Mongo 带过滤器的日期范围索引
Mongo date range index with filters
我们有以下查询
db.Comment.find(
{
$and: [
{ reportCount: { $gt: 0 } },
{ assignee: { $exists: false } },
{ creationDate: { $gt: new Date(1507831097809) } },
{ creationDate: { $lt: new Date(1508522297966) } },
{ siteId: 'MAIN' },
{ parent: { $exists: false } },
{ status: 'ACTIVE' }
]
})
.sort({ creationDate: 1 })
我们有一个索引
{
"v" : 2,
"key" : {
"creationDate" : 1,
"reportCount" : 1,
"label" : 1
}
}
这是 explain 个结果：
{
"queryPlanner" : {
"plannerVersion" : 1,
"namespace" : "myNameSpace",
"indexFilterSet" : false,
"parsedQuery" : {
"$and" : [
{
"siteId" : {
"$eq" : "MAIN"
}
},
{
"status" : {
"$eq" : "ACTIVE"
}
},
{
"creationDate" : {
"$lt" : ISODate("2017-10-20T17:58:17.966Z")
}
},
{
"creationDate" : {
"$gt" : ISODate("2017-10-12T17:58:17.809Z")
}
},
{
"reportCount" : {
"$gt" : 0.0
}
},
{
"$nor" : [
{
"assignee" : {
"$exists" : true
}
}
]
},
{
"$nor" : [
{
"parent" : {
"$exists" : true
}
}
]
}
]
},
"winningPlan" : {
"stage" : "FETCH",
"filter" : {
"$and" : [
{
"siteId" : {
"$eq" : "MAIN"
}
},
{
"status" : {
"$eq" : "ACTIVE"
}
},
{
"$nor" : [
{
"assignee" : {
"$exists" : true
}
}
]
},
{
"$nor" : [
{
"parent" : {
"$exists" : true
}
}
]
}
]
},
"inputStage" : {
"stage" : "IXSCAN",
"keyPattern" : {
"creationDate" : 1.0,
"reportCount" : 1.0,
"label" : 1.0
},
"indexName" : "creationDate_1_reportCount_1_label_1",
"isMultiKey" : false,
"multiKeyPaths" : {
"creationDate" : [],
"reportCount" : [],
"label" : []
},
"isUnique" : false,
"isSparse" : false,
"isPartial" : false,
"indexVersion" : 2,
"direction" : "forward",
"indexBounds" : {
"creationDate" : [
"(new Date(1507831097809), new Date(1508522297966))"
],
"reportCount" : [
"(0.0, inf.0]"
],
"label" : [
"[MinKey, MaxKey]"
]
}
}
},
"rejectedPlans" : [
{
"stage" : "SORT",
"sortPattern" : {
"creationDate" : 1.0
},
"inputStage" : {
"stage" : "SORT_KEY_GENERATOR",
"inputStage" : {
"stage" : "FETCH",
"filter" : {
"$and" : [
{
"$nor" : [
{
"parent" : {
"$exists" : true
}
}
]
},
{
"siteId" : {
"$eq" : "MAIN"
}
},
{
"status" : {
"$eq" : "ACTIVE"
}
},
{
"creationDate" : {
"$lt" : ISODate("2017-10-20T17:58:17.966Z")
}
},
{
"creationDate" : {
"$gt" : ISODate("2017-10-12T17:58:17.809Z")
}
},
{
"reportCount" : {
"$gt" : 0.0
}
},
{
"$nor" : [
{
"assignee" : {
"$exists" : true
}
}
]
}
]
},
"inputStage" : {
"stage" : "IXSCAN",
"keyPattern" : {
"parent" : 1.0
},
"indexName" : "parent_1",
"isMultiKey" : false,
"multiKeyPaths" : {
"parent" : []
},
"isUnique" : false,
"isSparse" : false,
"isPartial" : false,
"indexVersion" : 2,
"direction" : "forward",
"indexBounds" : {
"parent" : [
"[null, null]"
]
}
}
}
}
},
{
"stage" : "SORT",
"sortPattern" : {
"creationDate" : 1.0
},
"inputStage" : {
"stage" : "SORT_KEY_GENERATOR",
"inputStage" : {
"stage" : "FETCH",
