I'm having trouble coming up with a good way to do a certain MongoDb query. First, here's what kind of query I want to do. Assume a simple database which logs entry and exit events (and possibly other actions, doesn't matter) by electronic card swipe. So there's a collection called swipelog
with simple documents which look like this:
{
_id: ObjectId("524ab4790a4c0e402200052c")
name: "John Doe",
action: "entry",
timestamp: ISODate("2013-10-01T1:32:12.112Z")
}
Now I want to list names and their last entry times (and any other fields I may want, but example below uses just these two fields).
Here is what I have now, as a "one-liner" for MongoDb JavaScript console:
db.swipelog.distinct('name')
.forEach( function(name) {
db.swipelog.find( { name: name, action:"entry" } )
.sort( { $natural:-1 } )
.limit(1)
.forEach( function(entry) {
printjson( [ entry.name, entry.timestamp ] )
})
})
Which prints something like:
[ "John Doe", ISODate("2013-10-01T1:32:12.112Z")]
[ "Jane Deo", ISODate("2013-10-01T1:36:12.112Z")]
...
I think above has the obvious scaling problem. If there are a hundred names, then 1+100 queries will be made to the database. So what is a good/correct way to get "last timestamp
of every distinct name
" ? Changing database structure or adding some collections is ok, if it makes this easier.
In MongoDB, the distinct() method finds the distinct values for a given field across a single collection and returns the results in an array. It takes three parameters first one is the field for which to return distinct values and the others are optional.
To get last inserted document, use sort() along with limit(1).
You can do this via aggregation framework in Compass, using $unwind and $group. The $unwind is performed to create a unique document for each element in the target array, which enables the $addToSet operator in the $group stage to then capture the genres as distinct elements.
What is Aggregation in MongoDB? Aggregation is a way of processing a large number of documents in a collection by means of passing them through different stages. The stages make up what is known as a pipeline. The stages in a pipeline can filter, sort, group, reshape and modify documents that pass through the pipeline.
You can use aggregation framework to achieve this:
db.collection.aggregate(
[
{$match:
{action:'entry'}
},
{$group:
{_id:'$name',
first:
{$max:'$timestamp'}
}
}
])
If you likely to include other fields in the results, you can use the $first operator
db.collection.aggregate(
[
{$match:
{action:'entry'}
},
{$sort:
{name:1, timestamp:-1}
},
{$group:
{_id:'$name',
timestamp: {$first:'$timestamp'},
otherField: {$first:'$otherField'},
}
}
])
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