Retrieve only the queried element in an object array in MongoDB collection

Question

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?

Answer 1

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"
            }
        ]
    }
]

Answer 2

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
}

Answer 3

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()

Answer 4

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.

Answer 5

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.

Answer 6

 db.getCollection('aj').find({"shapes.color":"red"},{"shapes.$":1})

OUTPUTS

{

   "shapes" : [ 
       {
           "shape" : "circle",
           "color" : "red"
       }
   ]
}

Answer 7

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.

Answer 8

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"
    }
]}

Answer 9

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'.

Answer 10

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
    }
  }
)

Answer 11

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']]}
     }}
  }}
])

Answer 12

db.test.find( {"shapes.color": "red"}, {_id: 0})

Answer 13

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")
        }
    ]
}

Answer 14

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
                }
        ]
}