db.col.aggregate([
{
$match: {
field_nest: { $elemMatch: { /* conditions */ } }
}
}
])
This is my current set up. In addition to matching the parent document, it needs to also return only the subdocument that matches the $elemMatch
.
Otherwise, I would have to $unwind
and $match
again. But this would no long be able to use the index. The idea is to be able to use the indexes.
CodePudding user response:
No the $match
stage selects documents to pass along the pipeline, it does not modify the documents being passed along.
You can use $elemMatch
in the $match
stage to select the documents, and then use $filter
in an $addFields
stage to filter out the non-matching elements.
Perhaps something like:
db.col.aggregate([
{$match: {
field_nest: { $elemMatch: { /* conditions */ } }
}},
{$addFields: {
field_nest: {$filter:{
input: "$field_nest",
as: "item",
cond: { /* conditions */ }
}}
}}
])
This may be able to use an index, depending on the exact conditions and available indexes.
For example, if the query were
db.col.aggregate([
{$match: {
field_nest:{$elemMatch:{a:1,b:2}}
}}
])
It could use an index on {"field_nest.a":1,"field_nest.b":1}
, but it could not use an index on {field_nest:1}
or {"field_next.c":1, "field_next.a":1}
.
If the query were
db.col.aggregate([
{$match: {
top_field: "name",
some_value: {$gte: "never"},
field_nest:{$elemMatch:{a:1,b:2}}
}}
])
the query executor would look at all of the available indexes, but may use an index that does not include the array field.
If the query were
{$match: {
top_field: "name",
some_value: {$gte: "never"},
field_nest:{$elemMatch:{a:{$regex:"unanchored"},b:2}}
}}
])
it would not be able to use an index for selecting field_nest.a
, but might be able to use one for field_nest.b
.
The determination of whether or not an index will be used depends greatly on the exact nature of the match conditions and available indexes.