"filter" : {
"$and" : [
{
"$nor" : [
{
"assignee" : {
"$exists" : true
}
}
]
},
{
"siteId" : {
"$eq" : "MAIN"
}
},
{
"status" : {
"$eq" : "ACTIVE"
}
},
{
"creationDate" : {
"$lt" : ISODate("2017-10-20T17:58:17.966Z")
}
},
{
"creationDate" : {
"$gt" : ISODate("2017-10-12T17:58:17.809Z")
}
},
{
"reportCount" : {
"$gt" : 0.0
}
},
{
"$nor" : [
{
"parent" : {
"$exists" : true
}
}
]
}
]
},
"inputStage" : {
"stage" : "IXSCAN",
"keyPattern" : {
"assignee" : 1.0
},
"indexName" : "assignee_1",
"isMultiKey" : false,
"multiKeyPaths" : {
"assignee" : []
},
"isUnique" : false,
"isSparse" : false,
"isPartial" : false,
"indexVersion" : 2,
"direction" : "forward",
"indexBounds" : {
"assignee" : [
"[null, null]"
]
}
}
}
}
},
{
"stage" : "SORT",
"sortPattern" : {
"creationDate" : 1.0
},
"inputStage" : {
"stage" : "SORT_KEY_GENERATOR",
"inputStage" : {
"stage" : "FETCH",
"filter" : {
"$and" : [
{
"status" : {
"$eq" : "ACTIVE"
}
},
{
"creationDate" : {
"$lt" : ISODate("2017-10-20T17:58:17.966Z")
}
},
{
"creationDate" : {
"$gt" : ISODate("2017-10-12T17:58:17.809Z")
}
},
{
"reportCount" : {
"$gt" : 0.0
}
},
{
"$nor" : [
{
"assignee" : {
"$exists" : true
}
}
]
},
{
"$nor" : [
{
"parent" : {
"$exists" : true
}
}
]
}
]
},
"inputStage" : {
"stage" : "IXSCAN",
"keyPattern" : {
"siteId" : 1.0,
"updatedDate" : 1.0,
"label" : 1.0
},
"indexName" : "siteId_1_updatedDate_1_label_1",
"isMultiKey" : false,
"multiKeyPaths" : {
"siteId" : [],
"updatedDate" : [],
"label" : []
},
"isUnique" : false,
"isSparse" : false,
"isPartial" : false,
"indexVersion" : 2,
"direction" : "forward",
"indexBounds" : {
"siteId" : [
"[\"MAIN\", \"MAIN\"]"
],
"updatedDate" : [
"[MinKey, MaxKey]"
],
"label" : [
"[MinKey, MaxKey]"
]
}
}
}
}
},
{
"stage" : "SORT",
"sortPattern" : {
"creationDate" : 1.0
},
"inputStage" : {
"stage" : "SORT_KEY_GENERATOR",
"inputStage" : {
"stage" : "FETCH",
"filter" : {
"$and" : [
{
"$nor" : [
{
"parent" : {
"$exists" : true
}
}
]
},
{
"$nor" : [
{
"assignee" : {
"$exists" : true
}
}
]
},
{
"siteId" : {
"$eq" : "MAIN"
}
},
{
"status" : {
"$eq" : "ACTIVE"
}
},
{
"creationDate" : {
"$lt" : ISODate("2017-10-20T17:58:17.966Z")
}
},
{
"creationDate" : {
"$gt" : ISODate("2017-10-12T17:58:17.809Z")
}
},
{
"reportCount" : {
"$gt" : 0.0
}
}
]
},
"inputStage" : {
"stage" : "AND_SORTED",
"inputStages" : [
{
"stage" : "IXSCAN",
"keyPattern" : {
"parent" : 1.0
},
"indexName" : "parent_1",
"isMultiKey" : false,
"multiKeyPaths" : {
"parent" : []
},
"isUnique" : false,
"isSparse" : false,
"isPartial" : false,
"indexVersion" : 2,
"direction" : "forward",
"indexBounds" : {
"parent" : [
"[null, null]"
]
}
},
{
"stage" : "IXSCAN",
"keyPattern" : {
"assignee" : 1.0
},
"indexName" : "assignee_1",
"isMultiKey" : false,
"multiKeyPaths" : {
"assignee" : []
},
"isUnique" : false,
