db.test.find({"shapes.color": "red"}, {_id: 0, 'shapes.$': 1});
MongoDB 3.2 Update
Starting with the 3.2 release, you can use the new $filter aggregation operator to filter an array during projection, which has the benefit of including all matches, instead of just the first one.
db.test.aggregate([
// Get just the docs that contain a shapes element where color is 'red'
{$match: {'shapes.color': 'red'}},
{$project: {
shapes: {$filter: {
input: '$shapes',
as: 'shape',
cond: {$eq: ['$$shape.color', 'red']}
}},
_id: 0
}}
])
Results:
[
{
"shapes" : [
{
"shape" : "circle",
"color" : "red"
}
]
}
]
The new Aggregation Framework in MongoDB 2.2+ provides an alternative to Map/Reduce. The $unwind operator can be used to separate your shapes array into a stream of documents that can be matched:
db.test.aggregate(
// Start with a $match pipeline which can take advantage of an index and limit documents processed
{ $match : {
"shapes.color": "red"
}},
{ $unwind : "$shapes" },
{ $match : {
"shapes.color": "red"
}}
)
Results in:
{
"result" : [
{
"_id" : ObjectId("504425059b7c9fa7ec92beec"),
"shapes" : {
"shape" : "circle",
"color" : "red"
}
}
],
"ok" : 1
}
Caution: This answer provides a solution that was relevant at that time, before the new features of MongoDB 2.2 and up were introduced. See the other answers if you are using a more recent version of MongoDB.
The field selector parameter is limited to complete properties. It cannot be used to select part of an array, only the entire array. I tried using the $ positional operator, but that didn't work.
The easiest way is to just filter the shapes in the client.
If you really need the correct output directly from MongoDB, you can use a map-reduce to filter the shapes.
function map() {
filteredShapes = [];
this.shapes.forEach(function (s) {
if (s.color === "red") {
filteredShapes.push(s);
}
});
emit(this._id, { shapes: filteredShapes });
}
function reduce(key, values) {
return values[0];
}
res = db.test.mapReduce(map, reduce, { query: { "shapes.color": "red" } })
db[res.result].find()
Another interesing way is to use $redact, which is one of the new aggregation features of MongoDB 2.6. If you are using 2.6, you don't need an $unwind which might cause you performance problems if you have large arrays.
db.test.aggregate([
{ $match: {
shapes: { $elemMatch: {color: "red"} }
}},
{ $redact : {
$cond: {
if: { $or : [{ $eq: ["$color","red"] }, { $not : "$color" }]},
then: "$$DESCEND",
else: "$$PRUNE"
}
}}]);
$redact "restricts the contents of the documents based on information stored in the documents themselves". So it will run only inside of the document. It basically scans your document top to the bottom, and checks if it matches with your if condition which is in $cond, if there is match it will either keep the content($$DESCEND) or remove($$PRUNE).
In the example above, first $match returns the whole shapes array, and $redact strips it down to the expected result.
Note that {$not:"$color"} is necessary, because it will scan the top document as well, and if $redact does not find a color field on the top level this will return false that might strip the whole document which we don't want.
Better you can query in matching array element using $slice is it helpful to returning the significant object in an array.
db.test.find({"shapes.color" : "blue"}, {"shapes.$" : 1})
$slice is helpful when you know the index of the element, but sometimes you want
whichever array element matched your criteria. You can return the matching element
with the $ operator.
db.getCollection('aj').find({"shapes.color":"red"},{"shapes.$":1})
OUTPUTS
{
"shapes" : [
{
"shape" : "circle",
"color" : "red"
}
]
}
The syntax for find in mongodb is
db.<collection name>.find(query, projection);
and the second query that you have written, that is
db.test.find(
{shapes: {"$elemMatch": {color: "red"}}},
{"shapes.color":1})
in this you have used the $elemMatch operator in query part, whereas if you use this operator in the projection part then you will get the desired result. You can write down your query as
db.users.find(
{"shapes.color":"red"},
{_id:0, shapes: {$elemMatch : {color: "red"}}})
This will give you the desired result.
Thanks to JohnnyHK.
Here I just want to add some more complex usage.
// Document
{
"_id" : 1
"shapes" : [
{"shape" : "square", "color" : "red"},
{"shape" : "circle", "color" : "green"}
]
}
{
"_id" : 2
"shapes" : [
{"shape" : "square", "color" : "red"},
{"shape" : "circle", "color" : "green"}
]
}
// The Query
db.contents.find({
"_id" : ObjectId(1),
"shapes.color":"red"
},{
"_id": 0,
"shapes" :{
"$elemMatch":{
"color" : "red"
}
}
})
//And the Result
{"shapes":[
{
"shape" : "square",
"color" : "red"
}
]}
You just need to run query
db.test.find(
{"shapes.color": "red"},
{shapes: {$elemMatch: {color: "red"}}});
output of this query is
{
"_id" : ObjectId("562e7c594c12942f08fe4192"),
"shapes" : [
{"shape" : "circle", "color" : "red"}
]
}
as you expected it'll gives the exact field from array that matches color:'red'.
