MongoDB - 对范围查询进行排序和限制时未使用索引
MongoDB - Index not being used when sorting and limiting on ranged query
我正在尝试对包含公告板数据的集合使用范围查询来获取排序的项目列表。 "thread" 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，根据执行统计，它仍在扫描数百个 documents/keys：
{
"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，它只正确扫描了 25 个文档。无论我在排序函数中放置哪个字段，检查的键 (772) 都保持不变。
这是排序查询的完整 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
}
下面是未排序查询的完整 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
}
有谁知道为什么这可能没有完全使用索引？
我认为有 2 个问题都与您的类型有关。这些问题直接来自 documentations 但如果您愿意发表评论，我会帮助解释（并且我自己可能会学到一些东西）
第一个也是最大的问题是你必须按照索引给定的顺序排序。来自文档：
You can specify a sort on all the keys of the index or on a subset;
however, the sort keys must be listed in the same order as they appear
in the index. For example, an index key pattern { a: 1, b: 1 } can
support a sort on { a: 1, b: 1 } but not on { b: 1, a: 1 }.
这意味着您必须按照获胜计划给出的顺序排序：category, _id, sticky, lastPostAt（或该顺序的任何前缀，例如 category, _id, sticky 或 category _id）。如果不是，mongodb 将识别使用您的获胜计划编制索引的 772 个文档，但随后必须梳理每个键以评估值并提供所需的排序顺序。如果您想按当前查询的顺序排序，必须按该顺序提供索引：
第二个问题是您必须按照索引提供的方向（或相反方向）进行排序。
For a query to use a compound index for a sort, the specified sort
direction for all keys in the cursor.sort() document must match the
index key pattern or match the inverse of the index key pattern. For
example, an index key pattern { a: 1, b: -1 } can support a sort on {
a: 1, b: -1 } and { a: -1, b: 1 } but not on { a: -1, b: -1 } or {a:
1, b: 1}.
因为您的索引都是按升序排列的，所以您必须对所有索引按升序排序，或者对所有索引按降序排序。如果不是，我们 运行 会遇到同样的问题，其中 mongo 找到所有相关文档，但必须梳理它们以提供所需的顺序。
我相信您可以通过提供以下索引来获得改进的功能：
{ sticky: -1, lastPostAt: -1, _id: 1 }
或其倒数：
{ sticky: 1, lastPostAt: 1, _id: -1 }
这会导致 mongo 使用您的第一个索引
{ category: 1, _id: 1 }
为了识别潜在的未排序文档，然后使用新索引之一（上面提供），因为它们已经排序。那么这个限制将负责为您提供 25 个文档。
我很确定这会创建一个覆盖查询（一个没有检查文档的查询）。让我知道进展如何，干杯！
问题是您的 none 个索引实际上有助于排序查询。这就是大量扫描对象和存在 SORT_KEY_GENERATOR 阶段（内存排序，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是完全有效的，因为一个包含另一个的 prefix 。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 中提供了一篇关于如何创建索引的好文章。拿文章的重点来说，复合索引排序应该是equality --> sort --> range:
您的查询 "shape" 是：
db.collection.find({category:..., _id: {$gt:...}})
.sort({sticky:-1, lastPostAt:-1, _id:1})
.limit(25)
我们看到：
category:...等于相等sticky:-1, lastPostAt:-1, _id:1 是 排序_id: {$gt:...} 是 范围
所以你需要的复合索引是：
{category:1, sticky:-1, lastPostAt:-1, _id:1}
你的查询的 explain() 输出的获胜计划显示在上面的索引显示：
"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排序后的查询。
我正在尝试对包含公告板数据的集合使用范围查询来获取排序的项目列表。 "thread" 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，根据执行统计，它仍在扫描数百个 documents/keys：
{
"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，它只正确扫描了 25 个文档。无论我在排序函数中放置哪个字段，检查的键 (772) 都保持不变。
这是排序查询的完整 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
}
下面是未排序查询的完整 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
}
有谁知道为什么这可能没有完全使用索引？
我认为有 2 个问题都与您的类型有关。这些问题直接来自 documentations 但如果您愿意发表评论，我会帮助解释（并且我自己可能会学到一些东西）
第一个也是最大的问题是你必须按照索引给定的顺序排序。来自文档：
You can specify a sort on all the keys of the index or on a subset; however, the sort keys must be listed in the same order as they appear in the index. For example, an index key pattern { a: 1, b: 1 } can support a sort on { a: 1, b: 1 } but not on { b: 1, a: 1 }.
这意味着您必须按照获胜计划给出的顺序排序：category, _id, sticky, lastPostAt（或该顺序的任何前缀，例如 category, _id, sticky 或 category _id）。如果不是，mongodb 将识别使用您的获胜计划编制索引的 772 个文档，但随后必须梳理每个键以评估值并提供所需的排序顺序。如果您想按当前查询的顺序排序，必须按该顺序提供索引：
第二个问题是您必须按照索引提供的方向（或相反方向）进行排序。
For a query to use a compound index for a sort, the specified sort direction for all keys in the cursor.sort() document must match the index key pattern or match the inverse of the index key pattern. For example, an index key pattern { a: 1, b: -1 } can support a sort on { a: 1, b: -1 } and { a: -1, b: 1 } but not on { a: -1, b: -1 } or {a: 1, b: 1}.
因为您的索引都是按升序排列的，所以您必须对所有索引按升序排序，或者对所有索引按降序排序。如果不是，我们 运行 会遇到同样的问题，其中 mongo 找到所有相关文档，但必须梳理它们以提供所需的顺序。
我相信您可以通过提供以下索引来获得改进的功能：
{ sticky: -1, lastPostAt: -1, _id: 1 }
或其倒数：
{ sticky: 1, lastPostAt: 1, _id: -1 }
这会导致 mongo 使用您的第一个索引
{ category: 1, _id: 1 }
为了识别潜在的未排序文档，然后使用新索引之一（上面提供），因为它们已经排序。那么这个限制将负责为您提供 25 个文档。
我很确定这会创建一个覆盖查询（一个没有检查文档的查询）。让我知道进展如何，干杯！
问题是您的 none 个索引实际上有助于排序查询。这就是大量扫描对象和存在 SORT_KEY_GENERATOR 阶段（内存排序，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是完全有效的，因为一个包含另一个的 prefix 。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().
Optimizing MongoDB Compound Indexes 中提供了一篇关于如何创建索引的好文章。拿文章的重点来说，复合索引排序应该是equality --> sort --> range:
您的查询 "shape" 是：
db.collection.find({category:..., _id: {$gt:...}})
.sort({sticky:-1, lastPostAt:-1, _id:1})
.limit(25)
我们看到：
category:...等于相等sticky:-1, lastPostAt:-1, _id:1是 排序_id: {$gt:...}是 范围
所以你需要的复合索引是：
{category:1, sticky:-1, lastPostAt:-1, _id:1}
你的查询的 explain() 输出的获胜计划显示在上面的索引显示：
"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排序后的查询。