"isSparse" : false,
"isPartial" : false,
"indexVersion" : 2,
"direction" : "forward",
"indexBounds" : {
"assignee" : [
"[null, null]"
]
}
}
]
}
}
}
}
]
},
"executionStats" : {
"executionSuccess" : true,
"nReturned" : 19,
"executionTimeMillis" : 8,
"totalKeysExamined" : 533,
"totalDocsExamined" : 56,
"executionStages" : {
"stage" : "FETCH",
"filter" : {
"$and" : [
{
"siteId" : {
"$eq" : "MAIN"
}
},
{
"status" : {
"$eq" : "ACTIVE"
}
},
{
"$nor" : [
{
"assignee" : {
"$exists" : true
}
}
]
},
{
"$nor" : [
{
"parent" : {
"$exists" : true
}
}
]
}
]
},
"nReturned" : 19,
"executionTimeMillisEstimate" : 0,
"works" : 534,
"advanced" : 19,
"needTime" : 513,
"needYield" : 0,
"saveState" : 20,
"restoreState" : 20,
"isEOF" : 1,
"invalidates" : 0,
"docsExamined" : 56,
"alreadyHasObj" : 0,
"inputStage" : {
"stage" : "IXSCAN",
"nReturned" : 56,
"executionTimeMillisEstimate" : 0,
"works" : 533,
"advanced" : 56,
"needTime" : 476,
"needYield" : 0,
"saveState" : 20,
"restoreState" : 20,
"isEOF" : 1,
"invalidates" : 0,
"keyPattern" : {
"creationDate" : 1.0,
"reportCount" : 1.0,
"label" : 1.0
},
"indexName" : "creationDate_1_reportCount_1_label_1",
"isMultiKey" : false,
"multiKeyPaths" : {
"creationDate" : [],
"reportCount" : [],
"label" : []
},
"isUnique" : false,
"isSparse" : false,
"isPartial" : false,
"indexVersion" : 2,
"direction" : "forward",
"indexBounds" : {
"creationDate" : [
"(new Date(1507831097809), new Date(1508522297966))"
],
"reportCount" : [
"(0.0, inf.0]"
],
"label" : [
"[MinKey, MaxKey]"
]
},
"keysExamined" : 533,
"seeks" : 477,
"dupsTested" : 0,
"dupsDropped" : 0,
"seenInvalidated" : 0
}
}
},
"ok" : 1.0
}
查询仍需要 700-800 毫秒 return 数据。如何更改索引以使查询 运行 更快？不考虑 "keysExamined" : 533, "seeks" : 477, 这个数据。这只是测试数据。
看起来它使用了索引，但只使用了索引中的第一个字段？还有 multuKey 是假的？
解释计划输出的几个要点：
- 查询寻址以下属性：
siteId, status, creationDate, reportCount, assignee, parent
- 获胜计划分为两个阶段：
- IX_SCAN 使用
creationDate_1_reportCount_1_label_1，这在 creationDate 和 reportCount 上使用索引查找来识别 56 个文档，然后将其转发到 FETCH 阶段
- FETCH 从 IX_SCAN 阶段接收到 56 个文档，然后询问这些文档以应用
siteId、status、assignee 和 parent 过滤器。此询问导致 37 个文档被丢弃，从而导致 19 个文档被返回。
因此，您的索引仅涵盖查询中 6 个属性中的 2 个，查询中的其余 4 个属性通过检查 文档 而不是 来应用指数。如果您希望此查询完全被索引覆盖，请创建以下索引：
db.collection.createIndex(
{siteId: 1, status: 1, creationDate: 1, reportCount: 1, assignee: 1, parent: 1}
)
如果您重新 运行 使用此索引，那么您应该会发现 (a) MongoDB 选择此索引和 (b) IX_SCAN 转发的文档数stage 与您的 find 调用返回的文档数相同。
我说 "should find" 因为这里还有其他方面可能导致 MongoDB 选择不同的索引，例如使用 $nor 和排序阶段 (creationDate: 1)。我建议在每次调整后调整索引并 运行 解释 'on' 并在 executionStats 子文档中查找这些关键项目：
- "nReturned"
- "totalKeysExamined"
- "totalDocsExamined"
一个简单的经验法则是：totalKeysExamined 越接近 nReturned 并且 totalDocsExamined 越接近零……索引覆盖率就越好。
还有一个索引成本的问题（在对写入时间和索引存储的影响方面）所以我建议考虑您的非功能性需求 - 如果没有完整的索引覆盖率，是否可以实现您期望的运行时间？如果不是，那么您应该继续进行经验测试，但要准备好根据 explain() 输出告诉您的内容调整您的选择。
