我正在尝试使用包含公告板数据的集合上的远程查询来获取已排序的项目列表。 “线程”文档的数据结构是:
{
"_id" : ObjectId("5a779b47f4fa72412126526a"),
"title" : "necessitatibus tincidunt libris assueverit",
"content" : "Corrumpitvenenatis cubilia adipiscing sollicitudin",
"flagged" : false,
"locked" : false,
"sticky" : false,
"lastPostAt" : ISODate("2018-02-05T06:35:24.656Z"),
"postCount" : 42,
"user" : ObjectId("5a779b46f4fa72412126525a"),
"category" : ObjectId("5a779b31f4fa724121265164"),
"createdAt" : ISODate("2018-02-04T23:46:15.852Z"),
"updatedAt" : ISODate("2018-02-05T06:35:24.656Z")
}
查询是:
db.threads.find({
category: ObjectId('5a779b31f4fa724121265142'),
_id : { $gt: ObjectId('5a779b5cf4fa724121269be8') }
}).sort({ sticky: -1, lastPostAt: -1, _id: 1 }).limit(25)
我设置了以下索引来支持它:
{ category: 1, _id: 1 }
{ category: 1, _id: 1, sticky: 1, lastPostAt: 1 }
{ sticky: 1, lastPostAt: 1, _id: 1 }
尽管如此,它仍然根据执行统计数据扫描数百个文件/密钥:
{
"executionStats" : {
"executionSuccess" : true,
"nReturned" : 772,
"executionTimeMillis" : 17,
"totalKeysExamined" : 772,
"totalDocsExamined" : 772,
"executionStages" : {
"stage" : "SORT",
"nReturned" : 772,
"executionTimeMillisEstimate" : 0,
"works" : 1547,
"advanced" : 772,
"needTime" : 774,
"needYield" : 0,
"saveState" : 33,
"restoreState" : 33,
"isEOF" : 1,
"invalidates" : 0,
"sortPattern" : {
"sticky" : -1,
"lastPostAt" : -1,
"_id" : 1
},
"memUsage" : 1482601,
"memLimit" : 33554432,
"inputStage" : {
"stage" : "SORT_KEY_GENERATOR",
"nReturned" : 772,
"executionTimeMillisEstimate" : 0,
"works" : 774,
"advanced" : 772,
"needTime" : 1,
"needYield" : 0,
"saveState" : 33,
"restoreState" : 33,
"isEOF" : 1,
"invalidates" : 0,
"inputStage" : {
"stage" : "FETCH",
"nReturned" : 772,
"executionTimeMillisEstimate" : 0,
"works" : 773,
"advanced" : 772,
"needTime" : 0,
"needYield" : 0,
"saveState" : 33,
"restoreState" : 33,
"isEOF" : 1,
"invalidates" : 0,
"docsExamined" : 772,
"alreadyHasObj" : 0,
"inputStage" : {
"stage" : "IXSCAN",
"nReturned" : 772,
"executionTimeMillisEstimate" : 0,
"works" : 773,
"advanced" : 772,
"needTime" : 0,
"needYield" : 0,
"saveState" : 33,
"restoreState" : 33,
"isEOF" : 1,
"invalidates" : 0,
"keyPattern" : {
"category" : 1,
"_id" : 1,
"sticky" : 1,
"lastPostAt" : 1
},
"indexName" : "category_1__id_1_sticky_1_lastPostAt_1",
"isMultiKey" : false,
"multiKeyPaths" : {
"category" : [ ],
"_id" : [ ],
"sticky" : [ ],
"lastPostAt" : [ ]
},
"isUnique" : false,
"isSparse" : false,
"isPartial" : false,
"indexVersion" : 2,
"direction" : "forward",
"indexBounds" : {
"category" : [
"[ObjectId('5a779b31f4fa724121265142'), ObjectId('5a779b31f4fa724121265142')]"
],
"_id" : [
"(ObjectId('5a779b5cf4fa724121269be8'), ObjectId('ffffffffffffffffffffffff')]"
],
"sticky" : [
"[MinKey, MaxKey]"
],
"lastPostAt" : [
"[MinKey, MaxKey]"
]
},
"keysExamined" : 772,
"seeks" : 1,
"dupsTested" : 0,
"dupsDropped" : 0,
"seenInvalidated" : 0
}
}
}
}
}
当我取出排序阶段时,它只能正确扫描25个文档。无论我在sort函数中放置哪个字段,检查的键(772)都保持不变。
以下是已排序查询的完整explain()
:
{
"queryPlanner" : {
"plannerVersion" : 1,
"namespace" : "database.threads",
"indexFilterSet" : false,
"parsedQuery" : {
