Mongo 3.2 query timeseries value at specific time - mongodb

Question

I have some timeseries data stored in Mongo with one document per account, like so:
{
"account_number": 123,
"times": [
datetime(2017, 1, 2, 12, 34, 56),
datetime(2017, 3, 4, 17, 18, 19),
datetime(2017, 3, 11, 0, 1, 11),
]
"values": [
1,
10,
9001,
]
}
So, to be clear in the above representation account 123 has a value of 1 from 2017-01-02 12:34:56 until it changes to 10 on 2017-03-04 17:18:19, which then changes to 9001 at 2017-03-11, 00:01:11.
There are many accounts and each account's data is all different (could be at different times and could have more or fewer value changes than other accounts).
I'd like to query for each users value at a given time, e.g. "What was each users value at 2017-01-30 02:03:04? Would return 1 for the above account as it was set to 1 before the given time and did not change until after the given time.
It looks like $zip would be useful but thats only available in Mongo 3.4 and I'm using 3.2 and have no plans to upgrade soon.
Edit:
I can get a small part of the way there using:
> db.account_data.aggregate([{$unwind: '$times'}, {$unwind: '$values'}])
which returns something like:
{"account_number": 123, "times": datetime(2017, 1, 2, 12, 34, 56), "values": 1},
{"account_number": 123, "times": datetime(2017, 1, 2, 12, 34, 56), "values": 10},
#...
which isn't quite right as it is returning the cross product of times/values

Answer 1

This is possible using only 3.2 features. I tested with the Mingo library
var mingo = require('mingo')
var data = [{
"account_number": 123,
"times": [
new Date("2017-01-02T12:34:56"),
new Date("2017-03-04T17:18:19"),
new Date("2017-03-11T00:01:11")
],
"values": [1, 10, 9001]
}]
var maxDate = new Date("2017-01-30T02:03:04")
// 1. filter dates down to those less or equal to the maxDate
// 2. take the size of the filtered date array
// 3. subtract 1 from the size to get the index of the corresponding value
// 4. lookup the value by index in the "values" array into new "valueAtDate" field
// 5. project the extra fields
var result = mingo.aggregate(data, [{
$project: {
valueAtDate: {
$arrayElemAt: [
"$values",
{ $subtract: [ { $size: { $filter: { input: "$times", as: "time", cond: { $lte: [ "$$time", maxDate ] }} } }, 1 ] }
]
},
values: 1,
times: 1
}
}])
console.log(result)
// Outputs
[ { valueAtDate: 1,
values: [ 1, 10, 9001 ],
times:
[ 2017-01-02T12:34:56.000Z,
2017-03-04T17:18:19.000Z,
2017-03-11T00:01:11.000Z ] } ]

Answer 2

Not sure how to do the same with MongoDb 3.2, however from 3.4 you can do the following query:
db.test.aggregate([
{
$project:
{
index: { $indexOfArray: [ "$times", "2017,3,11,0,1,11" ] },
values: true
}
},
{
$project: {
resultValue: { $arrayElemAt: [ "$values", "$index" ] }
}
}])