嵌套对象的Mongodb索引

Question

我在该模式中的文章中有文档：

    {
    "schedule":  {
        "day_of_week": {
            "0": {"hour": {"3": [60], "6": [45, 60], "9": [60]}},
            "2": {"hour": {"2": [60], "3": [45, 60], "5": [60]}},
            "3": {"hour": {"1": [15, 45], "4": [30], "5": [60], "6": [30, 60], "7": [45]}},
            "6": {"hour": {"1": [30], "2": [15, 45, 60], "5": [30], "9": [15, 45]}}
        }
    }
   }

我有查询要查找这些文件：

db.my_coll.find({"schedule.day_of_week.0.hour.3":60})

我应该创建哪些索引来优化我的查询？

我已经创建了这些索引：

[
    {
            "v" : 1,
            "key" : {
                    "_id" : 1
            },
            "name" : "_id_",
            "ns" : "db.my_coll"
    },
    {
            "v" : 1,
            "key" : {
                    "schedule.day_of_week.0.hour" : 1
            },
            "name" : "schedule.day_of_week.0.hour_1",
            "ns" : "db.my_coll"
    },
    {
            "v" : 1,
            "key" : {
                    "schedule.day_of_week.0" : 1
            },
            "name" : "schedule.day_of_week.0_1",
            "ns" : "db.my_coll"
    },
    {
            "v" : 1,
            "key" : {
                    "schedule.day_of_week" : 1
            },
            "name" : "schedule.day_of_week_1",
            "ns" : "db.my_coll"
    },
    {
            "v" : 1,
            "key" : {
                    "schedule" : 1
            },
            "name" : "schedule_1",
            "ns" : "db.my_coll"
    }

但它没有任何效果，查询仍在使用COLLSCAN而不使用索引。

db.my_coll.explain（1）.find的输出（{＆＃34; schedule.day_of_week.0.hour.3＆＃34;：60}）

{
    "cursor" : "BasicCursor",
    "isMultiKey" : false,
    "n" : 2,
    "nscannedObjects" : 64,
    "nscanned" : 64,
    "nscannedObjectsAllPlans" : 64,
    "nscannedAllPlans" : 64,
    "scanAndOrder" : false,
    "indexOnly" : false,
    "nYields" : 0,
    "nChunkSkips" : 0,
    "millis" : 0,
    "allPlans" : [
            {
                    "cursor" : "BasicCursor",
                    "isMultiKey" : false,
                    "n" : 2,
                    "nscannedObjects" : 64,
                    "nscanned" : 64,
                    "scanAndOrder" : false,
                    "indexOnly" : false,
                    "nChunkSkips" : 0
            }
    ],
    "server" : "server:27017",
    "filterSet" : false,
    "stats" : {
            "type" : "COLLSCAN",
            "works" : 66,
            "yields" : 0,
            "unyields" : 0,
            "invalidates" : 0,
            "advanced" : 2,
            "needTime" : 63,
            "needFetch" : 0,
            "isEOF" : 1,
            "docsTested" : 64,
            "children" : [ ]
    }

}

收集64份文件