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I have collection that contains documents with below schema. I want to filter/find all documents that contain the gender female and aggregate the sum of brainscore. I tried the below statement and it shows a invalid pipeline error.
db['!all'].aggregate({ $and: [ {'GENDER' : 'F'} , {'DOB' : { $gte : 19400801, $lte : 20131231 }} ] }, { $group : { _id : "$GENDER", totalscore : { $sum : "$BRAINSCORE" } } } ) Schema:
{ "_id" : ObjectId("53f63fc8f2b643f6ebb8a1a9"), "DOB" : 19690112, "GENDER" : "F", "BRAINSCORE" : 65 }, { "_id" : ObjectId("53f63fc8f2b643f6ebb8a1a2"), "DOB" : 19950116, "GENDER" : "F", "BRAINSCORE" : 44 }, { "_id" : ObjectId("53f63fc8f2b643f6ebb8a902"), "DOB" : 19430216, "GENDER" : "M", "BRAINSCORE" : 71 } 
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To create an aggregation pipeline, you can use can use MongoDB's aggregate() method. This method uses a syntax that is fairly similar to the find() method used to query data in a collection, but aggregate() accepts one or more stage names as arguments. This step focuses on how to use the $match aggregation stage.
With aggregate + $match, you get a big monolithic BSON containing all matching documents. With find, you get a cursor to all matching documents. Then you can get each document one by one.
Aggregations operations process data records and return computed results. Aggregation operations group values from multiple documents together, and can perform a variety of operations on the grouped data to return a single result. In SQL count(*) and with group by is an equivalent of MongoDB aggregation.
Without seeing your data and your query it is difficult to answer why aggregate+sort is faster than find+sort. A well indexed(Indexing that suits your query) data will always yield faster results on your find query.
You have to use $match:
db['!all'].aggregate([ {$match: {'GENDER': 'F', 'DOB': { $gte: 19400801, $lte: 20131231 } } }, {$group: {_id: "$GENDER", totalscore:{ $sum: "$BRAINSCORE"}}} ]) Outputs:
{ "_id" : "F", "totalscore" : 109 } Sample working query :
db.getCollection('NOTIF_EVENT_RESULT').aggregate([ {$match: {'userId': {'$in' : ['user-900', 'user-1546']}, 'criteria.operator': 'greater than', 'criteria.thresold' : '90', 'category' : 'capacity'} }, {"$group" : {_id : {userId:"$userId"}, "count" : { "$sum" : 1} } } ]) If you love us? You can donate to us via Paypal or buy me a coffee so we can maintain and grow! Thank you!
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