Is there a way to retrieve documents from MongoDB by performing a calculation on two items stored in an array within each document?
Specifically, I am interested in fetching all documents where the last item in an array is lower than the second-to-last item in that same array.
Could someone guide me towards the relevant documentation for achieving this in MongoDB?
Any tips or suggestions would be highly valued. Thank you!
For the most optimal operation in modern MongoDB versions (3.2 and higher), utilizing $redact is recommended as it allows for a "logical filter" based on specified conditions, paired with $arrayElemAt to extract single values from an array.
Consider the following example:
{ "_id": 1, "data": [1,2,3] },
{ "_id": 2, "data": [3,2,1] }
The corresponding query would be:
db.collection.aggregate([
{ "$redact": {
"$cond": {
"if": {
"$lt": [
{ "$arrayElemAt": [ "$data", -1 ] },
{ "$arrayElemAt": [ "$data", -2 ] }
]
},
"then": "$$KEEP",
"else": "$$PRUNE"
}
}}
])
In cases where the document includes sub-document properties within the array elements, $map can be applied to extract desired property values for comparison. Additionally, $let aids in avoiding repetition of expressions.
Another illustration:
{
"_id": 1,
"data": [
{ "name": "c", "value": 1 },
{ "name": "b", "value": 2 },
{ "name": "a", "value": 3 }
]
},
{
"_id": 2,
"data": [
{ "name": "a", "value": 3 },
{ "name": "b", "value": 2 },
{ "name": "c", "value": 1 }
]
}
And the respective query:
db.collection.aggregate([
{ "$redact": {
"$cond": {
"if": {
"$let": {
"vars": {
"data": {
"$map": {
"input": "$data",
"as": "el",
"in": "$$el.value"
}
}
},
"in": {
"$lt": [
{ "$arrayElemAt": [ "$$data", -1 ] },
{ "$arrayElemAt": [ "$$data", -2 ] }
]
}
}
},
"then": "$$KEEP",
"else": "$$PRUNE"
}
}}
])
Ensuring extraction of the "property" value plays a crucial role here due to potential discrepancies when comparing Object values directly against other array elements.
While $where remains available for older MongoDB versions or alternate approaches, it involves JavaScript evaluation which impacts performance compared to using native aggregation framework operators.
Prior versions may still support achieving this through the aggregation framework, but such methods are discouraged due to lower efficiency. It typically entails manipulating array elements to derive comparisons between subsequent items, resulting in increased processing time:
db.collection.aggregate([
// Unwind array
{ "$unwind": "$data" },
// Group back and get $last
{ "$group": {
"_id": "$_id",
"data": { "$push": "$data" },
"lastData": { "$last" "$data" }
}},
// Unwind again
{ "$unwind": "$data" },
// Compare to mark the last element
{ "$project": {
"data": 1,
"lastData": 1,
"seen": { "$eq": [ "$lastData", "$data" ] }
}},
// Filter the previous $last from the list
{ "$match": { "seen": false } },
// Group back and compare values
{ "$group": {
"_id": "$_id",
"data": { "$push": "$data" },
"lastData": { "$last": "$lastData" },
"secondLastData": { "$last": "$data" },
"greater": {
"$last": { "$lt": [ "$data.value", "$lastData.value" ] }
}
}},
// Filter to return only true
{ "$match": { "greater": true } }
])
Conversely, employing $where proves cleaner and more efficient for scenarios involving earlier MongoDB versions that necessitate further aggregation operations post-condition matching.
Hence, transitioning to recent MongoDB releases and leveraging $redact along with logical comparisons in a singular pipeline stage yields enhanced performance by minimizing processing stages.
If you have MongoDB 3.2, the aggregation framework can be utilized to retrieve IDs of documents that match specific criteria. Once you have these IDs, you can then process them as needed.
For instance:
db.collection.aggregate([
{$project:{
cond :{$cond:[{
$gt:[{
$slice:["$v", -2,1]
}, {
$slice:["$v", -1,1]
}]
}, true, false]
}}
},
{$match:{cond: true}}
])
In my collection, I have the following documents:
{
"_id" : ObjectId("57094622b08be16cf12fcf6f"),
"v" : [
1.0,
2.0,
3.0,
4.0,
8.0,
7.0
]
}
{
"_id" : ObjectId("5709462bb08be16cf12fcf70"),
"v" : [
1.0,
2.0,
3.0,
4.0,
8.0,
10.0
]
}
Based on your specified conditions, you are looking to select a document where the last element in the array is less than the second-to-last element. Therefore, it should identify the document with
_id = ObjectId("57094622b08be16cf12fcf6f")The result of running the aggregation query will show:
{
"_id" : ObjectId("57094622b08be16cf12fcf6f"),
"cond" : true
}
This outcome aligns with what we expected.
As mentioned earlier, you can iterate through the retrieved information and carry out any necessary actions, such as fetching the complete document.
Note: If your document is straightforward, projecting fields may eliminate the need for cursor iteration to fetch the complete document. However, in this example, I am assuming the document is complex and lacks upfront information about its properties or attributes.
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