我们有以下查询
db.Comment.find(
{
$and: [
{ reportCount: { $gt: 0 } },
{ assignee: { $exists: false } },
{ creationDate: { $gt: new Date(1507831097809) } },
{ creationDate: { $lt: new Date(1508522297966) } },
{ siteId: 'MAIN' },
{ parent: { $exists: false } },
{ status: 'ACTIVE' }
]
})
.sort({ creationDate: 1 })
我们有一个索引
{
"v" : 2,
"key" : {
"creationDate" : 1,
"reportCount" : 1,
"label" : 1
}
}
这是 explain 个结果：
{
"queryPlanner" : {
"plannerVersion" : 1,
"namespace" : "myNameSpace",
"indexFilterSet" : false,
"parsedQuery" : {
"$and" : [
{
"siteId" : {
"$eq" : "MAIN"
}
},
{
"status" : {
"$eq" : "ACTIVE"
}
},
{
"creationDate" : {
"$lt" : ISODate("2017-10-20T17:58:17.966Z")
}
},
{
"creationDate" : {
"$gt" : ISODate("2017-10-12T17:58:17.809Z")
}
},
{
"reportCount" : {
"$gt" : 0.0
}
},
{
"$nor" : [
{
"assignee" : {
"$exists" : true
}
}
]
},
{
"$nor" : [
{
"parent" : {
"$exists" : true
}
}
]
}
]
},
"winningPlan" : {
"stage" : "FETCH",
"filter" : {
"$and" : [
{
"siteId" : {
"$eq" : "MAIN"
}
},
{
"status" : {
"$eq" : "ACTIVE"
}
},
{
"$nor" : [
{
"assignee" : {
"$exists" : true
}
}
]
},
{
"$nor" : [
{
"parent" : {
"$exists" : true
}
}
]
}
]
},
"inputStage" : {
"stage" : "IXSCAN",
"keyPattern" : {
"creationDate" : 1.0,
"reportCount" : 1.0,
"label" : 1.0
},
"indexName" : "creationDate_1_reportCount_1_label_1",
"isMultiKey" : false,
"multiKeyPaths" : {
"creationDate" : [],
"reportCount" : [],
"label" : []
},
"isUnique" : false,
"isSparse" : false,
"isPartial" : false,
"indexVersion" : 2,
"direction" : "forward",
"indexBounds" : {
"creationDate" : [
"(new Date(1507831097809), new Date(1508522297966))"
],
"reportCount" : [
"(0.0, inf.0]"
],
"label" : [
"[MinKey, MaxKey]"
]
}
}
},
"rejectedPlans" : [
{
"stage" : "SORT",
"sortPattern" : {
"creationDate" : 1.0
},
"inputStage" : {
"stage" : "SORT_KEY_GENERATOR",
"inputStage" : {
"stage" : "FETCH",
"filter" : {
"$and" : [
{
"$nor" : [
{
"parent" : {
"$exists" : true
}
}
]
},
{
"siteId" : {
"$eq" : "MAIN"
}
},
{
"status" : {
"$eq" : "ACTIVE"
}
},
{
"creationDate" : {
"$lt" : ISODate("2017-10-20T17:58:17.966Z")
}
},
{
"creationDate" : {
"$gt" : ISODate("2017-10-12T17:58:17.809Z")
}
},
{
"reportCount" : {
"$gt" : 0.0
}
},
{
"$nor" : [
{
"assignee" : {
"$exists" : true
}
}
]
}
]
},
"inputStage" : {
"stage" : "IXSCAN",
"keyPattern" : {
"parent" : 1.0
},
"indexName" : "parent_1",
"isMultiKey" : false,
"multiKeyPaths" : {
"parent" : []
},
"isUnique" : false,
"isSparse" : false,
"isPartial" : false,
"indexVersion" : 2,
"direction" : "forward",
"indexBounds" : {
"parent" : [
"[null, null]"
]
}
}
}
}
},
{
"stage" : "SORT",
"sortPattern" : {
"creationDate" : 1.0
},
"inputStage" : {
"stage" : "SORT_KEY_GENERATOR",
"inputStage" : {
"stage" : "FETCH",
"filter" : {
"$and" : [
{