Along with $project it will be more appropriate other wise matching elements will be clubbed together with other elements in document.
db.test.aggregate(
{ "$unwind" : "$shapes" },
{ "$match" : { "shapes.color": "red" } },
{
"$project": {
"_id":1,
"item":1
}
}
)
Likewise you can find for the multiple
db.getCollection('localData').aggregate([
// Get just the docs that contain a shapes element where color is 'red'
{$match: {'shapes.color': {$in : ['red','yellow'] } }},
{$project: {
shapes: {$filter: {
input: '$shapes',
as: 'shape',
cond: {$in: ['$$shape.color', ['red', 'yellow']]}
}}
}}
])
db.test.find( {"shapes.color": "red"}, {_id: 0})
Use aggregation function and $project to get specific object field in document
db.getCollection('geolocations').aggregate([ { $project : { geolocation : 1} } ])
result:
{
"_id" : ObjectId("5e3ee15968879c0d5942464b"),
"geolocation" : [
{
"_id" : ObjectId("5e3ee3ee68879c0d5942465e"),
"latitude" : 12.9718313,
"longitude" : 77.593551,
"country" : "India",
"city" : "Chennai",
"zipcode" : "560001",
"streetName" : "Sidney Road",
"countryCode" : "in",
"ip" : "116.75.115.248",
"date" : ISODate("2020-02-08T16:38:06.584Z")
}
]
}
Although the question was asked 9.6 years ago, this has been of immense help to numerous people, me being one of them. Thank you everyone for all your queries, hints and answers. Picking up from one of the answers here.. I found that the following method can also be used to project other fields in the parent document.This may be helpful to someone.
For the following document, the need was to find out if an employee (emp #7839) has his leave history set for the year 2020. Leave history is implemented as an embedded document within the parent Employee document.
db.employees.find( {"leave_history.calendar_year": 2020},
{leave_history: {$elemMatch: {calendar_year: 2020}},empno:true,ename:true}).pretty()
{
"_id" : ObjectId("5e907ad23997181dde06e8fc"),
"empno" : 7839,
"ename" : "KING",
"mgrno" : 0,
"hiredate" : "1990-05-09",
"sal" : 100000,
"deptno" : {
"_id" : ObjectId("5e9065f53997181dde06e8f8")
},
"username" : "none",
"password" : "none",
"is_admin" : "N",
"is_approver" : "Y",
"is_manager" : "Y",
"user_role" : "AP",
"admin_approval_received" : "Y",
"active" : "Y",
"created_date" : "2020-04-10",
"updated_date" : "2020-04-10",
"application_usage_log" : [
{
"logged_in_as" : "AP",
"log_in_date" : "2020-04-10"
},
{
"logged_in_as" : "EM",
"log_in_date" : ISODate("2020-04-16T07:28:11.959Z")
}
],
"leave_history" : [
{
"calendar_year" : 2020,
"pl_used" : 0,
"cl_used" : 0,
"sl_used" : 0
},
{
"calendar_year" : 2021,
"pl_used" : 0,
"cl_used" : 0,
"sl_used" : 0
}
]
}
if you want to do filter, set and find at the same time.
let post = await Post.findOneAndUpdate(
{
_id: req.params.id,
tasks: {
$elemMatch: {
id: req.params.jobId,
date,
},
},
},
{
$set: {
'jobs.$[i].performer': performer,
'jobs.$[i].status': status,
'jobs.$[i].type': type,
},
},
{
arrayFilters: [
{
'i.id': req.params.jobId,
},
],
new: true,
}
);
This answer does not fully answer the question but it's related and I'm writing it down because someone decided to close another question marking this one as duplicate (which is not).
In my case I only wanted to filter the array elements but still return the full elements of the array. All previous answers (including the solution given in the question) gave me headaches when applying them to my particular case because:
I needed my solution to be able to return multiple results of the subarray elements.
Using $unwind + $match + $group resulted in losing root documents without matching array elements, which I didn't want to in my case because in fact I was only looking to filter out unwanted elements.
Using $project > $filter resulted in loosing the rest of the fields or the root documents or forced me to specify all of them in the projection as well which was not desirable.
