How to add count inside of MongoDB aggregation. My document in collection looks like this:
{
_id,
Sat,
calories,
carbs,
category,
fat,
fiber,
food,
grams,
measure,
protein,
sat.fat
}
I want to do query which will return all documents where "food" is like string and I want to project only fields which user select in frontend (for example, only "protein" and "carbs"). Also I want to add count field which will count found documents. So output should look something like this:
{
nutrientList: [
// here come all found projected documents
],
count: numberOfFOundDocs
}
I tried with, but it doesnt work:
const { macros, foodName, skip } = req.body;
// search word
var keywords = [
foodName,
foodName.toLocaleLowerCase(),
foodName.toLocaleUpperCase(),
foodName.toLowerCase(),
foodName.toUpperCase(),
],
regex = keywords.join("|");
Nutrient.aggregate([
{ $match: { food: { $regex: regex } } },
{
$project: {
protein: {
$cond: {
if: { $eq: [false, macros.protein] },
then: "$$REMOVE",
else: "$protein",
},
},
carbs: {
$cond: {
if: { $eq: [false, macros.carbohydrate] },
then: "$$REMOVE",
else: "$carbs",
},
},
fat: {
$cond: {
if: { $eq: [false, macros.fat] },
then: "$$REMOVE",
else: "$fat",
},
},
"sat.fat": {
$cond: {
if: { $eq: [false, macros.satFat] },
then: "$$REMOVE",
else: "$sat.fat",
},
},
fiber: {
$cond: {
if: { $eq: [false, macros.fiber] },
then: "$$REMOVE",
else: "$fiber",
},
},
calories: 1,
food: 1,
grams: 1,
measure: 1,
category: 1
},
},
{
$addFields: {
'totalCount': {$count: {}}
}
}
])
Related
In my code i am trying to collect the available filters however there are fields that were not
filled by the user and left as empty strings e.g the "brands" field. however, empty strings should not be considered as a valid value
this is my group stage:
{
$group: {
_id: null,
sizes: { $addToSet: '$combinations.size' },
colors: { $push: '$combinations.color' },
brands: { $addToSet: '$brand' },
topPrice: { $max: `$price.${req.query.reg || 'aud'}` },
bottomPrice: { $min: `$price.${req.query.reg || 'aud'}` },
},
},
the brands field will be:
[ "" ]
what i wanted is
[]
You can use conditional aggregating.
db.collection.aggregate([
{
$group: {
"_id": null,
"brands": {
"$addToSet": {
$cond: [
{$eq: ["$brand",""]}, //if brands is empty string,
"$$REMOVE", //then, REMOVE it
"$brand" //else, keep it
]
}
}
}
}
])
Demo
I'm trying to aggregate $sum between 2 dates stored as UTC strings (yyyy-mm-dd-hh). It takes 5+ seconds to get the results. My collection has 5 million+ docs.
{
$match: {
start: {
$gte: '2020-08-01-00',
$lte: '2021-08-01-00'
}
}
},
{
$group: {
_id: {
symbol: '$symbol'
},
unverifiedCount: {
$sum: {
$cond: {
if: { $eq: ['$isVerified', false] }, then: '$count', else: 0
}
}
},
verifiedCount: {
$sum: {
$cond: {
if: { $eq: ['$isVerified', true]}, then: '$count', else: 0
}
}
}
}
}, {
$sort: {
unverifiedCount: -1
}
}
Tried using $toDateString but performance remained the same
Background:
A customer is an object that has a name field.
A line is an object that has the following fields:
inLine - an array of customers
currentCustomer - a customer
processed - an array of customers
The collection 'line' contains documents that are line objects.
Problem:
I'm trying to implement a procedure which would do the following:
Push currentCustomer to processed
Set currentCustomer to the 1st element in inLine
Pop the 1st element of inLine
Since the new value of a field depends on the previous value of another, atomicity is important here.
