Add a field with increasing value in MongoDB Aggregation based on condition - mongodb

Question

Sample of my collection :
[
{
_id: "bmasndvhjbcw",
name: "lucas",
occupation: "scientist",
age: 55,
location: "texas",
joining_date: 2019-01-01T15:24:15.068+00:00
},
{
_id: "bmasndvhjbcx",
name: "mark",
occupation: "scientist",
age: 45,
location: "texas",
joining_date: 2019-01-01T15:24:15.068+00:00
},
{
_id: "bmasndvhjbca",
name: "stuart",
occupation: "lab assistant",
age: 25,
location: "texas",
joining_date: 2019-01-02T20:25:16.068+00:00
},
{
_id: "bmasndvhjbcq",
name: "cooper",
occupation: "physicist",
age: 69,
location: "texas"
}
]
Which ever docs has joining_date column need to add a field with increasing value by checking the date like joining_date_count:1
if the dates are same like in two cases mark and lucas . count should consider it as different values and increase the count.
Expected Output :
[
{
_id: "bmasndvhjbcw",
name: "lucas",
occupation: "scientist",
age: 55,
location: "texas",
joining_date: 2019-01-01T15:24:15.068+00:00,
joining_date_count:1
},
{
_id: "bmasndvhjbcx",
name: "mark",
occupation: "scientist",
age: 45,
location: "texas",
joining_date: 2019-01-01T15:24:15.068+00:00,
joining_date_count:2
},
{
_id: "bmasndvhjbca",
name: "stuart",
occupation: "lab assistant",
age: 25,
location: "texas",
joining_date: 2019-01-02T20:25:16.068+00:00,
joining_date_count:3
},
{
_id: "bmasndvhjbcq",
name: "cooper",
occupation: "physicist",
age: 69,
location: "texas"
}
]

Answer 1

This aggregation adds a field with a counter:
db.collection.aggregate( [
{
$match: {
joining_date: { $exists: true }
}
},
{
$group: {
_id: null,
docs: { $push: "$$ROOT" }
}
},
{
$project: {
_id: 0,
R: {
$map: {
input: { $range: [ 0, { $size: "$docs" } ] },
in: {
$mergeObjects: [
{ joining_date_count: { $add: [ "$$this", 1 ] } },
{ $arrayElemAt: [ "$docs", "$$this" ] }
]
}
}
}
}
},
{
$unwind: "$R"
},
{
$replaceRoot: { newRoot: "$R" }
}
] )

Answer 2

You can try below query :
db.collection.aggregate([
/** Sort on joining_date field which will arrange docs with missing field at top & ascending where field exists */
{
$sort: {
joining_date: 1
}
},
/** group on empty & push every doc in collection to an array field named data */
{
$group: {
_id: "",
data: {
$push: "$$ROOT"
}
}
},
/** split data array into two array one has doc which doesn't field & other has docs which does have field */
{
$addFields: {
data: {
$reduce: {
input: "$data",
initialValue: {
missingField: [],
fieldExists: []
},
in: {
missingField: {
$cond: [
{
"$ifNull": [
"$$this.joining_date",
false
]
},
"$$value.missingField",
{
$concatArrays: [
"$$value.missingField",
[
"$$this"
]
]
}
]
},
fieldExists: {
$cond: [
{
"$ifNull": [
"$$this.joining_date",
false
]
},
{
$concatArrays: [
"$$value.fieldExists",
[
"$$this"
]
]
},
"$$value.fieldExists"
]
}
}
}
}
}
},
/** Add new field 'joining_date_count' to docs based on that doc index in fieldExists array &
* finally concatinate missingField with newly formed fieldExists array */
{
$addFields: {
"data": {
$concatArrays: [
"$data.missingField",
{
$map: {
input: "$data.fieldExists",
in: {
$mergeObjects: [
"$$this",
{
joining_date_count: {
$add: [
1,
{
$indexOfArray: [
"$data.fieldExists",
"$$this"
]
}
]
}
}
]
}
}
}
]
}
}
},
/** unwind data array */
{
$unwind: "$data"
},
/** replace each docs root as data field */
{
$replaceRoot: {
newRoot: "$data"
}
}
])
Test : MongoDB-Playground