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。
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w3xue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w3xue!