MongoDB之幾種情況下的索引選擇策略
一、MongoDB如何選擇索引
如果我們在Collection建了5個index，那麼當我們查詢的時候，MongoDB會根據查詢語句的篩選條件、sort排序等來定位可以使用的index作為候選索引；然後MongoDB會創建對應數量的查詢計劃，並分別使用不同執行緒執行查詢計劃，最終會選擇一個執行最快的index；但是這個選擇也不是一成不變的，後續還會有一段時間根據實際執行情況動態調整；
二、數據準備
for(let i = 0;i<1000000;i++){
db.users.insertOne({
"id":i,
"name":'user'+i,
"age":Math.floor(Math.random()*120),
"created":new Date(ISODate().getTime() - 1000 * 60*i)
});
}
三、正則對index的使用
MongoDB支援正則查詢，在特定的情況其也是可以利用index獲得查詢性能的提升；
雖然MongDB執行正則會最大限度的使用index，但是不同的用法還是會影響對index的利用程度的；
執行以下普通正則表達式
從queryPlanner.winningPlan部分的COLLSCAN，可以看到正則表達式默認會進行全表的掃描；
從executionStats.executionStages部分可以看到COLLSCAN共掃描了1000000個文檔，並返回1111個文檔，總耗時794ms；
db.users.find({
name:/user999/
}).explain('executionStats')
{
"queryPlanner" : {
"plannerVersion" : 1,
"namespace" : "test.users",
"indexFilterSet" : false,
"winningPlan" : {
"stage" : "COLLSCAN",
"filter" : {
"name" : {
"$regex" : "user999"
}
},
"direction" : "forward"
},
"rejectedPlans" : [ ]
},
"executionStats" : {
"executionSuccess" : true,
"nReturned" : 1111,
"executionTimeMillis" : 909,
"totalKeysExamined" : 0,
"totalDocsExamined" : 1000000,
"executionStages" : {
"stage" : "COLLSCAN",
"filter" : {
"name" : {
"$regex" : "user999"
}
},
"nReturned" : 1111,
"executionTimeMillisEstimate" : 794,
"works" : 1000002,
"advanced" : 1111,
"needTime" : 998890,
"needYield" : 0,
"saveState" : 7830,
"restoreState" : 7830,
"isEOF" : 1,
"invalidates" : 0,
"direction" : "forward",
"docsExamined" : 1000000
}
}
}
創建一個包含name的index；
db.users.createIndex({name:1})
再次執行上邊的查詢，可以看到使用了我們新建的name_1索引；但是從執行狀態來看，還是掃描了全體的索引的key，並不能很好的利用index；
{
"queryPlanner" : {
"plannerVersion" : 1,
"namespace" : "test.users",
"indexFilterSet" : false,
"parsedQuery" : {
"name" : {
"$regex" : "user999"
}
},
"winningPlan" : {
"stage" : "FETCH",
"inputStage" : {
"stage" : "IXSCAN",
"filter" : {
"name" : {
"$regex" : "user999"
}
},
"keyPattern" : {
"name" : 1
},
"indexName" : "name_1"
}
},
"rejectedPlans" : [ ]
},
"executionStats" : {
"executionSuccess" : true,
"nReturned" : 1111,
"executionTimeMillis" : 971,
"totalKeysExamined" : 1000000,
"totalDocsExamined" : 1111,
"executionStages" : {
"stage" : "FETCH",
"nReturned" : 1111,
"executionTimeMillisEstimate" : 887,
"docsExamined" : 1111,
"alreadyHasObj" : 0,
"inputStage" : {
"stage" : "IXSCAN",
"filter" : {
"name" : {
"$regex" : "user999"
}
},
"nReturned" : 1111,
"executionTimeMillisEstimate" : 876,
"keyPattern" : {
"name" : 1
},
"indexName" : "name_1",
"keysExamined" : 1000000
}
}
}
}
使用前綴匹配的話可以最大限度的利用index，從執行狀態可以看到只檢測了1111個index key；
db.users.find({
name:/^user999/
}).explain('executionStats')
{
"queryPlanner" : {
"plannerVersion" : 1,
"namespace" : "test.users",
"indexFilterSet" : false,
"parsedQuery" : {
"name" : {
"$regex" : "^user999"
}
},
"winningPlan" : {
"stage" : "FETCH",
"inputStage" : {
"stage" : "IXSCAN",
"keyPattern" : {
"name" : 1
},
"indexName" : "name_1"
}
},
"rejectedPlans" : [ ]
},
