MongoDB - aggregate multiple fields in one query -

i'm developing monitoring system our company's production system. means nature of data i'll storing time-series. picked mongodb purpose, after reviewing several other databases. events production system arrive time, intend store events in 10-minute interval document. eventually, documents in collection this:

{    _id: '04/25/2015 13:00',    event1_count : 130,    event2_count : 50,    event3_count : 200 },  {     _id: '04/25/2015 13:10',     event1_count : 230,     event2_count : 20,     event3_count : 400 } 

the document _id: '04/25/2015 13:00' means has events arrived between 04/25/2015 13:00 , 04/25/2015 13:10.

ultimately, i'll want different reports run on data. example - count of events within last 20 minutes. result event count in last 20 minute is:

{ event1_count : 360, event2_count : 70, event3_count : 600 } 

my question - there way aggregate multiple fields different documents, in 1 query?

btw - it's important me keep data @ 10 minute interval, because other reports need time resolution.

yes it's indeed possible. suppose collection storing documents in above-mentioned structure, modify structure adding field date stores _id isodate, rather string timestamp can aggregation using date operators. conversion, can use mongo's foreach() cursor method atomic update $set operator:

db.collection.find().foreach(function (doc){     var dateobject = new date(doc._id);         db.collection.update({_id: doc._id}, { $set: { date: dateobject } });                }); 

the above create field date in documents contains isodate object representation of _id string.

suppose have following sample documents in collection after update above:

/* 0 */ {     "_id" : "04/25/2015 13:00",     "event1_count" : 130,     "event2_count" : 50,     "event3_count" : 200,     "date" : isodate("2015-04-25t13:00:00.000z") }  /* 1 */ {     "_id" : "04/25/2015 13:10",     "event1_count" : 230,     "event2_count" : 20,     "event3_count" : 400,     "date" : isodate("2015-04-25t13:10:00.000z") }  /* 2 */ {     "_id" : "04/25/2015 13:20",     "event1_count" : 240,     "event2_count" : 30,     "event3_count" : 350,     "date" : isodate("2015-04-25t13:20:00.000z") }  /* 3 */ {     "_id" : "04/25/2015 13:30",     "event1_count" : 180,     "event2_count" : 60,     "event3_count" : 500,     "date" : isodate("2015-04-25t13:30:00.000z") } 

the following aggregation pipeline give desired result, based on 20 minute interval:

var interval = 20,     pipeline = [     {          "$group": {             "_id": {                 "year": { "$year": "$date" },                 "dayofyear": { "$dayofyear": "$date" },                 "interval": {                     "$subtract": [                          { "$minute": "$date" },                         { "$mod": [{ "$minute": "$date" }, interval ] }                     ]                 }             },             "event1_count": { "$sum": "$event1_count" },             "event2_count": { "$sum": "$event2_count" },             "event3_count": { "$sum": "$event3_count" }         }     },     {         "$project": {             "_id": 0,             "event1_count": 1,             "event2_count": 1,             "event3_count": 1         }     } ];  db.collection.aggregate(pipeline); 

output:

/* 0 */ {     "result" : [          {             "event1_count" : 420,             "event2_count" : 90,             "event3_count" : 850         },          {             "event1_count" : 360,             "event2_count" : 70,             "event3_count" : 600         }     ],     "ok" : 1 }