MongoDB 4.2官方支持索引类型如下：
单字段索引 复合索引 多键索引 文本索引 2dsphere索引 2d索引 geoHaystack索引 哈希索引
单字段索引
在单个字段上创建升序索引
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handong1:PRIMARY> db.test.getIndexes() [ { "v" : 2, "key" : { "_id" : 1 }, "name" : "_id_", "ns" : "db6.test" } ] |
在字段id上添加 升序 索引
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handong1:PRIMARY> db.test.createIndex({"id":1}) { "createdCollectionAutomatically" : false, "numIndexesBefore" : 1, "numIndexesAfter" : 2, "ok" : 1, "$clusterTime" : { "clusterTime" : Timestamp(1621322378, 1), "signature" : { "hash" : BinData(0,"AAAAAAAAAAAAAAAAAAAAAAAAAAA="), "keyId" : NumberLong(0) } }, "operationTime" : Timestamp(1621322378, 1) } |
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handong1:PRIMARY> db.test.getIndexes() [ { "v" : 2, "key" : { "_id" : 1 }, "name" : "_id_", "ns" : "db6.test" }, { "v" : 2, "key" : { "id" : 1 }, "name" : "id_1", "ns" : "db6.test" } ] |
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handong1:PRIMARY> db.test.find({"id":100}) { "_id" : ObjectId("60a35d061f183b1d8f092114"), "id" : 100, "name" : "handong", "ziliao" : { "name" : "handong", "age" : 25, "hobby" : "mongodb" } } |
上述查询可以使用新建的单字段索引。
在嵌入式字段上创建索引
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handong1:PRIMARY> db.test.createIndex({"ziliao.name":1}) { "createdCollectionAutomatically" : false, "numIndexesBefore" : 2, "numIndexesAfter" : 3, "ok" : 1, "$clusterTime" : { "clusterTime" : Timestamp(1621323677, 2), "signature" : { "hash" : BinData(0,"AAAAAAAAAAAAAAAAAAAAAAAAAAA="), "keyId" : NumberLong(0) } }, "operationTime" : Timestamp(1621323677, 2) } |
以下查询可以用的新建的索引。
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db.test.find({"ziliao.name":"handong"}) |
在内嵌文档上创建索引
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handong1:PRIMARY> db.test.createIndex({ziliao:1}) { "createdCollectionAutomatically" : false, "numIndexesBefore" : 3, "numIndexesAfter" : 4, "ok" : 1, "$clusterTime" : { "clusterTime" : Timestamp(1621324059, 2), "signature" : { "hash" : BinData(0,"AAAAAAAAAAAAAAAAAAAAAAAAAAA="), "keyId" : NumberLong(0) } }, "operationTime" : Timestamp(1621324059, 2) } |
以下查询可以使用新建的索引。
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db.test.find({ziliao:{ "name" : "handong", "age" : 25, "hobby" : "mongodb" }}) |
复合索引
创建复合索引
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db.user.createIndex({"product_id":1,"type":-1}) |
以下查询可以用到新建的复合索引
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db.user.find({"product_id":"e5a35cfc70364d2092b8f5d14b1a3217","type":0}) |
多键索引
基于一个数组创建索引，MongoDB会自动创建为多键索引，无需刻意指定。
多键索引也可以基于内嵌文档来创建。
多键索引的边界值的计算依赖于特定的规则。
查看文档：
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handong1:PRIMARY> db.score.find() { "_id" : ObjectId("60a32d7f1f183b1d8f0920ad"), "name" : "dandan", "age" : 30, "score" : [ { "english" : 90, "math" : 99, "physics" : 88 } ], "is_del" : false } { "_id" : ObjectId("60a32d8b1f183b1d8f0920ae"), "name" : "dandan", "age" : 30, "score" : [ 99, 98, 97, 96 ], "is_del" : false } { "_id" : ObjectId("60a32d9a1f183b1d8f0920af"), "name" : "dandan", "age" : 30, "score" : [ 100, 100, 100, 100 ], "is_del" : false } { "_id" : ObjectId("60a32e8c1f183b1d8f0920b0"), "name" : "dandan", "age" : 30, "score" : [ { "english" : 70, "math" : 99, "physics" : 88 } ], "is_del" : false } { "_id" : ObjectId("60a37b141f183b1d8f0aa751"), "name" : "dandan", "age" : 30, "score" : [ 96, 95 ] } { "_id" : ObjectId("60a37b1d1f183b1d8f0aa752"), "name" : "dandan", "age" : 30, "score" : [ 96, 95, 94 ] } { "_id" : ObjectId("60a37b221f183b1d8f0aa753"), "name" : "dandan", "age" : 30, "score" : [ 96, 95, 94, 93 ] } |