"executionStats" : {
"executionSuccess" : true,
"nReturned" : 1111,
"executionTimeMillis" : 2,
"totalKeysExamined" : 1111,
"totalDocsExamined" : 1111,
"executionStages" : {
"stage" : "FETCH",
"nReturned" : 1111,
"executionTimeMillisEstimate" : 0
"docsExamined" : 1111
"inputStage" : {
"stage" : "IXSCAN",
"nReturned" : 1111,
"executionTimeMillisEstimate" : 0,
"indexName" : "name_1",
"keysExamined" : 1111
}
}
}
}
即使是前綴匹配，如果忽略大小寫的話也無法充分利用index了；
db.users.find({
name:/^user999/i
}).explain('executionStats')
{
"queryPlanner" : {
"plannerVersion" : 1,
"namespace" : "test.users",
"indexFilterSet" : false,
"parsedQuery" : {
"name" : {
"$regex" : "user999",
"$options" : "i"
}
},
"winningPlan" : {
"stage" : "FETCH",
"inputStage" : {
"stage" : "IXSCAN",
"filter" : {
"name" : {
"$regex" : "user999",
"$options" : "i"
}
},
"keyPattern" : {
"name" : 1
},
"indexName" : "name_1"
}
},
"rejectedPlans" : [ ]
},
"executionStats" : {
"executionSuccess" : true,
"nReturned" : 1111,
"executionTimeMillis" : 943,
"totalKeysExamined" : 1000000,
"totalDocsExamined" : 1111,
"executionStages" : {
"stage" : "FETCH",
"nReturned" : 1111,
"executionTimeMillisEstimate" : 833,
"works" : 1000001,
"inputStage" : {
"stage" : "IXSCAN",
"filter" : {
"name" : {
"$regex" : "user999",
"$options" : "i"
}
},
"nReturned" : 1111,
"executionTimeMillisEstimate" : 833,
"keyPattern" : {
"name" : 1
},
"indexName" : "name_1"
"keysExamined" : 1000000
}
}
}
}
四、$or從句對索引的利用
MongoDB執行$or從句的時候，會將所有的從句作為邏輯的整體，要不就都使用index，要不就都進行全表掃描；
執行以下的查詢語句；
db.users.find({
$or:[
{name:/^user666/},
{age:{$gte:80}}
]
}).explain('executionStats')
在只有name_1這個index的時候，我們可以看到MongoDB進行了全表掃描，全表掃描的時候進行$or從句的過濾；
{
"queryPlanner" : {
"plannerVersion" : 1,
"namespace" : "test.users",
"indexFilterSet" : false,
"parsedQuery" : {
"$or" : [
{
"age" : {
"$gte" : 20
}
},
{
"name" : {
"$regex" : "^user666"
}
}
]
},
"winningPlan" : {
"stage" : "SUBPLAN",
"inputStage" : {
"stage" : "COLLSCAN",
"filter" : {
"$or" : [
{
"age" : {
"$gte" : 20
}
},
{
"name" : {
"$regex" : "^user666"
}
}
]
},
"direction" : "forward"
}
},
"rejectedPlans" : [ ]
},
"executionStats" : {
"executionSuccess" : true,
"nReturned" : 833995,
"executionTimeMillis" : 576,
"totalKeysExamined" : 0,
"totalDocsExamined" : 1000000,
"executionStages" : {
"stage" : "SUBPLAN",
"nReturned" : 833995,
"executionTimeMillisEstimate" : 447,
"inputStage" : {
"stage" : "COLLSCAN",
"filter" : {
"$or" : [
{
"age" : {
"$gte" : 20
}
},
{
"name" : {
"$regex" : "^user666"
}
}
]
},
"nReturned" : 833995,
"executionTimeMillisEstimate" : 447,
"docsExamined" : 1000000
}
}
}
}
我們對name欄位新建一個index；
db.users.createIndex({age:1})
再次執行以上的查詢語句，這次可以看到每個從句都利用了index，並且每個從句會單獨執行並最終進行or操作；
{
"queryPlanner" : {
"plannerVersion" : 1,
"namespace" : "test.users",
"indexFilterSet" : false,
"parsedQuery" : {
"$or" : [
{
"age" : {
"$gte" : 80
}
},
{
"name" : {
"$regex" : "^user666"
}
}
]
},
"winningPlan" : {
"stage" : "SUBPLAN",
