Combining Unique Items From Arrays - mongodb

Question

I have a data set that I am querying. The data looks like this:
db.activity.insert(
{
"_id" : ObjectId("5908e64e3b03ca372dc945d5"),
"startDate" : ISODate("2017-05-06T00:00:00Z"),
"details" : [
{
"code" : "2",
"_id" : ObjectId("5908ebf96ae5003a4471c9b2"),
"walkDistance" : "03",
"jogDistance" : "01",
"runDistance" : "08",
"sprintDistance" : "01"
}
]
}
)
db.activity.insert(
{
"_id" : ObjectId("58f79163bebac50d5b2ae760"),
"startDate" : ISODate("2017-05-07T00:00:00Z"),
"details" : [
{
"code" : "2",
"_id" : ObjectId("58f7948fbebac50d5b2ae7f2"),
"walkDistance" : "01",
"jogDistance" : "02",
"runDistance" : "09",
"sprintDistance" : ""
}
]
}
)
My desired output looks as such:
[
{
"_id": null,
"uniqueValues": [
"03",
"01",
"08",
"02",
"09"
]
}
]
In order to do that, I've developed the following code:
db.activity.aggregate([
{
$facet: {
"walk": [
{$unwind: '$details'},
{$group: {_id: null, uniqueValues: {$addToSet: "$details.walkDistance"}}}
], "jog": [
{$unwind: '$details'},
{$group: {_id: null, uniqueValues: {$addToSet: "$details.jogDistance"}}}
], "run": [
{$unwind: '$details'},
{$group: {_id: null, uniqueValues: {$addToSet: "$details.runDistance"}}}
], "sprint": [
{$unwind: '$details'},
{$group: {_id: null, uniqueValues: {$addToSet: "$details.sprintDistance"}}}
]
}
}])
However, I am still getting 4 different facets with their own _id: null and uniqueValues array. How do I change the query so that they all included in a single array, and the "" is also excluded.

Answer 1

$facet really is not the best thing to use here. You should really just be applying $concatArrays and filtering down the result with $setDifference and $filter:
db.activity.aggregate([
{ "$project": {
"_id": 0,
"unique": {
"$filter": {
"input": {
"$setDifference": [
{ "$concatArrays": [
"$details.walkDistance",
"$details.jogDistance",
"$details.runDistance",
"$details.sprintDistance"
]},
[]
]
},
"cond": { "$ne": [ "$$this", "" ] }
}
}
}},
{ "$unwind": "$unique" },
{ "$group": {
"_id": null,
"uniqueArray": { "$addToSet": "$unique" }
}}
])
Returns the result:
/* 1 */
{
"_id" : null,
"uniqueArray" : [
"09",
"03",
"01",
"02",
"08"
]
}
So after bringing all the array values into a single array using $concatArrays, you apply $setDifference to reduce the list to the "unique" values. The $filter removes the "" values you don't want.
Then it's just a matter of applying $unwind on the singular and reduced list and bringing it back together in the $group with $addToSet to only keep unique values across documents.
You could also just $concatArrays only and then $unwind and $match, but the other operators don't really cost much and reduce some of the load by already narrowing down to "unique" within the document before you get to the $unwind. So it's better to do it that way.
Really this can even be broken down futher, to simply $setUnion and $setDifference since we are talking about "sets" afterall:
db.activity.aggregate([
{ "$project": {
"_id": 0,
"unique": {
"$setDifference": [
{ "$setUnion": [
"$details.walkDistance",
"$details.jogDistance",
"$details.runDistance",
"$details.sprintDistance"
]},
[""]
]
}
}},
{ "$unwind": "$unique" },
{ "$group": {
"_id": null,
"uniqueArray": { "$addToSet": "$unique" }
}}
])
And that means that the overall statement becomes compatible back to MongoDB 2.6, or would be if all the forms such as $details.walkDistance were written out in their longer form using $map:
"$setDifference": [
{ "$setUnion": [
{ "$map": { "input": "$details", "as": "d", "in": "$$d.walkDistance" } },
{ "$map": { "input": "$details", "as": "d", "in": "$$d.jogDistance" } },
{ "$map": { "input": "$details", "as": "d", "in": "$$d.runDistance" } },
{ "$map": { "input": "$details", "as": "d", "in": "$$d.sprintDistance" } }
]},
[""]
]
On the other hand running $facet causes a "brute force" parse through the whole collection for every property from within the array, and $unwind being processed on each of those passes. So it's a really inefficient way to obtain the result. So don't do it that way.