What I tried so far:
Naive approach
db.collection('line').findOneAndUpdate({
_id: new ObjectId(lineId),
}, {
$set: {
currentCustomer: '$inLine.0',
},
$pop: {
inLine: -1,
},
$push: {
processed: '$currentCustomer',
},
});
However, currentCustomer is set to a string which is literally "$inLine.0" and processed has a string which is literally "$currentCustomer".
Aggregation approach
db.collection('line').findOneAndUpdate({
_id: new ObjectId(lineId),
}, [{
$set: {
currentCustomer: '$inLine.0',
},
$pop: {
inLine: -1,
},
$push: {
processed: '$currentCustomer',
},
}]);
However, I got the following error:
MongoError: A pipeline stage specification object must contain exactly one field.
Multi-stage aggregation approach
db.collection('line').findOneAndUpdate({
_id: new ObjectId(lineId),
}, [{
$set: {
currentCustomer: '$inLine.0',
},
}, {
$pop: {
inLine: -1,
},
}, {
$push: {
processed: '$currentCustomer',
},
}]);
However, $pop and $push are Unrecognized pipeline stage names.
I tried making it using only $set stages, but it ended up very ugly and I still couldn't get it to work.
Based on turivishal's answer, it was solved like so:
db.collection('line').findOneAndUpdate({
_id: new ObjectId(lineId),
}, [{
$set: {
// currentCustomer = inLine.length === 0 ? null : inLine[0]
currentCustomer: {
$cond: [
{ $eq: [{ $size: '$inLine' }, 0] },
null,
{ $first: '$inLine' },
],
},
// inLine = inLine.slice(1)
inLine: {
$cond: [
{ $eq: [{ $size: '$inLine' }, 0] },
[],
{ $slice: ['$inLine', 1, { $size: '$inLine' }] },
],
},
// if currentCustomer !== null then processed.push(currentCustomer)
processed: {
$cond: [
{
$eq: ['$currentCustomer', null],
},
'$processed',
{
$concatArrays: [
'$processed', ['$currentCustomer'],
],
}
],
},
},
}]);
I don't think its possible with simple update using $push or $pop.
As per your experiment, the aggregation can not support direct $push, $pop stage in root level, so I have corrected your query,
currentCustomer check condition if size of inLine is 0 then return null otherwise get first element from inLine array using $arrayElemAt,
inLine check condition if size of inLine is 0 then return [] otherwise remove first element from inLine array using $slice and $size
processed concat both arrays using $concatArrays, $ifNull to check if field is null then return blank array, check condition if currentCustomer null then return [] otherwise return currentCustomer
db.collection('line').findOneAndUpdate(
{ _id: new ObjectId(lineId), },
[{
$set: {
currentCustomer: {
$cond: [
{ $eq: [{ $size: "$inLine" }, 0] },
null,
{ $arrayElemAt: ["$inLine", 0] }
]
},
inLine: {
$cond: [
{ $eq: [{ $size: "$inLine" }, 0] },
[],
{ $slice: ["$inLine", 1, { $size: "$inLine" }] }
]
},
processed: {
$concatArrays: [
{ $ifNull: ["$processed", []] },
{
$cond: [
{ $eq: ["$currentCustomer", null] },
[],
["$currentCustomer"]
]
}
]
}
}
}]
);
Playground
I am writing an aggregation pipeline to return a win ratio. When I use $sum the value is output from $facet $project within an array. This has me confused. To solve the issue I simply run $sum on the arrays when I calculate the winRatio, which works fine. How do I use $project without it adding values into an array?
