A bit more modern than the original answer:
db.collection.aggregate([
{ "$sort": { "date": 1 } },
{ "$group": {
"_id": {
"$subtract": ["$date",{"$mod": ["$date",86400000]}]
},
"doc": { "$last": "$$ROOT" }
}},
{ "$replaceRoot": { "newDocument": "$doc" } }
])
The same principle applies that you essentially $sort
the collection and then $group
on the required grouping key picking up the $last
data from the grouping boundary.
Making things a bit clearer since the original writing is that you can use $$ROOT
instead of specifying every document property, and of course the $replaceRoot
stage allows you to restore that data fully as the original document form.
But the general solution is still $sort
first, then $group
on the common key that is required and keep the $last
or $first
depending on sort order occurrences from the grouping boundary for the properties that are required.
Also for BSON Dates as opposed to a timestamp value as in the question, see Group result by 15 minutes time interval in MongoDb for different approaches on how to accumulate for different time intervals actually using and returning BSON Date values.
Not quite sure what you are going for here but you could do this in aggregate if my understanding is right. So to get the last record for each day:
db.collection.aggregate([
// Sort in date order as ascending
{"$sort": { "date": 1 } },
// Date math converts to whole day
{"$project": {
"adco": 1,
"hchc": 1,
"hchp": 1,
"hhphc": 1,
"ptec": 1,
"iinst": 1,
"papp": 1,
"imax": 1,
"optarif": 1,
"isousc": 1,
"motdetat": 1,
"date": 1,
"wholeDay": {"$subtract": ["$date",{"$mod": ["$date",86400000]}]}
}},
// Group on wholeDay ( _id insertion is monotonic )
{"$group":
"_id": "$wholeDay",
"docId": {"$last": "$_id" },
"adco": {"$last": "$adco" },
"hchc": {"$last": "$hchc" },
"hchp": {"$last": "$hchp" },
"hhphc": {"$last": "$hhphc" },
"ptec": {"$last": "$ptec" },
"iinst": {"$last": "$iinst" },
"papp": {"$last": "$papp" },
"imax": {"$last": "$imax" },
"optarif": {"$last": "$optarif",
"isousc": {"$last": "$isouc" },
"motdetat": {"$last": "$motdetat" },
"date": {"$last": "$date" },
}}
])
So the principle here is that given the timestamp value, do the date math to project that as the midnight time at the beginning of each day. Then as the _id
key on the document is already monotonic (always increasing), then simply group on the wholeDay
value while pulling the $last
document from the grouping boundary.
If you don't need all the fields then only project and group on the ones you want.
And yes you can do this in the spring data framework. I'm sure there is a wrapped command in there. But otherwise, the incantation to get to the native command goes something like this:
mongoOps.getCollection("yourCollection").aggregate( ... )
For the record, if you actually had BSON date types rather than a timestamp as a number, then you can skip the date math:
db.collection.aggregate([
{ "$group": {
"_id": {
"year": { "$year": "$date" },
"month": { "$month": "$date" },
"day": { "$dayOfMonth": "$date" }
},
"hchp": { "$last": "$hchp" }
}}
])