"inputStage" : {
"stage" : "FETCH",
"inputStage" : {
"stage" : "OR",
"inputStages" : [
{
"stage" : "IXSCAN",
"keyPattern" : {
"name" : 1
},
"indexName" : "name_1",
"isMultiKey" : false,
"multiKeyPaths" : {
"name" : [ ]
},
"isUnique" : false,
"isSparse" : false,
"isPartial" : false,
"indexVersion" : 2,
"direction" : "forward",
"indexBounds" : {
"name" : [
"[\"user666\", \"user667\")",
"[/^user666/, /^user666/]"
]
}
},
{
"stage" : "IXSCAN",
"keyPattern" : {
"age" : 1
},
"indexName" : "age_1",
"isMultiKey" : false,
"multiKeyPaths" : {
"age" : [ ]
},
"isUnique" : false,
"isSparse" : false,
"isPartial" : false,
"indexVersion" : 2,
"direction" : "forward",
"indexBounds" : {
"age" : [
"[80.0, inf.0]"
]
}
}
]
}
}
},
"rejectedPlans" : [ ]
},
"executionStats" : {
"executionSuccess" : true,
"nReturned" : 333736,
"executionTimeMillis" : 741,
"totalKeysExamined" : 334102,
"totalDocsExamined" : 333736,
"executionStages" : {
"stage" : "SUBPLAN",
"nReturned" : 333736,
"executionTimeMillisEstimate" : 703,
"inputStage" : {
"stage" : "FETCH",
"nReturned" : 333736,
"executionTimeMillisEstimate" : 682
"docsExamined" : 333736,
"inputStage" : {
"stage" : "OR",
"nReturned" : 333736,
"executionTimeMillisEstimate" : 366,
"inputStages" : [
{
"stage" : "IXSCAN",
"nReturned" : 1111,
"executionTimeMillisEstimate" : 0,
"keyPattern" : {
"name" : 1
},
"indexName" : "name_1",
"indexBounds" : {
"name" : [
"[\"user666\", \"user667\")",
"[/^user666/, /^user666/]"
]
},
"keysExamined" : 1112
},
{
"stage" : "IXSCAN",
"nReturned" : 332990,
"executionTimeMillisEstimate" : 212,
"keyPattern" : {
"age" : 1
},
"indexName" : "age_1",
"indexBounds" : {
"age" : [
"[80.0, inf.0]"
]
},
"keysExamined" : 332990
}
]
}
}
}
}
}
五、sort對索引的利用
如果sort操作無法利用index，則MongoDB就會在記憶體中排序數據，並且數據量一大就會報錯；
db.users.find().sort({created: -1}).explain('executionStats')
{
"queryPlanner" : {
"plannerVersion" : 1,
"namespace" : "test.users",
"indexFilterSet" : false,
"parsedQuery" : {
},
"winningPlan" : {
"stage" : "SORT",
"sortPattern" : {
"created" : -1
},
"inputStage" : {
"stage" : "SORT_KEY_GENERATOR",
"inputStage" : {
"stage" : "COLLSCAN",
"direction" : "forward"
}
}
},
"rejectedPlans" : [ ]
},
"executionStats" : {
"executionSuccess" : false,
"errorMessage" : "Exec error resulting in state FAILURE :: caused by :: Sort operation used more than the maximum 33554432 bytes of RAM. Add an index, or specify a smaller limit.",
"errorCode" : 96,
"nReturned" : 0,
"executionTimeMillis" : 959,
"totalKeysExamined" : 0,
"totalDocsExamined" : 361996,
"executionStages" : {
"stage" : "SORT",
"nReturned" : 0,
"executionTimeMillisEstimate" : 922,
"sortPattern" : {
"created" : -1
},
"memUsage" : 33554518,
"memLimit" : 33554432,
"inputStage" : {
"stage" : "SORT_KEY_GENERATOR",
"nReturned" : 361996,
"executionTimeMillisEstimate" : 590,
"inputStage" : {
"stage" : "COLLSCAN",
"nReturned" : 361996,
"executionTimeMillisEstimate" : 147,