创建score字段多键索引：
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db.score.createIndex("score":1) |
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handong1:PRIMARY> db.score.find({"score":[ 96, 95 ]}) { "_id" : ObjectId("60a37b141f183b1d8f0aa751"), "name" : "dandan", "age" : 30, "score" : [ 96, 95 ] } |
查看执行计划：
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handong1:PRIMARY> db.score.find({"score":[ 96, 95 ]}).explain() { "queryPlanner" : { "plannerVersion" : 1, "namespace" : "db6.score", "indexFilterSet" : false, "parsedQuery" : { "score" : { "$eq" : [ 96, 95 ] } }, "queryHash" : "8D76FC59", "planCacheKey" : "E2B03CA1", "winningPlan" : { "stage" : "FETCH", "filter" : { "score" : { "$eq" : [ 96, 95 ] } }, "inputStage" : { "stage" : "IXSCAN", "keyPattern" : { "score" : 1 }, "indexName" : "score_1", "isMultiKey" : true, "multiKeyPaths" : { "score" : [ "score" ] }, "isUnique" : false, "isSparse" : false, "isPartial" : false, "indexVersion" : 2, "direction" : "forward", "indexBounds" : { "score" : [ "[96.0, 96.0]", "[[ 96.0, 95.0 ], [ 96.0, 95.0 ]]" ] } } }, "rejectedPlans" : [ ] }, "serverInfo" : { "host" : "mongo3", "port" : 27017, "version" : "4.2.12", "gitVersion" : "5593fd8e33b60c75802edab304e23998fa0ce8a5" }, "ok" : 1, "$clusterTime" : { "clusterTime" : Timestamp(1621326912, 1), "signature" : { "hash" : BinData(0,"AAAAAAAAAAAAAAAAAAAAAAAAAAA="), "keyId" : NumberLong(0) } }, "operationTime" : Timestamp(1621326912, 1) } |
可以看到已经使用了新建的多键索引。
文本索引
为了支持对字符串内容的文本搜索查询，MongoDB提供了文本索引。文本(text )索引可以包含任何值为字符串或字符串元素数组的字段
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db.user.createIndex({"sku_attributes":"text"}) |
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db.user.find({$text:{$search:"测试"}}) |
查看执行计划：
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handong1:PRIMARY> db.user.find({$text:{$search:"测试"}}).explain() { "queryPlanner" : { "plannerVersion" : 1, "namespace" : "db6.user", "indexFilterSet" : false, "parsedQuery" : { "$text" : { "$search" : "测试", "$language" : "english", "$caseSensitive" : false, "$diacriticSensitive" : false } }, "queryHash" : "83098EE1", "planCacheKey" : "7E2D582B", "winningPlan" : { "stage" : "TEXT", "indexPrefix" : {
}, "indexName" : "sku_attributes_text", "parsedTextQuery" : { "terms" : [ "测试" ], "negatedTerms" : [ ], "phrases" : [ ], "negatedPhrases" : [ ] }, "textIndexVersion" : 3, "inputStage" : { "stage" : "TEXT_MATCH", "inputStage" : { "stage" : "FETCH", "inputStage" : { "stage" : "OR", "inputStage" : { "stage" : "IXSCAN", "keyPattern" : { "_fts" : "text", "_ftsx" : 1 }, "indexName" : "sku_attributes_text", "isMultiKey" : true, "isUnique" : false, "isSparse" : false, "isPartial" : false, "indexVersion" : 2, "direction" : "backward", "indexBounds" : {
} } } } } }, "rejectedPlans" : [ ] }, "serverInfo" : { "host" : "mongo3", "port" : 27017, "version" : "4.2.12", "gitVersion" : "5593fd8e33b60c75802edab304e23998fa0ce8a5" }, "ok" : 1, "$clusterTime" : { "clusterTime" : Timestamp(1621328543, 1), "signature" : { "hash" : BinData(0,"AAAAAAAAAAAAAAAAAAAAAAAAAAA="), "keyId" : NumberLong(0) } }, "operationTime" : Timestamp(1621328543, 1) } |
可以看到通过文本索引可以查到包含 测试 关键字的数据。
**注意：**可以根据自己需要创建复合文本索引。
2dsphere索引
创建测试数据
