I have the following collection in mongoDB
{ _id, startTime, duration }
So the basic idea is that a camera looks out for people and once it detects a person it saves the startTime and once a person disappears it saves the duration. So the entity basically says "A person appeared at X time and was in the camera range for Y milliseconds". Both startTime and duration are numeric values.
So, I want to perform various queries like: 1. Give me the number of people per month/year 2. Give me the number of people per month with duration > 5000ms
etc.
I'm fairly new to MongoDB though and I have a bit of trouble with the aggregation framework, so I would appreciate if someone gives me an idea of how to do a query such as the above, in order to get some sort of head start.
EDIT:
Ok I have done a couple of tries but no luck. Right now my objects have this form:
{
"_id" : ObjectId("52de407c75895eaf5ea99715"),
"startTime" : "new Date('02 01 2011 08:36:54')",
"duration" : 27000
}
and I'm trying this query:
db.collection.aggregate(
{$project : {
year : {$year : "$startTime"}
}},
{$group : {
_id : {year : "$year"},
count : {$sum : 1}
}}
)
but I'm getting the following exception:
Error occurred in performing aggregation
Command 'aggregate' failed: exception: can't convert from BSON type String to Date (response: { "errmsg" : "exception: can't convert from BSON type String to Date", "code" : 16006, "ok" : 0.0 })
Type: MongoDB.Driver.MongoCommandException
Stack: at MongoDB.Driver.Operations.CommandOperation`1.Execute(MongoConnection connection)
at MongoDB.Driver.MongoCollection.RunCommandAs[TCommandResult](IMongoCommand command, IBsonSerializer resultSerializer, IBsonSerializationOptions resultSerializationOptions)
at MongoDB.Driver.MongoCollection.RunCommandAs[TCommandResult](IMongoCommand command)
at MongoDB.Driver.MongoCollection.Aggregate(IEnumerable`1 operations)
at MangoUI.ComAggregate.kRemove_Click(Object sender, EventArgs e)
Inputs::
Command: aggregate
Ok: False
ErrorMsg: exception: can't convert from BSON type String to Date
Request: { "aggregate" : "person", "pipeline" : [{ "$project" : { "year" : { "$year" : "$startTime" } } }, { "$group" : { "_id" : { "year" : "$year" }, "count" : { "$sum" : 1 } } }] }
Response: { "errmsg" : "exception: can't convert from BSON type String to Date", "code" : 16006, "ok" : 0.0 }
You can do them with Aggregation Framework.
Give me the number of people per month/year
db.collection.aggregate(
{$project : {
year : {$year : "$startTime"},
month : {$month : "$startTime"}
}},
{$group : {
_id : {year : "$year", month : "$month"},
count : {$sum : 1}
}}
)
Give me the number of people per month with duration > 5000ms
db.collection.aggregate(
{$project : {
year : {$year : "$startTime"},
month : {$month : "$startTime"},
duration: {$cond: [{$gt: ['$duration', 5000]}, 1, 0]}
}},
{$group : {
_id : {year : "$year",month : "$month"},
duration : {$sum : "$duration"}
}}
)
For more information check Aggregation Framework.
Please refer to compatible data format of MongoDB at http://docs.mongodb.org/manual/reference/bson-types/#document-bson-type-date
And below is the way to test to aggreagations.
rs1:PRIMARY>
rs1:PRIMARY> db.dbversitycol.insert({ "_id" : "1", "LastUpdatedOn" : new Date() , "company" : "microsoft" })
rs1:PRIMARY> db.dbversitycol.insert({ "_id" : "2", "LastUpdatedOn" : new Date() , "company" : "google" })
rs1:PRIMARY> db.dbversitycol.insert({ "_id" : "3", "LastUpdatedOn" : new Date() , "company" : "ibm" })
rs1:PRIMARY> db.dbversitycol.insert({ "_id" : "4", "LastUpdatedOn" : new Date() , "company" : "cisco" })
rs1:PRIMARY> db.dbversitycol.insert({ "_id" : "5", "LastUpdatedOn" : new Date() , "company" : "dbversity.com" })
rs1:PRIMARY>
rs1:PRIMARY> db.dbversitycol.find()
{ "_id" : "1", "LastUpdatedOn" : ISODate("2014-11-28T13:09:13.203Z"), "company" : "microsoft" }
{ "_id" : "2", "LastUpdatedOn" : ISODate("2014-11-28T13:09:13.207Z"), "company" : "google" }
{ "_id" : "3", "LastUpdatedOn" : ISODate("2014-11-28T13:09:13.210Z"), "company" : "ibm" }
{ "_id" : "4", "LastUpdatedOn" : ISODate("2014-11-28T13:09:13.213Z"), "company" : "cisco" }
{ "_id" : "5", "LastUpdatedOn" : ISODate("2014-11-28T13:09:14.035Z"), "company" : "dbversity.com" }
rs1:PRIMARY>
rs1:PRIMARY>
rs1:PRIMARY> db.dbversitycol.aggregate(
... {
... "$project" :
... {
... _id : 0,
... "datePartDay" : {"$concat" : [
... {"$substr" : [{"$dayOfMonth" : "$LastUpdatedOn"}, 0, 2]}, "-",
... {"$substr" : [{"$month" : "$LastUpdatedOn"}, 0, 2]}, "-",
... {"$substr" : [{"$year" : "$LastUpdatedOn"}, 0, 4]}
... ] }
... }
... },
... { "$group" :
... { "_id" : "$datePartDay", "Count" : { "$sum" : 1 } }
... }
... )
{ "result" : [ { "_id" : "28-11-2014", "Count" : 5 } ], "ok" : 1 }
rs1:PRIMARY>
rs1:PRIMARY>
rs1:PRIMARY> db.dbversitycol.aggregate(
... {$project : {
... year : {$year : "$LastUpdatedOn"},
... month : {$month : "$LastUpdatedOn"}
... }},
... {$group : {
... _id : {year : "$year", month : "$month"},
... count : {$sum : 1}
... }}
... )
{
"result" : [
{
"_id" : {
"year" : 2014,
"month" : 11
},
"count" : 5
}
],
"ok" : 1
}
rs1:PRIMARY>
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