Conditional $sum in MongoDB - mongodb

Question

My collection in mongodb is similar to the following table in SQL:
Sentiments(Company,Sentiment)
Now, I need to execute a query like this:
SELECT
Company,
SUM(CASE WHEN Sentiment >0 THEN Sentiment ELSE 0 END) AS SumPosSenti,
SUM(CASE WHEN Sentiment <0 THEN Sentiment ELSE 0 END) AS SumNegSenti
FROM Sentiments
GROUP BY Company
What should I do to write this query in Mongo? I am stuck at the following query:
db.Sentiments.aggregate(
{ $project: {_id:0, Company:1, Sentiment: 1} },
{ $group: {_id: "$Company", SumPosSenti: {$sum: ? }, SumNegSenti: {$sum: ? } } }
);

Answer 1

As Sammaye suggested, you need to use the $cond aggregation projection operator to do this:
db.Sentiments.aggregate(
{ $project: {
_id: 0,
Company: 1,
PosSentiment: {$cond: [{$gt: ['$Sentiment', 0]}, '$Sentiment', 0]},
NegSentiment: {$cond: [{$lt: ['$Sentiment', 0]}, '$Sentiment', 0]}
}},
{ $group: {
_id: "$Company",
SumPosSentiment: {$sum: '$PosSentiment'},
SumNegSentiment: {$sum: '$NegSentiment'}
}});

Answer 2

Starting from version 3.4, we can use the $switch operator which allows logical condition processing in the $group stage. Of course we still need to use the $sum accumulator to return the sum.
db.Sentiments.aggregate(
[
{ "$group": {
"_id": "$Company",
"SumPosSenti": {
"$sum": {
"$switch": {
"branches": [
{
"case": { "$gt": [ "$Sentiment", 0 ] },
"then": "$Sentiment"
}
],
"default": 0
}
}
},
"SumNegSenti": {
"$sum": {
"$switch": {
"branches": [
{
"case": { "$lt": [ "$Sentiment", 0 ] },
"then": "$Sentiment"
}
],
"default": 0
}
}
}
}}
]
)
If you have not yet migrated your mongod to 3.4 or newer, then note that the $project stage in this answer is redundant because the $cond operator returns a numeric value which means that you can $group your documents and apply $sum to the $cond expression.
This will improve the performance in your application especially for large collection.
db.Sentiments.aggregate(
[
{ '$group': {
'_id': '$Company',
'PosSentiment': {
'$sum': {
'$cond': [
{ '$gt': ['$Sentiment', 0]},
'$Sentiment',
0
]
}
},
'NegSentiment': {
'$sum': {
'$cond': [
{ '$lt': ['$Sentiment', 0]},
'$Sentiment',
0
]
}
}
}}
]
)
Consider a collection Sentiments with the following documents:
{ "Company": "a", "Sentiment" : 2 }
{ "Company": "a", "Sentiment" : 3 }
{ "Company": "a", "Sentiment" : -1 }
{ "Company": "a", "Sentiment" : -5 }
The aggregation query produces:
{ "_id" : "a", "SumPosSenti" : 5, "SumNegSenti" : -6 }

Answer 3

Explaining the snippets above, that uses the array syntax:
PosSentiment: {$cond: [{$gt: ['$Sentiment', 0]}, '$Sentiment', 0]}
is equal to:
PosSentiment: {$cond: { if: {$gt: ['$Sentiment', 0]}, then: '$Sentiment', else: 0} }
The array syntax summarizes the long syntax to just { $cond: [if, then, else] }