I have a series of documents (check events) in MongoDB that look like this:
{
"_id" : ObjectId("5397a78ab87523acb46f56"),
"inspector_id" : ObjectId("5397997a02b8751dc5a5e8b1"),
"status" : 'defect',
"utc_timestamp" : ISODate("2014-06-11T00:49:14.109Z")
}
{
"_id" : ObjectId("5397a78ab87523acb46f57"),
"inspector_id" : ObjectId("5397997a02b8751dc5a5e8b2"),
"status" : 'ok',
"utc_timestamp" : ISODate("2014-06-11T00:49:14.109Z")
}
I need to get a result set that looks like this:
[
{
"date" : "2014-06-11",
"defect_rate" : '.92'
},
{
"date" : "2014-06-11",
"defect_rate" : '.84'
},
]
In other words, I need to get the average defect rate per day. Is this possible?
2 Answers
The aggregation framework is what you want:
db.collection.aggregate([
{ "$group": {
"_id": {
"year": { "$year": "$utc_timestamp" },
"month": { "$month": "$utc_timestamp" },
"day": { "$dayOfMonth": "$utc_timestamp" },
},
"defects": {
"$sum": { "$cond": [
{ "$eq": [ "$status", "defect" ] },
1,
0
]}
},
"totalCount": { "$sum": 1 }
}},
{ "$project": {
"defect_rate": {
"$cond": [
{ "$eq": [ "$defects", 0 ] },
0,
{ "$divide": [ "$defects", "$totalCount" ] }
]
}
}}
])
So first you group on the day using the date aggregation operators and get the totalCount of items on the given day. The use of the $cond operator here determines whether the "status" is actually a defect or not and the result is a conditional $sum where only the "defect" values are counted.
Once those are grouped per day you simply $divide the result, with another check with $cond to make sure you are not dividing by zero.
Would this be the best approach for the updated question?
$group : {
_id : '$symbol',
amount : {
$sum : '$amount'
},
value : {
$sum : '$value'
},
occurences : {
$sum : 1
},
in : {
$sum : {
$cond : [
{
$eq : [
'$direction',
'IN'
]
},
1,
0
]
}
},
out : {
$sum : {
$cond : [
{
$eq : [
'$direction',
'OUT'
]
},
1,
0
]
}
}
}
