A data set of time series data needs to be turned from one with irregular time intervals to a regular time series, probably using interpolation and and resampling.
Python's pandas.Dataframe.resample
is a function that will do this. Can Javascript do the same? The time series data set is stored in Mongodb.
It is kind of possible. Keep in mind that Pandas is a library built explicitly for those kind of tasks, and a beast at it, while MongoDB is meant to be a database. But chances are high that the following will suit your needs, if one ignores your probable need for using interpolation:
Assuming that you have the following data stored in a MongoDB collection named devices
/* 0 */
{
"_id" : ObjectId("543fc08ccf1e8c06c0288802"),
"t" : ISODate("2014-10-20T14:56:44.097+02:00"),
"a" : "192.168.0.16",
"i" : 0,
"o" : 32
}
/* 1 */
{
"_id" : ObjectId("543fc08ccf1e8c06c0288803"),
"t" : ISODate("2014-10-20T14:56:59.107+02:00"),
"a" : "192.168.0.16",
"i" : 14243,
"o" : 8430
}
and so on...
which, in this case, is sampled at around every 15 seconds, but it could as well be irregularly. If you want to resample it to a 5 minute boundary for a certain day, then you should do the following:
var low = ISODate("2014-10-23T00:00:00.000+02:00")
var high = ISODate("2014-10-24T00:00:00.000+02:00")
var interval = 5*60*1000;
db.devices.aggregate([
{$match: {t:{$gte: low, $lt: high}, a:"192.168.0.16"}},
{$group: {
_id:{
$subtract: ["$t", {
$mod: [{
$subtract: ["$t", low]
}, interval]
}]
},
total: {$sum: 1},
incoming: {$sum: "$i"},
outgoing: {$sum: "$o"},
}
},
{
$project: {
total: true,
incoming: true,
outgoing: true,
incoming_avg: {$divide: ["$incoming", "$total"]},
outgoing_avg: {$divide: ["$outgoing", "$total"]},
},
},
{$sort: {_id : 1}}
])
This will result in something like this
{
"result" : [
{
"_id" : ISODate("2014-10-23T07:25:00.000+02:00"),
"total" : 8,
"incoming" : 11039108,
"outgoing" : 404983,
"incoming_avg" : 1379888.5,
"outgoing_avg" : 50622.875
},
{
"_id" : ISODate("2014-10-23T07:30:00.000+02:00"),
"total" : 19,
"incoming" : 187241,
"outgoing" : 239912,
"incoming_avg" : 9854.78947368421,
"outgoing_avg" : 12626.94736842105
},
{
"_id" : ISODate("2014-10-23T07:35:00.000+02:00"),
"total" : 17,
"incoming" : 22420099,
"outgoing" : 1018766,
"incoming_avg" : 1318829.352941176,
"outgoing_avg" : 59927.41176470588
},
...
If you want to discard the total incoming, then just leave the line out in the $project stage. The incoming_average is just an example of how to compute the average, in case your stored data is something like what rrdtool names a gauge (temperature, cpu, sensor data). If you're only after the sum aggregated in that time inverval, that is the incoming and outgoing field, then you can leave the entire $project stage out. It is only there to compute the average of the time interval.
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