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db.places.insert( { loc : { type: "Point", coordinates: [ 116.291226, 39.981198 ] }, name: "火器营桥", category : "火器营桥" } )
db.places.insert( { loc : { type: "Point", coordinates: [ 116.281452, 39.914226 ] }, name: "五棵松", category : "五棵松" } )
db.places.insert( { loc : { type: "Point", coordinates: [ 116.378038, 39.851467 ] }, name: "角门西", category : "角门西" } )
db.places.insert( { loc : { type: "Point", coordinates: [ 116.467833, 39.881581 ] }, name: "潘家园", category : "潘家园" } )
db.places.insert( { loc : { type: "Point", coordinates: [ 116.468264, 39.914766 ] }, name: "国贸", category : "国贸" } )
db.places.insert( { loc : { type: "Point", coordinates: [ 116.46618, 39.960213 ] }, name: "三元桥", category : "三元桥" } )
db.places.insert( { loc : { type: "Point", coordinates: [ 116.400064, 40.007827 ] }, name: "奥林匹克森林公园", category : "奥林匹克森林公园" } ) |
添加2dsphere索引
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db.places.createIndex( { loc : "2dsphere" } ) |
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db.places.createIndex( { loc : "2dsphere" , category : -1, name: 1 } ) |
利用2dsphere索引查询多边形里的点
凤凰岭
[116.098234,40.110569]
天安门
[116.405239,39.913839]
四惠桥
[116.494351,39.912068]
望京
[116.494494,40.004594]
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handong1:PRIMARY> db.places.find( { loc : ... { $geoWithin : ... { $geometry : ... { type : "Polygon" , ... coordinates : [ [ ... [116.098234,40.110569] , ... [116.405239,39.913839] , ... [116.494351,39.912068] , ... [116.494494,40.004594] , ... [116.098234,40.110569] ... ] ] ... } } } } ) { "_id" : ObjectId("60a4c950d4211a77d22bf7f8"), "loc" : { "type" : "Point", "coordinates" : [ 116.400064, 40.007827 ] }, "name" : "奥林匹克森林公园", "category" : "奥林匹克森林公园" } { "_id" : ObjectId("60a4c94fd4211a77d22bf7f7"), "loc" : { "type" : "Point", "coordinates" : [ 116.46618, 39.960213 ] }, "name" : "三元桥", "category" : "三元桥" } { "_id" : ObjectId("60a4c94fd4211a77d22bf7f6"), "loc" : { "type" : "Point", "coordinates" : [ 116.468264, 39.914766 ] }, "name" : "国贸", "category" : "国贸" } |
可以看到把集合中包含在指定四边形里的点，全部列了出来。
利用2dsphere索引查询球体上定义的圆内的点
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handong1:PRIMARY> db.places.find( { loc : ... { $geoWithin : ... { $centerSphere : ... [ [ 116.439518, 39.954751 ] , 2/3963.2 ] ... } } } ) { "_id" : ObjectId("60a4c94fd4211a77d22bf7f7"), "loc" : { "type" : "Point", "coordinates" : [ 116.46618, 39.960213 ] }, "name" : "三元桥", "category" : "三元桥" } |
返回所有半径为经度 116.439518 E 和纬度 39.954751 N 的2英里内坐标。示例将2英里的距离转换为弧度，通过除以地球近似的赤道半径3963.2英里。
2d索引
在以下情况下使用2d索引：
您的数据库具有来自MongoDB 2.2或更早版本的旧版旧版坐标对。 您不打算将任何位置数据存储为GeoJSON对象。
哈希索引
要创建hashed索引，请指定 hashed 作为索引键的值， 如下例所示：
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handong1:PRIMARY> db.test.createIndex({"_id":"hashed"}) { "createdCollectionAutomatically" : false, "numIndexesBefore" : 4, "numIndexesAfter" : 5, "ok" : 1, "$clusterTime" : { "clusterTime" : Timestamp(1621419338, 1), "signature" : { "hash" : BinData(0,"AAAAAAAAAAAAAAAAAAAAAAAAAAA="), "keyId" : NumberLong(0) } }, "operationTime" : Timestamp(1621419338, 1) } |
注意事项
MongoDB支持任何单个字段的 hashed 索引。hashing函数折叠嵌入的文档并计算整个值的hash值，但不支持多键(即.数组)索引。 您不能创建具有hashed索引字段的复合索引，也不能在索引上指定唯一约束hashed；但是，您可以hashed在同一字段上创建索引和升序/降序（即非哈希）索引：MongoDB将对范围查询使用标量索引。到此这篇关于MongoDB索引类型汇总分享的文章就介绍到这了,更多相关MongoDB索引内容请搜索服务器之家以前的文章或继续浏览下面的相关文章希望大家以后多多支持服务器之家！
原文链接：https://blog.51cto.com/u_12592884/2786578