I have a MongoDB collection named post
with 35 million objects. The collection has two secondary indexes defined as follows.
> db.post.getIndexKeys()
[
{
"_id" : 1
},
{
"namespace" : 1,
"domain" : 1,
"post_id" : 1
},
{
"namespace" : 1,
"post_time" : 1,
"tags" : 1 // this is an array field
}
]
I expect the following query, which simply filters by namespace
and post_time
, to run in a reasonable time without scanning all objects.
>db.post.find({post_time: {"$gte" : ISODate("2013-04-09T00:00:00Z"), "$lt" : ISODate("2013-04-09T01:00:00Z")}, namespace: "my_namespace"}).count()
7408
However, it takes MongoDB at least ten minutes to retrieve the result and, curiously, it manages to scan 70 million objects to do the job according to the explain
function.
> db.post.find({post_time: {"$gte" : ISODate("2013-04-09T00:00:00Z"), "$lt" : ISODate("2013-04-09T01:00:00Z")}, namespace: "my_namespace"}).explain()
{
"cursor" : "BtreeCursor namespace_1_post_time_1_tags_1",
"isMultiKey" : true,
"n" : 7408,
"nscannedObjects" : 69999186,
"nscanned" : 69999186,
"nscannedObjectsAllPlans" : 69999186,
"nscannedAllPlans" : 69999186,
"scanAndOrder" : false,
"indexOnly" : false,
"nYields" : 378967,
"nChunkSkips" : 0,
"millis" : 290048,
"indexBounds" : {
"namespace" : [
[
"my_namespace",
"my_namespace"
]
],
"post_time" : [
[
ISODate("2013-04-09T00:00:00Z"),
ISODate("292278995-01--2147483647T07:12:56.808Z")
]
],
"tags" : [
[
{
"$minElement" : 1
},
{
"$maxElement" : 1
}
]
]
},
"server" : "localhost:27017"
}
The difference between the number of objects and the number of scans must be caused by the lengths of the tag arrays (which are all equal to 2). Still, I don't understand why post_time
filter does not make use of the index.
Can you tell me what I might be missing?
(I am working on a descent machine with 24 cores and 96 GB RAM. I am using MongoDB 2.2.3.)