"direction" : "forward",
"docsExamined" : 361996
}
}
}
}
}
如果是單欄位index，sort從兩個方向都可以充分利用index；可以看到MongoDB直接按照index的順序返回結果，直接就沒有sort階段了；
db.users.find().sort({name: -1}).explain('executionStats')
{
"queryPlanner" : {
"plannerVersion" : 1,
"namespace" : "test.users",
"indexFilterSet" : false,
"parsedQuery" : {
},
"winningPlan" : {
"stage" : "FETCH",
"inputStage" : {
"stage" : "IXSCAN",
"keyPattern" : {
"name" : 1
},
"indexName" : "name_1",
"direction" : "backward",
"indexBounds" : {
"name" : [
"[MaxKey, MinKey]"
]
}
}
},
"rejectedPlans" : [ ]
},
"executionStats" : {
"executionSuccess" : true,
"nReturned" : 1000000,
"executionTimeMillis" : 1317,
"totalKeysExamined" : 1000000,
"totalDocsExamined" : 1000000,
"executionStages" : {
"stage" : "FETCH",
"nReturned" : 1000000,
"executionTimeMillisEstimate" : 1180,
"inputStage" : {
"stage" : "IXSCAN",
"nReturned" : 1000000,
"executionTimeMillisEstimate" : 560,
"keyPattern" : {
"name" : 1
},
"indexName" : "name_1",
"isMultiKey" : false,
"multiKeyPaths" : {
"name" : [ ]
},
"isUnique" : false,
"isSparse" : false,
"isPartial" : false,
"indexVersion" : 2,
"direction" : "backward",
"indexBounds" : {
"name" : [
"[MaxKey, MinKey]"
]
},
"keysExamined" : 1000000,
"seeks" : 1,
"dupsTested" : 0,
"dupsDropped" : 0,
"seenInvalidated" : 0
}
}
}
}
對於複合索引，sort除了可以從整體上從兩個方向利用index，也可以利用index的前綴索引和非前綴局部索引；
新建複合索引
db.users.createIndex({created:-1, name:1, age:1})
按照複合索引的反方向進行整體排序；
db.users.find().sort({created:1, name:-1, age:-1}).explain('executionStats')
{
"queryPlanner" : {
"plannerVersion" : 1,
"namespace" : "test.users",
"indexFilterSet" : false,
"parsedQuery" : {
},
"winningPlan" : {
"stage" : "FETCH",
"inputStage" : {
"stage" : "IXSCAN",
"keyPattern" : {
"created" : -1,
"name" : 1,
"age" : 1
},
"indexName" : "created_-1_name_1_age_1",
"isMultiKey" : false,
"multiKeyPaths" : {
"created" : [ ],
"name" : [ ],
"age" : [ ]
},
"isUnique" : false,
"isSparse" : false,
"isPartial" : false,
"indexVersion" : 2,
"direction" : "backward",
"indexBounds" : {
"created" : [
"[MinKey, MaxKey]"
],
"name" : [
"[MaxKey, MinKey]"
],
"age" : [
"[MaxKey, MinKey]"
]
}
}
},
"rejectedPlans" : [ ]
},
"executionStats" : {
"executionSuccess" : true,
"nReturned" : 1000000,
"executionTimeMillis" : 1518,
"totalKeysExamined" : 1000000,
"totalDocsExamined" : 1000000,
"executionStages" : {
"stage" : "FETCH",
"nReturned" : 1000000,
"executionTimeMillisEstimate" : 1364,
"docsExamined" : 1000000,
"inputStage" : {
"stage" : "IXSCAN",
"nReturned" : 1000000,
"executionTimeMillisEstimate" : 816,
"keyPattern" : {
"created" : -1,
"name" : 1,
"age" : 1
},
"indexName" : "created_-1_name_1_age_1",
"isMultiKey" : false,
"multiKeyPaths" : {
"created" : [ ],
"name" : [ ],
"age" : [ ]
},
"isUnique" : false,
"isSparse" : false,
"isPartial" : false,
"indexVersion" : 2,
"direction" : "backward",
"indexBounds" : {
"created" : [
"[MinKey, MaxKey]"
],
"name" : [
"[MaxKey, MinKey]"
],
"age" : [
