多键索引
多键索引是专门针对数组字段的, 会为数组字段的每一个元素都创建一个索引。
?> 插入测试数据：
db.person.insert([
{name:'as', age:18, tags:['ahtml', 'bcss']},
{name:'bs', age:17, tags:['cjs', 'enode']},
{name:'cs', age:19, tags:[ 'dvue', 'freact']},
])
首先来看看我们没有创建多键索引之前的查询效果：
db.person.explain().find({'tags':{$in:['ahtml']}})
从如下结果集返回来看，是一个全表扫描的情况：
{
"queryPlanner" : {
"plannerVersion" : 1,
"namespace" : "test.person",
"indexFilterSet" : false,
"parsedQuery" : {
"tags" : {
"$eq" : "ahtml"
}
},
"winningPlan" : {
"stage" : "COLLSCAN",
"filter" : {
"tags" : {
"$eq" : "ahtml"
}
},
"direction" : "forward"
},
"rejectedPlans" : [ ]
},
"serverInfo" : {
"host" : "LAPTOP-A8CAC6IT",
"port" : 27017,
"version" : "4.0.28",
"gitVersion" : "af1a9dc12adcfa83cc19571cb3faba26eeddac92"
},
"ok" : 1
}
创建多键索引：
db.person.createIndex({tags:1})
再次进行查询：
db.person.explain().find({'tags':{$in:['ahtml']}})
返回结果：
{
"queryPlanner" : {
"plannerVersion" : 1,
"namespace" : "test.person",
"indexFilterSet" : false,
"parsedQuery" : {
"tags" : {
"$eq" : "ahtml"
}
},
"winningPlan" : {
"stage" : "FETCH",
"inputStage" : {
"stage" : "IXSCAN",
"keyPattern" : {
"tags" : 1
},
"indexName" : "tags_1",
"isMultiKey" : true,
"multiKeyPaths" : {
"tags" : [
"tags"
]
},
"isUnique" : false,
"isSparse" : false,
"isPartial" : false,
"indexVersion" : 2,
"direction" : "forward",
"indexBounds" : {
"tags" : [
"[\"ahtml\", \"ahtml\"]"
]
}
}
},
"rejectedPlans" : [ ]
},
"serverInfo" : {
"host" : "LAPTOP-A8CAC6IT",
"port" : 27017,
"version" : "4.0.28",
"gitVersion" : "af1a9dc12adcfa83cc19571cb3faba26eeddac92"
},
"ok" : 1
}
很明显是通过索引进行命中对应的数据。
在我们创建了对应了多键索引之后，我们插入的测试数据对应的数据结构大概的体系结构如下可以进行稍微了解了解：
'ahtml' -> {name:'as', age:18, tags:['ahtml', 'bcss']}
'bcss' -> {name:'as', age:18, tags:['ahtml', 'bcss']}
'cjs' -> {name:'bs', age:17, tags:['cjs', 'enode']}
'dvue' -> {name:'cs', age:19, tags:[ 'dvue', 'freact']}
'enode' -> {name:'bs', age:17, tags:['cjs', 'enode']}
'freact' -> {name:'cs', age:19, tags:[ 'dvue', 'freact']}