"$and" : [
{
"category" : {
"$eq" : ObjectId("5a779b31f4fa724121265142")
}
},
{
"_id" : {
"$gt" : ObjectId("5a779b5cf4fa724121269be8")
}
}
]
},
"winningPlan" : {
"stage" : "SORT",
"sortPattern" : {
"sticky" : -1,
"lastPostAt" : -1,
"_id" : 1
},
"limitAmount" : 25,
"inputStage" : {
"stage" : "SORT_KEY_GENERATOR",
"inputStage" : {
"stage" : "FETCH",
"inputStage" : {
"stage" : "IXSCAN",
"keyPattern" : {
"category" : 1,
"_id" : 1,
"sticky" : 1,
"lastPostAt" : 1
},
"indexName" : "category_1__id_1_sticky_1_lastPostAt_1",
"isMultiKey" : false,
"multiKeyPaths" : {
"category" : [ ],
"_id" : [ ],
"sticky" : [ ],
"lastPostAt" : [ ]
},
"isUnique" : false,
"isSparse" : false,
"isPartial" : false,
"indexVersion" : 2,
"direction" : "forward",
"indexBounds" : {
"category" : [
"[ObjectId('5a779b31f4fa724121265142'), ObjectId('5a779b31f4fa724121265142')]"
],
"_id" : [
"(ObjectId('5a779b5cf4fa724121269be8'), ObjectId('ffffffffffffffffffffffff')]"
],
"sticky" : [
"[MinKey, MaxKey]"
],
"lastPostAt" : [
"[MinKey, MaxKey]"
]
}
}
}
}
},
"rejectedPlans" : [
{
"stage" : "SORT",
"sortPattern" : {
"sticky" : -1,
"lastPostAt" : -1,
"_id" : 1
},
"limitAmount" : 25,
"inputStage" : {
"stage" : "SORT_KEY_GENERATOR",
"inputStage" : {
"stage" : "FETCH",
"filter" : {
"_id" : {
"$gt" : ObjectId("5a779b5cf4fa724121269be8")
}
},
"inputStage" : {
"stage" : "IXSCAN",
"keyPattern" : {
"category" : 1
},
"indexName" : "category_1",
"isMultiKey" : false,
"multiKeyPaths" : {
"category" : [ ]
},
"isUnique" : false,
"isSparse" : false,
"isPartial" : false,
"indexVersion" : 2,
"direction" : "forward",
"indexBounds" : {
"category" : [
"[ObjectId('5a779b31f4fa724121265142'), ObjectId('5a779b31f4fa724121265142')]"
]
}
}
}
}
},
{
"stage" : "SORT",
"sortPattern" : {
"sticky" : -1,
"lastPostAt" : -1,
"_id" : 1
},
"limitAmount" : 25,
"inputStage" : {
"stage" : "SORT_KEY_GENERATOR",
"inputStage" : {
"stage" : "FETCH",
"inputStage" : {
"stage" : "IXSCAN",
"keyPattern" : {
"category" : 1,
"_id" : 1
},
"indexName" : "category_1__id_1",
"isMultiKey" : false,
"multiKeyPaths" : {
"category" : [ ],
"_id" : [ ]
},
"isUnique" : false,
"isSparse" : false,
"isPartial" : false,
"indexVersion" : 2,
"direction" : "forward",
"indexBounds" : {
"category" : [
"[ObjectId('5a779b31f4fa724121265142'), ObjectId('5a779b31f4fa724121265142')]"
],
"_id" : [
"(ObjectId('5a779b5cf4fa724121269be8'), ObjectId('ffffffffffffffffffffffff')]"
]
}
}
}
}
},
{
"stage" : "SORT",
"sortPattern" : {
"sticky" : -1,
"lastPostAt" : -1,
"_id" : 1
},
"limitAmount" : 25,
"inputStage" : {
"stage" : "SORT_KEY_GENERATOR",
"inputStage" : {
"stage" : "FETCH",
"filter" : {
"category" : {
"$eq" : ObjectId("5a779b31f4fa724121265142")
}
},
"inputStage" : {
"stage" : "IXSCAN",
"keyPattern" : {
"_id" : 1
},
"indexName" : "_id_",
"isMultiKey" : false,
"multiKeyPaths" : {
"_id" : [ ]
},
"isUnique" : true,
"isSparse" : false,
"isPartial" : false,
"indexVersion" : 2,
"direction" : "forward",
"indexBounds" : {
"_id" : [
"(ObjectId('5a779b5cf4fa724121269be8'), ObjectId('ffffffffffffffffffffffff')]"
]
}
}
}
}
}
]
},