"$nor" : [
{
"assignee" : {
"$exists" : true
}
}
]
},
{
"siteId" : {
"$eq" : "MAIN"
}
},
{
"status" : {
"$eq" : "ACTIVE"
}
},
{
"creationDate" : {
"$lt" : ISODate("2017-10-20T17:58:17.966Z")
}
},
{
"creationDate" : {
"$gt" : ISODate("2017-10-12T17:58:17.809Z")
}
},
{
"reportCount" : {
"$gt" : 0.0
}
},
{
"$nor" : [
{
"parent" : {
"$exists" : true
}
}
]
}
]
},
"inputStage" : {
"stage" : "IXSCAN",
"keyPattern" : {
"assignee" : 1.0
},
"indexName" : "assignee_1",
"isMultiKey" : false,
"multiKeyPaths" : {
"assignee" : []
},
"isUnique" : false,
"isSparse" : false,
"isPartial" : false,
"indexVersion" : 2,
"direction" : "forward",
"indexBounds" : {
"assignee" : [
"[null, null]"
]
}
}
}
}
},
{
"stage" : "SORT",
"sortPattern" : {
"creationDate" : 1.0
},
"inputStage" : {
"stage" : "SORT_KEY_GENERATOR",
"inputStage" : {
"stage" : "FETCH",
"filter" : {
"$and" : [
{
"status" : {
"$eq" : "ACTIVE"
}
},
{
"creationDate" : {
"$lt" : ISODate("2017-10-20T17:58:17.966Z")
}
},
{
"creationDate" : {
"$gt" : ISODate("2017-10-12T17:58:17.809Z")
}
},
{
"reportCount" : {
"$gt" : 0.0
}
},
{
"$nor" : [
{
"assignee" : {
"$exists" : true
}
}
]
},
{
"$nor" : [
{
"parent" : {
"$exists" : true
}
}
]
}
]
},
"inputStage" : {
"stage" : "IXSCAN",
"keyPattern" : {
"siteId" : 1.0,
"updatedDate" : 1.0,
"label" : 1.0
},
"indexName" : "siteId_1_updatedDate_1_label_1",
"isMultiKey" : false,
"multiKeyPaths" : {
"siteId" : [],
"updatedDate" : [],
"label" : []
},
"isUnique" : false,
"isSparse" : false,
"isPartial" : false,
"indexVersion" : 2,
"direction" : "forward",
"indexBounds" : {
"siteId" : [
"[\"MAIN\", \"MAIN\"]"
],
"updatedDate" : [
"[MinKey, MaxKey]"
],
"label" : [
"[MinKey, MaxKey]"
]
}
}
}
}
},
{
"stage" : "SORT",
"sortPattern" : {
"creationDate" : 1.0
},
"inputStage" : {
"stage" : "SORT_KEY_GENERATOR",
"inputStage" : {
"stage" : "FETCH",
"filter" : {
"$and" : [
{
"$nor" : [
{
"parent" : {
"$exists" : true
}
}
]
},
{
"$nor" : [
{
"assignee" : {
"$exists" : true
}
}
]
},
{
"siteId" : {
"$eq" : "MAIN"
}
},
{
"status" : {
"$eq" : "ACTIVE"
}
},
{
"creationDate" : {
"$lt" : ISODate("2017-10-20T17:58:17.966Z")
}
},
{
"creationDate" : {
"$gt" : ISODate("2017-10-12T17:58:17.809Z")
}
},
{
"reportCount" : {
"$gt" : 0.0
}
}
]
},
"inputStage" : {
"stage" : "AND_SORTED",
"inputStages" : [
{
"stage" : "IXSCAN",
"keyPattern" : {
"parent" : 1.0
},
"indexName" : "parent_1",
"isMultiKey" : false,
"multiKeyPaths" : {
"parent" : []
},
"isUnique" : false,
"isSparse" : false,
"isPartial" : false,
"indexVersion" : 2,
"direction" : "forward",
"indexBounds" : {
"parent" : [
"[null, null]"
]
}
},
{
"stage" : "IXSCAN",
"keyPattern" : {
"assignee" : 1.0
},
"indexName" : "assignee_1",
"isMultiKey" : false,
"multiKeyPaths" : {
"assignee" : []
},
"isUnique" : false,
"isSparse" : false,