Round.aggregate([
{
$match: {
$and: query,
},
},
{
$facet: {
wins: [
{
$match: {
winner: user,
},
},
{
$group: {
_id: { user: '$scores.player', game: '$game' },
value: { $sum: 1 }, // value *not* within array
},
},
],
rounds: [
{
$unwind: '$scores',
},
{
$match: {
'scores.player': user,
},
},
{
$group: {
_id: { user: '$scores.player', game: '$game' },
value: { $sum: 1 }, // value *not* within array
},
},
],
},
},
{
$project: {
_id: '$rounds._id',
rounds: '$rounds.value', // value within an array
wins: '$wins.value', // value within an array
winRatio: { ... },
},
},
]);
Schema:
const schema = new mongoose.Schema(
{
game: { type: mongoose.Schema.ObjectId, required: true },
scores: [
{
player: { type: mongoose.Schema.ObjectId, ref: 'User', required: true },
playerName: { type: String }, // denormalise
score: { type: Number, required: true },
},
],
winner: { type: mongoose.Schema.ObjectId, required: true },
datePlayed: { type: Date },
},
{ timestamps: true },
);
Your asking why $sum 'works' and $project dosent.
Lets start off by understand the output of the $facet phase.
{
"wins" : [
{
"_id" : {
"user" : [
"player1",
"player2"
],
"game" : 1.0
},
"value" : 2.0
}
],
"rounds" : [
{
"_id" : {
"user" : "player1",
"game" : 1.0
},
"value" : 3.0
}
]
}
As we can see each document result is an array, even though you grouped at the end, imagine each result as its own aggregation, that return value is always an array (either empty or not depending on results).
so when you $project on $rounds.value you're telling mongo to keep the value field for each of the results in the array. in our case its only one but still.
$sum on the other hand is an accumulative operator, from the docs:
With a single expression as its operand, if the expression resolves to an array, $sum traverses into the array to operate on the numerical elements of the array to return a single value.
a quick fix to your 'issue' is just to add $sum while projecting:
{
$project: {
_id: '$rounds._id',
rounds: {$sum: '$rounds.value'},
wins: {$sum: '$wins.value'},
winRatio: { ... },
},
},
how to make a mongodb collection find (db.collection.find) with empty values?
currently i have:
function test(s) {
if (!s) {
return null;
} else {
return s;
}
}
var content = {
date: {
from: '2017-10-15',
to: '2017-11-15'
},
'name': 'some text', //this can be null or empty
'text': 'some other text' //this can be null or empty
}
col.find({
"date": {
$gte: new Date(content.date.from),
$lte: new Date(content.date.to)
},
"name": {
$ne: {
$type: null
},
$eq: test(content.name)
},
"text": {
$ne: {
$type: null
},
$eq: test(content.text)
},
}).toArray((err, items) => {
console.log(items)
});
but it returns an empty array, because "name" or "text" is null / an empty string,
i want that it query only the values that have something specified or ignore it (like content.name is something in it or its empty)
how do i get it? i already searched ... but didnt found something
thanks!
( already testet mongoDB : multi value field search ignoring null fields)
Versions:
Node: 8.9.0
(npm) mongodb: 2.2.33
mongodb: 3.4
Try using $and, $or operators. Something like.
col.find({
$and:[
{"date": {$gte: new Date(content.date.from),$lte: new Date(content.date.to)}},
{"$or":[{"name": {$ne: {$type: null}}},{"name":test(content.name)}]},
{"$or":[{"text": {$ne: {$type: null}}},{"text":test(content.text)}]}
]
}).toArray((err, items) => {
console.log(items)
});
col.find({
$and: [
{
$and: [
{
"date": {
$gte: new Date(content.date.from)
}
},
{
"date": {
$lte: new Date(content.date.to)
}
},
]
},
{
$or: [
{ 'name': null },
{ 'name': content.name }
]
},
{
$or: [
{ 'text': null },
{ 'text': content.text }
]
}
]
})
Edited:
col.find({
$and: [
{
$and: [
{
"date": {
$gte: new Date(content.date.from)
}
},
{
"date": {
$lte: new Date(content.date.to)
}
},
]
},
{
$or: [
{ 'name': null },
{ 'name':'' }
{ 'name': content.name }
]
},
{
$or: [
{ 'text': null },
{ 'text': '' },
{ 'text': content.text }
]
}
]
})
null and empty is different, you need to add one more condition for empty string in query.
Logical Query Operators