"serverInfo" : {
"host" : "CRF-MBP.local",
"port" : 27017,
"version" : "3.6.2",
"gitVersion" : "489d177dbd0f0420a8ca04d39fd78d0a2c539420"
},
"ok" : 1
}
以下是非排序查询的完整explain()
:
{
"queryPlanner" : {
"plannerVersion" : 1,
"namespace" : "database.threads",
"indexFilterSet" : false,
"parsedQuery" : {
"$and" : [
{
"category" : {
"$eq" : ObjectId("5a779b31f4fa724121265142")
}
},
{
"_id" : {
"$gt" : ObjectId("5a779b5cf4fa724121269be8")
}
}
]
},
"winningPlan" : {
"stage" : "LIMIT",
"limitAmount" : 25,
"inputStage" : {
"stage" : "FETCH",
"inputStage" : {
"stage" : "IXSCAN",
"keyPattern" : {
"category" : 1,
"_id" : 1,
"sticky" : 1,
"lastPostAt" : 1
},
"indexName" : "category_1__id_1_sticky_1_lastPostAt_1",
"isMultiKey" : false,
"multiKeyPaths" : {
"category" : [ ],
"_id" : [ ],
"sticky" : [ ],
"lastPostAt" : [ ]
},
"isUnique" : false,
"isSparse" : false,
"isPartial" : false,
"indexVersion" : 2,
"direction" : "forward",
"indexBounds" : {
"category" : [
"[ObjectId('5a779b31f4fa724121265142'), ObjectId('5a779b31f4fa724121265142')]"
],
"_id" : [
"(ObjectId('5a779b5cf4fa724121269be8'), ObjectId('ffffffffffffffffffffffff')]"
],
"sticky" : [
"[MinKey, MaxKey]"
],
"lastPostAt" : [
"[MinKey, MaxKey]"
]
}
}
}
},
"rejectedPlans" : [
{
"stage" : "LIMIT",
"limitAmount" : 25,
"inputStage" : {
"stage" : "FETCH",
"filter" : {
"_id" : {
"$gt" : ObjectId("5a779b5cf4fa724121269be8")
}
},
"inputStage" : {
"stage" : "IXSCAN",
"keyPattern" : {
"category" : 1
},
"indexName" : "category_1",
"isMultiKey" : false,
"multiKeyPaths" : {
"category" : [ ]
},
"isUnique" : false,
"isSparse" : false,
"isPartial" : false,
"indexVersion" : 2,
"direction" : "forward",
"indexBounds" : {
"category" : [
"[ObjectId('5a779b31f4fa724121265142'), ObjectId('5a779b31f4fa724121265142')]"
]
}
}
}
},
{
"stage" : "LIMIT",
"limitAmount" : 25,
"inputStage" : {
"stage" : "FETCH",
"inputStage" : {
"stage" : "IXSCAN",
"keyPattern" : {
"category" : 1,
"_id" : 1
},
"indexName" : "category_1__id_1",
"isMultiKey" : false,
"multiKeyPaths" : {
"category" : [ ],
"_id" : [ ]
},
"isUnique" : false,
"isSparse" : false,
"isPartial" : false,
"indexVersion" : 2,
"direction" : "forward",
"indexBounds" : {
"category" : [
"[ObjectId('5a779b31f4fa724121265142'), ObjectId('5a779b31f4fa724121265142')]"
],
"_id" : [
"(ObjectId('5a779b5cf4fa724121269be8'), ObjectId('ffffffffffffffffffffffff')]"
]
}
}
}
},
{
"stage" : "LIMIT",
"limitAmount" : 25,
"inputStage" : {
"stage" : "FETCH",
"filter" : {
"category" : {
"$eq" : ObjectId("5a779b31f4fa724121265142")
}
},
"inputStage" : {
"stage" : "IXSCAN",
"keyPattern" : {
"_id" : 1
},
"indexName" : "_id_",
"isMultiKey" : false,
"multiKeyPaths" : {
"_id" : [ ]
},
"isUnique" : true,
"isSparse" : false,
"isPartial" : false,
"indexVersion" : 2,
"direction" : "forward",
"indexBounds" : {
"_id" : [
"(ObjectId('5a779b5cf4fa724121269be8'), ObjectId('ffffffffffffffffffffffff')]"
]
}
}
}
}
]
},
"serverInfo" : {
"host" : "CRF-MBP.local",
"port" : 27017,
"version" : "3.6.2",
"gitVersion" : "489d177dbd0f0420a8ca04d39fd78d0a2c539420"
},
"ok" : 1
}
有没有人知道为什么这可能无法完全使用索引?
