Efficiency of indexed embedded array - mongodb

Question

I am currently evaluating the efficiency of different databases for a use case. In Mongodb, would like to store around 1 million objects with the following structure. Each object will have between 5 and 10 objects in the foo array.
{
name:"my name",
foos:[
{
foo:"...",
bar:"..."
},
{
foo:"...",
bar:"..."
},
{
foo:"...",
bar:"..."
}
]
}
I often need to search for objects which where the foos collection contains an object with a specific property, e.g.:
// mongo collection
[
{
name:'my name',
foos:[
{
foo:'one_foo',
bar:'a_bar'
},
{
foo:'two_foo',
bar:'b_bar'
}
]
},
{
name:'another name',
foos:[
{
foo:'another foo',
bar:'a_bar'
},
{
foo:'just another foo',
bar:'c_bar'
}
]
}
]
// search (pseudo code)
{ foos: {$elemMatch: {bar: 'c_bar'}} }
// returns
{
name:'another name',
foos:[
{
foo:'another foo',
bar:'a_bar'
},
{
foo:'just another foo',
bar:'c_bar'
}
]
}
Can this efficiently be done with mongo and how should the indexes be set?
I don't want you to evaluate performance for me, just an idea how mongo performs for my use case or how optimization could look like.

Answer 1

MongoDB has documentation explaining how to create indexes on embedded documents, through dot notation:
Dot Notation (Reaching into Objects)
> db.blogposts.findOne()
{ title : "My First Post", author: "Jane",
comments : [{ by: "Abe", text: "First" },
{ by : "Ada", text : "Good post" } ]
}
> db.blogposts.find( { "comments.by" : "Ada" } )
> db.blogposts.ensureIndex( { "comments.by" : 1 } );
As for the performance characteristic... just test it with your dataset.