MongoDB索引类型怎么实现

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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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