MongoDB 2dsphere索引$ geoWithin性能

Question

我有一个包含GeoJSON Point形式坐标数据的集合,我需要从中查询区域内的10个最新条目.现在有1.000.000个条目,但是会有大约10倍的条目.

我的问题是,当所需区域内有大量条目时,我的查询性能会大幅下降(案例3).我当前拥有的测试数据是随机的,但实际数据不是,因此根据区域的尺寸选择另一个索引(如案例4)是不可能的.

无论区域如何,我应该怎么做才能让它以可预测的方式执行？

1.收集统计:

> db.randomcoordinates.stats()
{
    "ns" : "test.randomcoordinates",
    "count" : 1000000,
    "size" : 224000000,
    "avgObjSize" : 224,
    "storageSize" : 315006976,
    "numExtents" : 15,
    "nindexes" : 3,
    "lastExtentSize" : 84426752,
    "paddingFactor" : 1,
    "systemFlags" : 0,
    "userFlags" : 0,
    "totalIndexSize" : 120416128,
    "indexSizes" : {
        "_id_" : 32458720,
        "position_2dsphere_timestamp_-1" : 55629504,
        "timestamp_-1" : 32327904
    },
    "ok" : 1
}

2.指数:

> db.randomcoordinates.getIndexes()
[
    {
        "v" : 1,
        "key" : {
            "_id" : 1
        },
        "ns" : "test.randomcoordinates",
        "name" : "_id_"
    },
    {
        "v" : 1,
        "key" : {
            "position" : "2dsphere",
            "timestamp" : -1
        },
        "ns" : "test.randomcoordinates",
        "name" : "position_2dsphere_timestamp_-1"
    },
    {
        "v" : 1,
        "key" : {
            "timestamp" : -1
        },
        "ns" : "test.randomcoordinates",
        "name" : "timestamp_-1"
    }
]

3.使用2dsphere复合索引查找:

> db.randomcoordinates.find({position: {$geoWithin: {$geometry: {type: "Polygon", coordinates: [[[1, 1], [1, 90], [180, 90], [180, 1], [1, 1]]]}}}}).sort({timestamp: -1}).limit(10).hint("position_2dsphere_timestamp_-1").explain()
{
    "cursor" : "S2Cursor",
    "isMultiKey" : true,
    "n" : 10,
    "nscannedObjects" : 116775,
    "nscanned" : 283424,
    "nscannedObjectsAllPlans" : 116775,
    "nscannedAllPlans" : 283424,
    "scanAndOrder" : true,
    "indexOnly" : false,
    "nYields" : 4,
    "nChunkSkips" : 0,
    "millis" : 3876,
    "indexBounds" : {

    },
    "nscanned" : 283424,
    "matchTested" : NumberLong(166649),
    "geoTested" : NumberLong(166649),
    "cellsInCover" : NumberLong(14),
    "server" : "chan:27017"
}

4.使用时间戳索引查找:

> db.randomcoordinates.find({position: {$geoWithin: {$geometry: {type: "Polygon", coordinates: [[[1, 1], [1, 90], [180, 90], [180, 1], [1, 1]]]}}}}).sort({timestamp: -1}).limit(10).hint("timestamp_-1").explain()
{
    "cursor" : "BtreeCursor timestamp_-1",
    "isMultiKey" : false,
    "n" : 10,
    "nscannedObjects" : 63,
    "nscanned" : 63,
    "nscannedObjectsAllPlans" : 63,
    "nscannedAllPlans" : 63,
    "scanAndOrder" : false,
    "indexOnly" : false,
    "nYields" : 0,
    "nChunkSkips" : 0,
    "millis" : 0,
    "indexBounds" : {
        "timestamp" : [
            [
                {
                    "$maxElement" : 1
                },
                {
                    "$minElement" : 1
                }
            ]
        ]
    },
    "server" : "chan:27017"
}

有些人建议使用{timestamp: -1, position: "2dsphere"}索引,所以我也试过了,但它似乎表现不佳.

5.使用Timestamp + 2dsphere复合索引查找

> db.randomcoordinates.find({position: {$geoWithin: {$geometry: {type: "Polygon", coordinates: [[[1, 1], [1, 90], [180, 90], [180, 1], [1, 1]]]}}}}).sort({timestamp: -1}).limit(10).hint("timestamp_-1_position_2dsphere").explain()
{
    "cursor" : "S2Cursor",
    "isMultiKey" : true,
    "n" : 10,
    "nscannedObjects" : 116953,
    "nscanned" : 286513,
    "nscannedObjectsAllPlans" : 116953,
    "nscannedAllPlans" : 286513,
    "scanAndOrder" : true,
    "indexOnly" : false,
    "nYields" : 4,
    "nChunkSkips" : 0,
    "millis" : 4597,
    "indexBounds" : {

    },
    "nscanned" : 286513,
    "matchTested" : NumberLong(169560),
    "geoTested" : NumberLong(169560),
    "cellsInCover" : NumberLong(14),
    "server" : "chan:27017"
}

Answer 1

您是否尝试过在数据集上使用聚合框架？

您想要的查询类似于：

db.randomcoordinates.aggregate(
    { $match: {position: {$geoWithin: {$geometry: {type: "Polygon", coordinates: [[[1, 1], [1, 90], [180, 90], [180, 1], [1, 1]]]}}}}},
    { $sort: { timestamp: -1 } },
    { $limit: 10 }
);

不幸的是，聚合框架尚未explain进入生产版本，因此您只能知道它是否会产生巨大的时间差异。如果您可以从源代码构建，那么看起来它可能在上个月末就已经存在： https: //jira.mongodb.org/browse/SERVER-4504。它看起来也将出现在计划于下周二（2013 年 10 月 15 日）发布的 Dev 版本 2.5.3 中。