"[MaxKey, MinKey]"
]
},
"keysExamined" : 1000000
}
}
}
}
排序使用索引前綴，也需要保證欄位的順序，但是可以反方向排序；
db.users.find().sort({created:1, name:-1, age:-1}).explain('executionStats')
{
"queryPlanner" : {
"plannerVersion" : 1,
"namespace" : "test.users",
"indexFilterSet" : false,
"parsedQuery" : {
},
"winningPlan" : {
"stage" : "FETCH",
"inputStage" : {
"stage" : "IXSCAN",
"keyPattern" : {
"created" : -1,
"name" : 1,
"age" : 1
},
"indexName" : "created_-1_name_1_age_1",
"isMultiKey" : false,
"multiKeyPaths" : {
"created" : [ ],
"name" : [ ],
"age" : [ ]
},
"isUnique" : false,
"isSparse" : false,
"isPartial" : false,
"indexVersion" : 2,
"direction" : "backward",
"indexBounds" : {
"created" : [
"[MinKey, MaxKey]"
],
"name" : [
"[MaxKey, MinKey]"
],
"age" : [
"[MaxKey, MinKey]"
]
}
}
},
"rejectedPlans" : [ ]
},
"executionStats" : {
"executionSuccess" : true,
"nReturned" : 1000000,
"executionTimeMillis" : 1487,
"totalKeysExamined" : 1000000,
"totalDocsExamined" : 1000000,
"executionStages" : {
"stage" : "FETCH",
"nReturned" : 1000000,
"executionTimeMillisEstimate" : 1339,
"works" : 1000001,
"advanced" : 1000000,
"needTime" : 0,
"needYield" : 0,
"saveState" : 7845,
"restoreState" : 7845,
"isEOF" : 1,
"invalidates" : 0,
"docsExamined" : 1000000,
"alreadyHasObj" : 0,
"inputStage" : {
"stage" : "IXSCAN",
"nReturned" : 1000000,
"executionTimeMillisEstimate" : 769,
"works" : 1000001,
"advanced" : 1000000,
"needTime" : 0,
"needYield" : 0,
"saveState" : 7845,
"restoreState" : 7845,
"isEOF" : 1,
"invalidates" : 0,
"keyPattern" : {
"created" : -1,
"name" : 1,
"age" : 1
},
"indexName" : "created_-1_name_1_age_1",
"isMultiKey" : false,
"multiKeyPaths" : {
"created" : [ ],
"name" : [ ],
"age" : [ ]
},
"isUnique" : false,
"isSparse" : false,
"isPartial" : false,
"indexVersion" : 2,
"direction" : "backward",
"indexBounds" : {
"created" : [
"[MinKey, MaxKey]"
],
"name" : [
"[MaxKey, MinKey]"
],
"age" : [
"[MaxKey, MinKey]"
]
},
"keysExamined" : 1000000,
"seeks" : 1,
"dupsTested" : 0,
"dupsDropped" : 0,
"seenInvalidated" : 0
}
}
}
}
排序如果使用的是非前綴的局部字典排序，name需要保證前邊的欄位是等值篩選操作才行；
db.users.find({created:new Date("2021-10-30T08:17:01.184Z")}).sort({name:-1}).explain('executionStats')
{
"queryPlanner" : {
"plannerVersion" : 1,
"namespace" : "test.users",
"indexFilterSet" : false,
"parsedQuery" : {
"created" : {
"$eq" : ISODate("2021-10-30T08:17:01.184Z")
}
},
"winningPlan" : {
"stage" : "FETCH",
"inputStage" : {
"stage" : "IXSCAN",
"keyPattern" : {
"created" : -1,
"name" : 1,
"age" : 1
},
"indexName" : "created_-1_name_1_age_1",
"isMultiKey" : false,
"multiKeyPaths" : {
"created" : [ ],
"name" : [ ],
"age" : [ ]
},
"isUnique" : false,
"isSparse" : false,
"isPartial" : false,
"indexVersion" : 2,
"direction" : "backward",
"indexBounds" : {
"created" : [
"[new Date(1635581821184), new Date(1635581821184)]"
],
"name" : [
"[MaxKey, MinKey]"
],
"age" : [
"[MaxKey, MinKey]"
]
}
}
},
"rejectedPlans" : [ ]
