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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
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
handong1:PRIMARY> db.test.createIndex({"id":1}){"createdCollectionAutomatically" : false,"numIndexesBefore" : 1,"numIndexesAfter" : 2,"ok" : 1,"$clusterTime" : {"clusterTime" : Timestamp(1621322378, 1),"signature" : {"hash" : BinData(0,"AAAAAAAAAAAAAAAAAAAAAAAAAAA="),"keyId" : NumberLong(0)}},"operationTime" : Timestamp(1621322378, 1)}handong1:PRIMARY> db.test.getIndexes()[{"v" : 2,"key" : {"_id" : 1},"name" : "_id_","ns" : "db6.test"},{"v" : 2,"key" : {"id" : 1},"name" : "id_1","ns" : "db6.test"}]handong1:PRIMARY> db.test.find({"id":100}){ "_id" : ObjectId("60a35d061f183b1d8f092114"), "id" : 100, "name" : "handong", "ziliao" : { "name" : "handong", "age" : 25, "hobby" : "mongodb" } }上述查询可以使用新建的单字段索引。
在嵌入式字段上创建索引
handong1:PRIMARY> db.test.createIndex({"ziliao.name":1}){"createdCollectionAutomatically" : false,"numIndexesBefore" : 2,"numIndexesAfter" : 3,"ok" : 1,"$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。
db.test.find({"ziliao.name":"handong"})在内嵌文档上创建索引
handong1:PRIMARY> db.test.createIndex({ziliao:1}){"createdCollectionAutomatically" : false,"numIndexesBefore" : 3,"numIndexesAfter" : 4,"ok" : 1,"$clusterTime" : {"clusterTime" : Timestamp(1621324059, 2),"signature" : {"hash" : BinData(0,"AAAAAAAAAAAAAAAAAAAAAAAAAAA="),"keyId" : NumberLong(0)}},"operationTime" : Timestamp(1621324059, 2)}以下查询可以使用新建的索引。
db.test.find({ziliao:{ "name" : "handong", "age" : 25, "hobby" : "mongodb" }})复合索引
创建复合索引
db.user.createIndex({"product_id":1,"type":-1})以下查询可以用到新建的复合索引
db.user.find({"product_id":"e5a35cfc70364d2092b8f5d14b1a3217","type":0})多键索引
基于一个数组创建索引，MongoDB会自动创建为多键索引，无需刻意指定。
多键索引也可以基于内嵌文档来创建。
多键索引的边界值的计算依赖于特定的规则。
查看文档：
handong1:PRIMARY> db.score.find(){ "_id" : ObjectId("60a32d7f1f183b1d8f0920ad"), "name" : "dandan", "age" : 30, "score" : [ { "english" : 90, "math" : 99, "physics" : 88 } ], "is_del" : false }{ "_id" : ObjectId("60a32d8b1f183b1d8f0920ae"), "name" : "dandan", "age" : 30, "score" : [ 99, 98, 97, 96 ], "is_del" : false }{ "_id" : ObjectId("60a32d9a1f183b1d8f0920af"), "name" : "dandan", "age" : 30, "score" : [ 100, 100, 100, 100 ], "is_del" : false }{ "_id" : ObjectId("60a32e8c1f183b1d8f0920b0"), "name" : "dandan", "age" : 30, "score" : [ { "english" : 70, "math" : 99, "physics" : 88 } ], "is_del" : false }{ "_id" : ObjectId("60a37b141f183b1d8f0aa751"), "name" : "dandan", "age" : 30, "score" : [ 96, 95 ] }{ "_id" : ObjectId("60a37b1d1f183b1d8f0aa752"), "name" : "dandan", "age" : 30, "score" : [ 96, 95, 94 ] }{ "_id" : ObjectId("60a37b221f183b1d8f0aa753"), "name" : "dandan", "age" : 30, "score" : [ 96, 95, 94, 93 ] }创建score字段多键索引：
db.score.createIndex("score":1)handong1:PRIMARY> db.score.find({"score":[ 96, 95 ]}){ "_id" : ObjectId("60a37b141f183b1d8f0aa751"), "name" : "dandan", "age" : 30, "score" : [ 96, 95 ] }查看执行计划：
handong1:PRIMARY> db.score.find({"score":[ 96, 95 ]}).explain(){"queryPlanner" : {"plannerVersion" : 1,"namespace" : "db6.score","indexFilterSet" : false,"parsedQuery" : {"score" : {"$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
db.user.createIndex({"sku_attributes":"text"})db.user.find({$text:{$search:"测试"}})查看执行计划：
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
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
db.places.createIndex( { loc : "2dsphere" } )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]
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
handong1:PRIMARY> db.places.find( { loc :... { $geoWithin :... { $centerSphere :... [ [ 116.439518, 39.954751 ] , 2/3963.2 ]... } } } ){ "_id" : ObjectId("60a4c94fd4211a77d22bf7f7"), "loc" : { "type" : "Point", "coordinates" : [ 116.46618, 39.960213 ] }, "name" : "三元桥", "category" : "三元桥" }返回所有半径为经度 116.439518 E 和纬度 39.954751 N 的2英里内坐标。示例将2英里的距离转换为弧度，通过除以地球近似的赤道半径3963.2英里。
2d索引
在以下情况下使用2d索引：
您的数据库具有来自MongoDB 2.2或更早版本的旧版旧版坐标对。
您不打算将任何位置数据存储为GeoJSON对象。
哈希索引
要创建hashed索引，请指定 hashed 作为索引键的值，如下例所示：
handong1:PRIMARY> db.test.createIndex({"_id":"hashed"}){"createdCollectionAutomatically" : false,"numIndexesBefore" : 4,"numIndexesAfter" : 5,"ok" : 1,"$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。
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