MongoDB Aggregation to get events in timespan, plus the previous event - mongodb

Question

I have timeseries data as events coming in at random times. They are not ongoing metrics, but rather events. "This device went online." "This device went offline."
I need to report on the number of actual transitions within a time range. Because there are occasionally same-state events, for example two "went online" events in a row, I need to "seed" the data with the state previous to the time range. If I have events in my time range, I need to compare them to the state before the time range in order to determine if something actually changed.
I already have aggregation stages that remove same-state events.
Is there a way to add "the latest, previous event" to the data in the pipeline without writing two queries? A $facet stage totally ruins performance.
For "previous", I'm currently trying something like this in a separate query, but it's very slow on the millions of records:
// Get the latest event before a given date
db.devicemetrics.aggregate([
{
$match: {
'device.someMetadata': '70b28808-da2b-4623-ad83-6cba3b20b774',
time: {
$lt: ISODate('2023-01-18T07:00:00.000Z'),
},
someValue: { $ne: null },
},
},
{
$group: {
_id: '$device._id',
lastEvent: { $last: '$$ROOT' },
},
},
{
$replaceRoot: { newRoot: '$lastEvent' },
}
]);

Answer 1

You are looking for something akin to LAG window function in SQL. Mongo has $setWindowFields for this, combined with $shift Order operator.
Not sure about fields in your collection, but this should give you an idea.
{
$setWindowFields: {
partitionBy: "$device._id", //1. partition the data based on $device._id
sortBy: { time: 1 }, //2. within each partition, sort based on $time
output: {
"shiftedEvent": { //3. add a new field shiftedEvent to each document
$shift: {
output: "$event", //4. whose value is previous $event
by: -1
}
}
}
}
}
Then, you can compare the event and shiftedEvent fields.