},
"executionStats" : {
"executionSuccess" : true,
"nReturned" : 0,
"executionTimeMillis" : 0,
"totalKeysExamined" : 0,
"totalDocsExamined" : 0,
"executionStages" : {
"stage" : "FETCH",
"nReturned" : 0,
"executionTimeMillisEstimate" : 0,
"works" : 1,
"advanced" : 0,
"needTime" : 0,
"needYield" : 0,
"saveState" : 0,
"restoreState" : 0,
"isEOF" : 1,
"invalidates" : 0,
"docsExamined" : 0,
"alreadyHasObj" : 0,
"inputStage" : {
"stage" : "IXSCAN",
"nReturned" : 0,
"executionTimeMillisEstimate" : 0,
"works" : 1,
"advanced" : 0,
"needTime" : 0,
"needYield" : 0,
"saveState" : 0,
"restoreState" : 0,
"isEOF" : 1,
"invalidates" : 0,
"keyPattern" : {
"created" : -1,
"name" : 1,
"age" : 1
},
"indexName" : "created_-1_name_1_age_1",
"isMultiKey" : false,
"multiKeyPaths" : {
"created" : [ ],
"name" : [ ],
"age" : [ ]
},
"isUnique" : false,
"isSparse" : false,
"isPartial" : false,
"indexVersion" : 2,
"direction" : "backward",
"indexBounds" : {
"created" : [
"[new Date(1635581821184), new Date(1635581821184)]"
],
"name" : [
"[MaxKey, MinKey]"
],
"age" : [
"[MaxKey, MinKey]"
]
},
"keysExamined" : 0,
"seeks" : 1,
"dupsTested" : 0,
"dupsDropped" : 0,
"seenInvalidated" : 0
}
}
}
}
六、搜索數據對索引命中的影響
MongoDB對index的選擇是受到實際場景的數據影響比較大的，即與實際數據的分布規律有關，也跟實際篩選出來的數據有關係；所以我們對索引的優化和測試都需要考慮實際的數據場景才行；
由於name的欄位值篩選出來的key太多，不能充分利用index，所以MongoDB拒絕了name_1並選擇了age_1;
db.users.find({
name:/^user/,
age:{$gte:110}
}).explain('executionStats')
{
"queryPlanner" : {
"plannerVersion" : 1,
"namespace" : "test.users",
"indexFilterSet" : false,
"parsedQuery" : {
"$and" : [
{
"age" : {
"$gte" : 110
}
},
{
"name" : {
"$regex" : "^user"
}
}
]
},
"winningPlan" : {
"stage" : "FETCH",
"filter" : {
"name" : {
"$regex" : "^user"
}
},
"inputStage" : {
"stage" : "IXSCAN",
"keyPattern" : {
"age" : 1
},
"indexName" : "age_1",
"isMultiKey" : false,
"multiKeyPaths" : {
"age" : [ ]
},
"isUnique" : false,
"isSparse" : false,
"isPartial" : false,
"indexVersion" : 2,
"direction" : "forward",
"indexBounds" : {
"age" : [
"[110.0, inf.0]"
]
}
}
},
"rejectedPlans" : [
{
"stage" : "FETCH",
"filter" : {
"age" : {
"$gte" : 110
}
},
"inputStage" : {
"stage" : "IXSCAN",
"keyPattern" : {
"name" : 1
},
"indexName" : "name_1",
"isMultiKey" : false,
"multiKeyPaths" : {
"name" : [ ]
},
"isUnique" : false,
"isSparse" : false,
"isPartial" : false,
"indexVersion" : 2,
"direction" : "forward",
"indexBounds" : {
"name" : [
"[\"user\", \"uses\")",
"[/^user/, /^user/]"
]
}
}
}
]
},
"executionStats" : {
"executionSuccess" : true,
"nReturned" : 83215,
"executionTimeMillis" : 246,
"totalKeysExamined" : 83215,
"totalDocsExamined" : 83215,
"executionStages" : {
"stage" : "FETCH",
"filter" : {
"name" : {
"$regex" : "^user"
}
},
"nReturned" : 83215,
"executionTimeMillisEstimate" : 232,
"works" : 83216,
"advanced" : 83215,
"needTime" : 0,
"needYield" : 0,
"saveState" : 658,
"restoreState" : 658,
"isEOF" : 1,
"invalidates" : 0,
"docsExamined" : 83215,