So at the end I fixed all of this problems with an $addFields > $filter like this:
db.test.aggregate([
{ $match: { 'shapes.color': 'red' } },
{ $addFields: { 'shapes': { $filter: {
input: '$shapes',
as: 'shape',
cond: { $eq: ['$$shape.color', 'red'] }
} } } },
])
Explanation:
First match documents with a red coloured shape.
For those documents, add a field called shapes, which in this case will replace the original field called the same way.
To calculate the new value of shapes, $filter the elements of the original $shapes array, temporarily naming each of the array elements as shape so that later we can check if the $$shape.color is red.
Now the new shapes array only contains the desired elements.
for more details refer =
mongo db official referance
suppose you have document like this (you can have multiple document too) -
{
"_id": {
"$oid": "63b5cfbfbcc3196a2a23c44b"
},
"results": [
{
"yearOfRelease": "2022",
"imagePath": "https://upload.wikimedia.org/wikipedia/en/d/d4/The_Kashmir_Files_poster.jpg",
"title": "The Kashmir Files",
"overview": "Krishna endeavours to uncover the reason behind his parents' brutal killings in Kashmir. He is shocked to uncover a web of lies and conspiracies in connection with the massive genocide.",
"originalLanguage": "hi",
"imdbRating": "8.3",
"isbookMark": null,
"originCountry": "india",
"productionHouse": [
"Zee Studios"
],
"_id": {
"$oid": "63b5cfbfbcc3196a2a23c44c"
}
},
{
"yearOfRelease": "2022",
"imagePath": "https://upload.wikimedia.org/wikipedia/en/a/a9/Black_Adam_%28film%29_poster.jpg",
"title": "Black Adam",
"overview": "In ancient Kahndaq, Teth Adam was bestowed the almighty powers of the gods. After using these powers for vengeance, he was imprisoned, becoming Black Adam. Nearly 5,000 years have passed, and Black Adam has gone from man to myth to legend. Now free, his unique form of justice, born out of rage, is challenged by modern-day heroes who form the Justice Society: Hawkman, Dr. Fate, Atom Smasher and Cyclone",
"originalLanguage": "en",
"imdbRating": "8.3",
"isbookMark": null,
"originCountry": "United States of America",
"productionHouse": [
"DC Comics"
],
"_id": {
"$oid": "63b5cfbfbcc3196a2a23c44d"
}
},
{
"yearOfRelease": "2022",
"imagePath": "https://upload.wikimedia.org/wikipedia/en/0/09/The_Sea_Beast_film_poster.png",
"title": "The Sea Beast",
"overview": "A young girl stows away on the ship of a legendary sea monster hunter, turning his life upside down as they venture into uncharted waters.",
"originalLanguage": "en",
"imdbRating": "7.1",
"isbookMark": null,
"originCountry": "United States Canada",
"productionHouse": [
"Netflix Animation"
],
"_id": {
"$oid": "63b5cfbfbcc3196a2a23c44e"
}
},
{
"yearOfRelease": "2021",
"imagePath": "https://upload.wikimedia.org/wikipedia/en/7/7d/Hum_Do_Hamare_Do_poster.jpg",
"title": "Hum Do Hamare Do",
"overview": "Dhruv, who grew up an orphan, is in love with a woman who wishes to marry someone with a family. In order to fulfil his lover's wish, he hires two older individuals to pose as his parents.",
"originalLanguage": "hi",
"imdbRating": "6.0",
"isbookMark": null,
"originCountry": "india",
"productionHouse": [
"Maddock Films"
],
"_id": {
"$oid": "63b5cfbfbcc3196a2a23c44f"
}
},
{
"yearOfRelease": "2021",
"imagePath": "https://upload.wikimedia.org/wikipedia/en/7/74/Shang-Chi_and_the_Legend_of_the_Ten_Rings_poster.jpeg",
"title": "Shang-Chi and the Legend of the Ten Rings",
"overview": "Shang-Chi, a martial artist, lives a quiet life after he leaves his father and the shadowy Ten Rings organisation behind. Years later, he is forced to confront his past when the Ten Rings attack him.",
"originalLanguage": "en",
"imdbRating": "7.4",
"isbookMark": null,
"originCountry": "United States of America",
"productionHouse": [
"Marvel Entertainment"
],
"_id": {
"$oid": "63b5cfbfbcc3196a2a23c450"
}
}
],
"__v": 0
}
=======
mongo db query by aggregate command -
mongomodels.movieMainPageSchema.aggregate(
[
{
$project: {
_id:0, // to supress id
results: {
$filter: {
input: "$results",
as: "result",
cond: { $eq: [ "$$result.yearOfRelease", "2022" ] }
}
}
}
}
]
)
For the new version of MongoDB, it's slightly different.
For db.collection.find you can use the second parameter of find with the key being projection
db.collection.find({}, {projection: {name: 1, email: 0}});
You can also use the .project() method.