答案 0 :(得分:2)
问题是您的索引实际上没有帮助排序查询。这就是扫描对象数量较多且存在SORT_KEY_GENERATOR
阶段(内存中排序,限制为32MB)的原因。
另一方面,非排序查询可以使用{ category: 1, _id: 1 }
或{ category: 1, _id: 1, sticky: 1, lastPostAt: 1 }
索引。请注意,使用其中任何一个都非常有效,因为其中一个包含另一个的前缀。有关详细信息,请参阅Prefixes。
MongoDB find()
查询通常只使用一个索引,因此单个compound index应该满足查询的所有参数。这将包括find()
和sort()
的参数。
Optimizing MongoDB Compound Indexes中提供了有关如何创建索引的详细说明。让我们来看一篇文章的主要观点,其中复合索引排序应该是相等 - >排序 - >范围强>:
您的查询"形状"是:
db.collection.find({category:..., _id: {$gt:...}})
.sort({sticky:-1, lastPostAt:-1, _id:1})
.limit(25)
我们看到了:
category:...
平等 sticky:-1, lastPostAt:-1, _id:1
排序 _id: {$gt:...}
范围 所以你需要的复合索引是:
{category:1, sticky:-1, lastPostAt:-1, _id:1}
具有上述索引的查询的explain()
输出的获胜计划显示:
"winningPlan": {
"stage": "LIMIT",
"limitAmount": 25,
"inputStage": {
"stage": "FETCH",
"inputStage": {
"stage": "IXSCAN",
"keyPattern": {
"category": 1,
"sticky": -1,
"lastPostAt": -1,
"_id": 1
},
"indexName": "category_1_sticky_-1_lastPostAt_-1__id_1",
"isMultiKey": false,
"multiKeyPaths": {
"category": [ ],
"sticky": [ ],
"lastPostAt": [ ],
"_id": [ ]
},
"isUnique": false,
"isSparse": false,
"isPartial": false,
"indexVersion": 2,
"direction": "forward",
"indexBounds": {
"category": [
"[ObjectId('5a779b31f4fa724121265142'), ObjectId('5a779b31f4fa724121265142')]"
],
"sticky": [
"[MaxKey, MinKey]"
],
"lastPostAt": [
"[MaxKey, MinKey]"
],
"_id": [
"(ObjectId('5a779b5cf4fa724121269be8'), ObjectId('ffffffffffffffffffffffff')]"
]
}
}
}
}
请注意,获胜计划不包含SORT_KEY_GENERATOR
阶段。这意味着可以充分利用索引来响应已排序的查询。
答案 1 :(得分:1)
我相信有2个问题都与你的排序有关。这些问题直接来自documentations,但如果你发表评论我会帮助解释(并且可能会自己学习一些东西)
第一个也是最大的问题是你必须按照索引给出的顺序排序。来自docs:
您可以对索引的所有键或子集指定排序; 但是,排序键必须按它们出现的顺序列出 在索引中。例如,索引键模式{a:1,b:1}可以 支持对{a:1,b:1}进行排序,但不对{b:1,a:1}进行排序。
这意味着您必须按照获胜计划给出的顺序排序:category, _id, sticky, lastPostAt
(或该订单的任何前缀,例如category, _id, sticky
或category _id
)。如果不是mongodb将识别使用您的获胜计划索引的772文档,但是必须梳理每个密钥以评估值并提供所需的排序顺序。如果您想按顺序排序,那么查询必须按顺序提供索引:
第二个问题是您必须按索引(或反方向)提供的方向排序。
对于使用复合索引进行排序的查询,指定的排序 cursor.sort()文档中所有键的方向必须与 索引键模式或匹配索引键模式的反转。对于 例如,索引键模式{a:1,b:-1}可以支持{ a:1,b:-1}和{a:-1,b:1}但不在{a:-1,b:-1}或{a: 1,b:1}。
由于索引都是按升序排列的,因此您必须按升序对所有索引进行排序,或者按降序排序所有索引。如果不是,我们遇到了mongo找到所有相关文档的相同问题,但必须梳理它们以提供所需的顺序。
我相信你会通过提供额外的索引来获得改进的功能:
{ sticky: -1, lastPostAt: -1, _id: 1 }
或其反过来:
{ sticky: 1, lastPostAt: 1, _id: -1 }
这会产生mongo使用你的第一个索引的情况
{ category: 1, _id: 1 }
要识别潜在的未排序文档,然后使用新索引之一(上面提供),因为它们已经被排序。然后限制将照顾给你25个文档。
我很确定这会创建一个覆盖查询(没有检查过文档的查询)。让我知道它是怎么回事,干杯!