"isPartial" : false,
"indexVersion" : 2,
"direction" : "forward",
"indexBounds" : {
"assignee" : [
"[null, null]"
]
}
}
]
}
}
}
}
]
},
"executionStats" : {
"executionSuccess" : true,
"nReturned" : 19,
"executionTimeMillis" : 8,
"totalKeysExamined" : 533,
"totalDocsExamined" : 56,
"executionStages" : {
"stage" : "FETCH",
"filter" : {
"$and" : [
{
"siteId" : {
"$eq" : "MAIN"
}
},
{
"status" : {
"$eq" : "ACTIVE"
}
},
{
"$nor" : [
{
"assignee" : {
"$exists" : true
}
}
]
},
{
"$nor" : [
{
"parent" : {
"$exists" : true
}
}
]
}
]
},
"nReturned" : 19,
"executionTimeMillisEstimate" : 0,
"works" : 534,
"advanced" : 19,
"needTime" : 513,
"needYield" : 0,
"saveState" : 20,
"restoreState" : 20,
"isEOF" : 1,
"invalidates" : 0,
"docsExamined" : 56,
"alreadyHasObj" : 0,
"inputStage" : {
"stage" : "IXSCAN",
"nReturned" : 56,
"executionTimeMillisEstimate" : 0,
"works" : 533,
"advanced" : 56,
"needTime" : 476,
"needYield" : 0,
"saveState" : 20,
"restoreState" : 20,
"isEOF" : 1,
"invalidates" : 0,
"keyPattern" : {
"creationDate" : 1.0,
"reportCount" : 1.0,
"label" : 1.0
},
"indexName" : "creationDate_1_reportCount_1_label_1",
"isMultiKey" : false,
"multiKeyPaths" : {
"creationDate" : [],
"reportCount" : [],
"label" : []
},
"isUnique" : false,
"isSparse" : false,
"isPartial" : false,
"indexVersion" : 2,
"direction" : "forward",
"indexBounds" : {
"creationDate" : [
"(new Date(1507831097809), new Date(1508522297966))"
],
"reportCount" : [
"(0.0, inf.0]"
],
"label" : [
"[MinKey, MaxKey]"
]
},
"keysExamined" : 533,
"seeks" : 477,
"dupsTested" : 0,
"dupsDropped" : 0,
"seenInvalidated" : 0
}
}
},
"ok" : 1.0
}
查询仍需要 700-800 毫秒 return 数据。如何更改索引以使查询 运行 更快？不考虑 "keysExamined" : 533, "seeks" : 477, 这个数据。这只是测试数据。
看起来它使用了索引，但只使用了索引中的第一个字段？还有 multuKey 是假的？
解释计划输出的几个要点：
- 查询寻址以下属性：
siteId, status, creationDate, reportCount, assignee, parent - 获胜计划分为两个阶段：
- IX_SCAN 使用
creationDate_1_reportCount_1_label_1，这在creationDate和reportCount上使用索引查找来识别 56 个文档，然后将其转发到 FETCH 阶段 - FETCH 从 IX_SCAN 阶段接收到 56 个文档，然后询问这些文档以应用
siteId、status、assignee和parent过滤器。此询问导致 37 个文档被丢弃，从而导致 19 个文档被返回。
- IX_SCAN 使用
因此，您的索引仅涵盖查询中 6 个属性中的 2 个，查询中的其余 4 个属性通过检查 文档 而不是 来应用指数。如果您希望此查询完全被索引覆盖，请创建以下索引：
db.collection.createIndex(
{siteId: 1, status: 1, creationDate: 1, reportCount: 1, assignee: 1, parent: 1}
)
如果您重新 运行 使用此索引，那么您应该会发现 (a) MongoDB 选择此索引和 (b) IX_SCAN 转发的文档数stage 与您的 find 调用返回的文档数相同。
我说 "should find" 因为这里还有其他方面可能导致 MongoDB 选择不同的索引，例如使用 $nor 和排序阶段 (creationDate: 1)。我建议在每次调整后调整索引并 运行 解释 'on' 并在 executionStats 子文档中查找这些关键项目：
- "nReturned"
- "totalKeysExamined"
- "totalDocsExamined"
一个简单的经验法则是：totalKeysExamined 越接近 nReturned 并且 totalDocsExamined 越接近零……索引覆盖率就越好。
还有一个索引成本的问题（在对写入时间和索引存储的影响方面）所以我建议考虑您的非功能性需求 - 如果没有完整的索引覆盖率，是否可以实现您期望的运行时间？如果不是，那么您应该继续进行经验测试，但要准备好根据 explain() 输出告诉您的内容调整您的选择。