"alreadyHasObj" : 0,
"inputStage" : {
"stage" : "IXSCAN",
"nReturned" : 83215,
"executionTimeMillisEstimate" : 43,
"works" : 83216,
"advanced" : 83215,
"needTime" : 0,
"needYield" : 0,
"saveState" : 658,
"restoreState" : 658,
"isEOF" : 1,
"invalidates" : 0,
"keyPattern" : {
"age" : 1
},
"indexName" : "age_1",
"isMultiKey" : false,
"multiKeyPaths" : {
"age" : [ ]
},
"isUnique" : false,
"isSparse" : false,
"isPartial" : false,
"indexVersion" : 2,
"direction" : "forward",
"indexBounds" : {
"age" : [
"[110.0, inf.0]"
]
},
"keysExamined" : 83215,
"seeks" : 1,
"dupsTested" : 0,
"dupsDropped" : 0,
"seenInvalidated" : 0
}
}
}
}
我們修改一下name篩選條件的值，進一步縮小命中的範圍，可以看到這次MongoDB選擇了name_1;
db.users.find({
name:/^user8888/,
age:{$gte:110}
}).explain('executionStats')
{
"queryPlanner" : {
"plannerVersion" : 1,
"namespace" : "test.users",
"indexFilterSet" : false,
"parsedQuery" : {
"$and" : [
{
"age" : {
"$gte" : 110
}
},
{
"name" : {
"$regex" : "^user8888"
}
}
]
},
"winningPlan" : {
"stage" : "FETCH",
"filter" : {
"age" : {
"$gte" : 110
}
},
"inputStage" : {
"stage" : "IXSCAN",
"keyPattern" : {
"name" : 1
},
"indexName" : "name_1",
"isMultiKey" : false,
"multiKeyPaths" : {
"name" : [ ]
},
"isUnique" : false,
"isSparse" : false,
"isPartial" : false,
"indexVersion" : 2,
"direction" : "forward",
"indexBounds" : {
"name" : [
"[\"user8888\", \"user8889\")",
"[/^user8888/, /^user8888/]"
]
}
}
},
"rejectedPlans" : [
{
"stage" : "FETCH",
"filter" : {
"name" : {
"$regex" : "^user8888"
}
},
"inputStage" : {
"stage" : "IXSCAN",
"keyPattern" : {
"age" : 1
},
"indexName" : "age_1",
"isMultiKey" : false,
"multiKeyPaths" : {
"age" : [ ]
},
"isUnique" : false,
"isSparse" : false,
"isPartial" : false,
"indexVersion" : 2,
"direction" : "forward",
"indexBounds" : {
"age" : [
"[110.0, inf.0]"
]
}
}
}
]
},
"executionStats" : {
"executionSuccess" : true,
"nReturned" : 10,
"executionTimeMillis" : 0,
"totalKeysExamined" : 112,
"totalDocsExamined" : 111,
"executionStages" : {
"stage" : "FETCH",
"filter" : {
"age" : {
"$gte" : 110
}
},
"nReturned" : 10,
"executionTimeMillisEstimate" : 0,
"works" : 114,
"advanced" : 10,
"needTime" : 102,
"needYield" : 0,
"saveState" : 1,
"restoreState" : 1,
"isEOF" : 1,
"invalidates" : 0,
"docsExamined" : 111,
"alreadyHasObj" : 0,
"inputStage" : {
"stage" : "IXSCAN",
"nReturned" : 111,
"executionTimeMillisEstimate" : 0,
"works" : 113,
"advanced" : 111,
"needTime" : 1,
"needYield" : 0,
"saveState" : 1,
"restoreState" : 1,
"isEOF" : 1,
"invalidates" : 0,
"keyPattern" : {
"name" : 1
},
"indexName" : "name_1",
"isMultiKey" : false,
"multiKeyPaths" : {
"name" : [ ]
},
"isUnique" : false,
"isSparse" : false,
"isPartial" : false,
"indexVersion" : 2,
"direction" : "forward",
"indexBounds" : {
"name" : [
"[\"user8888\", \"user8889\")",
"[/^user8888/, /^user8888/]"
]
},
"keysExamined" : 112,
"seeks" : 2,
"dupsTested" : 0,
"dupsDropped" : 0,
"seenInvalidated" : 0
}
}
}
}