However, it is not a native MongoDB method, it's a method provided by most MongoDB driver like Mongoose, MongoDB Node.js driver etc.
db.collection.find({}).project({name: 1, email: 0});
And if you want to use findOne, it's the same that with find
db.collection.findOne({}, {projection: {name: 1, email: 0}});
But findOne doesn't have a .project() method.
I am new to MongoDB and I am doing some exercises on it. In particular I got stuck on this exercise, of which I report here the question:
Given the following structure for document "Restaurant":
{
"_id" : ObjectId("5704adbc2eb7ebe23f582818"),
"address" : {
"building" : "1007",
"coord" : [
-73.856077,
40.848447
],
"street" : "Morris Park Ave",
"zipcode" : "10462"
},
"borough" : "Bronx",
"cuisine" : "Bakery",
"grades" : [
{
"date" : ISODate("2014-03-03T00:00:00Z"),
"grade" : "A",
"score" : 2
},
{
"date" : ISODate("2013-09-11T00:00:00Z"),
"grade" : "A",
"score" : 6
},
{
"date" : ISODate("2013-01-24T00:00:00Z"),
"grade" : "A",
"score" : 10
},
{
"date" : ISODate("2011-11-23T00:00:00Z"),
"grade" : "A",
"score" : 9
},
{
"date" : ISODate("2011-03-10T00:00:00Z"),
"grade" : "B",
"score" : 14
}
],
"name" : "Morris Park Bake Shop",
"restaurant_id" : "30075445"
}
Write a MongoDB query to find the restaurant Id, name and grades for those restaurants where 2nd element of grades array contains a grade of "A" and score 9 on an ISODate "2014-08-11T00:00:00Z".
I wrote this query:
db.restaurants.find(
{
'grades.1': {
'score': 'A',
'grade': 9,
'date' : ISODate("2014-08-11T00:00:00Z")
}
},
{
restaurant_id: 1,
name: 1,
grades: 1
});
which is not working.
The solution provided is the following:
db.restaurants.find(
{ "grades.1.date": ISODate("2014-08-11T00:00:00Z"),
"grades.1.grade":"A" ,
"grades.1.score" : 9
},
{"restaurant_id" : 1,"name":1,"grades":1}
);
My questions are:
is there a way to write the query avoiding to repeat the grades.1 part?
Why is my query wrong, given that grades.1 is a document object?
If it can help answering my question, I am using MongoDB shell version: 3.2.4
EDIT:
I found an answer to question 2 thanks to this question.
In particular I discovered that order matters. Indeed, if I perform the following query, I get a valid result:
db.restaurants.find({'grades.1': {'date': ISODate("2014-08-11T00:00:00Z"), 'grade':'A', score:9}}, {restaurant_id:1, name:1, grades:1})
Note that this query works only because all subdocument's "fields" are specified, and they are specified in the same order.
Not really. But perhaps an explanation of what you "can" do:
db.junk.find({
"grades": {
"$elemMatch": {
"date" : ISODate("2014-03-03T00:00:00Z"),
"grade" : "A",
"score" : 2
}
},
"$where": function() {
var grade = this.grades[0];
return (
grade.date.valueOf() == ISODate("2014-03-03T00:00:00Z").valueOf() &&
grade.grade === "A" &&
grade.score ==== 2
)
}
})
The $elemMatch allows you to shorten a little, but it is not the "nth" element of the array. In order to narrow that further you need to use the $where clause to inspect the "nth" array element to see if all values are a match.
db.junk.aggregate([
{ "$match": {
"grades": {
"$elemMatch": {
"date" : ISODate("2014-03-03T00:00:00Z"),
"grade" : "A",
"score" : 2
}
}
}},
{ "$redact": {
"$cond": {
"if": {
"$let": {
"vars": { "grade": { "$arrayElemAt": [ "$grades", 0 ] } },
"in": {
"$and": [
{ "$eq": [ "$grade.date", ISODate("2014-03-03T00:00:00Z") ] },
{ "$eq": [ "$grade.grade", "A" ] },
{ "$eq": [ "$grade.score", 2 ] }
]
}
}
},
"then": "$$KEEP",
"else": "$$PRUNE"
}
}}
])
You can do the same logic with $redact as well using .aggregate(). It runs a little quicker, but the basic truth should be clear by now.
So using "dot notation" to specify the "nth" position for each element within the array like you have already done is the most efficient and "brief" way to write this. You cannot make it shorter or better.
Your other attempt is looking for a "document" within "grades.1" that matches exactly the document condition you are providing. If for any reason those are not the only fields present, or if they are indeed in "different order" in the stored document, then such a query condition will not be a match.