I have the following structure in the database:
{
"_id" : {
"user" : 14197,
"date" : ISODate("2014-10-24T00:00:00.000Z")
},
...
}
I have a performance problem when I try to select data by user & date-range. Monogo doesn't use index & runs full-scan over collection.
db.timeuse.daily.find({ "_id.user": 289006, "_id.date" : {$gt: ISODate("2014-10-23T00:00:00Z"), $lte: ISODate("2014-10-30T00:00:00Z")}}).explain()
{
"cursor" : "BasicCursor",
"isMultiKey" : false,
"n" : 6,
"nscannedObjects" : 66967,
"nscanned" : 66967,
"nscannedObjectsAllPlans" : 66967,
"nscannedAllPlans" : 66967,
"scanAndOrder" : false,
"indexOnly" : false,
"nYields" : 523,
"nChunkSkips" : 0,
"millis" : 1392,
"server" : "mongo-shard0003:27018",
"filterSet" : false,
"stats" : {
"type" : "COLLSCAN",
"works" : 66969,
"yields" : 523,
"unyields" : 523,
"invalidates" : 16,
"advanced" : 6,
"needTime" : 66962,
"needFetch" : 0,
"isEOF" : 1,
"docsTested" : 66967,
"children" : [ ]
},
"millis" : 1392
}
So far I found only one way - use $in.
db.timeuse.daily.find({"_id": { $in: [
{"user": 289006, "date": ISODate("2014-10-23T00:00:00Z")},
{"user": 289006, "date": ISODate("2014-10-24T00:00:00Z")}
]}}).explain()
{
"cursor" : "BtreeCursor _id_",
"isMultiKey" : false,
"n" : 2,
"nscannedObjects" : 2,
"nscanned" : 2,
"nscannedObjectsAllPlans" : 2,
"nscannedAllPlans" : 2,
"scanAndOrder" : false,
"indexOnly" : false,
"nYields" : 0,
"nChunkSkips" : 0,
"millis" : 0,
"indexBounds" : {
"_id" : [
[
{
"user" : 289006,
"date" : ISODate("2014-10-23T00:00:00Z")
},
{
"user" : 289006,
"date" : ISODate("2014-10-23T00:00:00Z")
}
],
[
{
"user" : 289006,
"date" : ISODate("2014-10-24T00:00:00Z")
},
{
"user" : 289006,
"date" : ISODate("2014-10-24T00:00:00Z")
}
]
]
},
If there's a more elegant way to run this kind of query?