? ??? MongoDB? ???? MongoDB? ??? ??? ??? ???? ? ??? ? ????.

MongoDB? ???? MySql? ???? ????? ??? ??? ??? ???, MySql? ????? ?? ?????. <code>MongoDB的索引和MySql的索引的作用和優(yōu)化要遵循的原則基本相似,MySql索引類型基本可以區(qū)分為:

• 單鍵索引 - 聯(lián)合索引
• 主鍵索引(聚簇索引) - 非主鍵索引(非聚簇索引)

在MongoDB中除了這些基礎的分類之外,還有一些特殊的索引類型,如: 數組索引 | 稀疏索引 | 地理空間索引 | TTL索引等.

為了下面方便測試我們使用腳本插入以下數據

for(var i = 0;i < 100000;i++){
    db.users.insertOne({
        username: "user"+i,
        age: Math.random() * 100,
        sex: i % 2,
        phone: 18468150001+i
    });
}

單鍵索引

單鍵索引即索引的字段只有一個,是最基礎的索引方式.

在集合中使用username字段,創(chuàng)建一個單鍵索引,MongoDB會自動將這個索引命名為username_1

db.users.createIndex({username:1})
'username_1'

在創(chuàng)建索引后查看一下使用username字段的查詢計劃,stage為IXSCAN代表使用使用了索引掃描

db.users.find({username:"user40001"}).explain()
{ 
   queryPlanner: 
   { 
     winningPlan: 
     { 
        ......
        stage: 'FETCH',
        inputStage: 
        { 
           stage: 'IXSCAN',
           keyPattern: { username: 1 },
           indexName: 'username_1',
           ......
        } 
     }
     rejectedPlans: [] ,
   },
   ......
   ok: 1 
}

在索引優(yōu)化的原則當中,有很重要的原則就是索引要建立在基數高的的字段上,所謂基數就是一個字段上不重復數值的個數,即我們在創(chuàng)建users集合時年齡出現的數值是0-99那么age這個字段將會有100個不重復的數值,即age字段的基數為100,而sex這個字段只會出現0 | 1這個兩個值,即sex字段的基礎是2,這是一個相當低的基數,在這種情況下,索引的效率并不高并且會導致索引失效.

下面就船艦一個sex字段索引,來查詢執(zhí)行計劃會發(fā)現,查詢時是走的全表掃描,而沒有走相關索引.

db.users.createIndex({sex:1})
'sex_1'

db.users.find({sex:1}).explain()
{ 
  queryPlanner: 
  { 
     ......
     winningPlan: 
     { 
        stage: 'COLLSCAN',
        filter: { sex: { '$eq': 1 } },
        direction: 'forward' 
     },
     rejectedPlans: [] 
  },
  ......
  ok: 1 
}

聯(lián)合索引

聯(lián)合索引即索引上會有多個字段,下面使用age和sex兩個字段創(chuàng)建一個索引

db.users.createIndex({age:1,sex:1})
'age_1_sex_1'

然后我們使用這兩個字段進行一次查詢,查看執(zhí)行計劃,順利地走了這條索引

db.users.find({age:23,sex:1}).explain()
{ 
  queryPlanner: 
  { 
     ......
     winningPlan: 
     { 
        stage: 'FETCH',
        inputStage: 
        { 
           stage: 'IXSCAN',
           keyPattern: { age: 1, sex: 1 },
           indexName: 'age_1_sex_1',
           .......
           indexBounds: { age: [ '[23, 23]' ], sex: [ '[1, 1]' ] } 
        } 
     },
     rejectedPlans: [], 
  },
  ......
  ok: 1 
 }

數組索引

數組索引就是對數組字段創(chuàng)建索引,也叫做多值索引,下面為了測試將users集合中的數據增加一部分數組字段.

db.users.updateOne({username:"user1"},{$set:{hobby:["唱歌","籃球","rap"]}})
......

創(chuàng)建數組索引并進行查看其執(zhí)行計劃,注意isMultiKey: true表示使用的索引是多值索引.

db.users.createIndex({hobby:1})
'hobby_1'

db.users.find({hobby:{$elemMatch:{$eq:"釣魚"}}}).explain()
{ 
   queryPlanner: 
   { 
     ......
     winningPlan: 
     { 
        stage: 'FETCH',
        filter: { hobby: { '$elemMatch': { '$eq': '釣魚' } } },
        inputStage: 
        { 
           stage: 'IXSCAN',
           keyPattern: { hobby: 1 },
           indexName: 'hobby_1',
           isMultiKey: true,
           multiKeyPaths: { hobby: [ 'hobby' ] },
           ......
           indexBounds: { hobby: [ '["釣魚", "釣魚"]' ] } } 
         },
     rejectedPlans: [] 
  },
  ......
  ok: 1 
}

數組索引相比于其它索引來說索引條目和體積必然呈倍數增加,例如平均每個文檔的hobby數組的size為10,那么這個集合的hobby數組索引的條目數量將是普通索引的10倍.

聯(lián)合數組索引

聯(lián)合數組索引就是含有數組字段的聯(lián)合索引,這種索引不支持一個索引中含有多個數組字段,即一個索引中最多能有一個數組字段,這是為了避免索引條目爆炸式增長,假設一個索引中有兩個數組字段,那么這個索引條目的數量將是普通索引的n*m倍

地理空間索引

在原先的users集合上,增加一些地理信息

for(var i = 0;i < 100000;i++){
    db.users.updateOne(
    {username:"user"+i},
    {
        $set:{
            location:{
                type: "Point",
                coordinates: [100+Math.random() * 4,40+Math.random() * 3]
            }
        }
    });
}

創(chuàng)建一個二維空間索引

db.users.createIndex({location:"2dsphere"})
'location_2dsphere'

//查詢500米內的人
db.users.find({
  location:{
    $near:{
      $geometry:{type:"Point",coordinates:[102,41.5]},
      $maxDistance:500
    }
  }
})

地理空間索引的type有很多包含Ponit(點) | LineString(線) | Polygon(多邊形) 等

TTL索引

TTL的全拼是time to live,主要是用于過期數據自動刪除,使用這種索引需要在文檔中聲明一個時間類型的字段,然后為這個字段創(chuàng)建TTL索引的時候還需要設置一個expireAfterSeconds過期時間單位為秒,創(chuàng)建完成后MongoDB

• ?? ? ??? - ?? ???
• ?? ? ???(????? ???) - ??? ? ???(?????? ???)< /li>

for(var i = 90000;i < 100000;i++){
    db.users.updateOne(
    {username:"user"+i},
    {
        $set:{
            createdDate:new Date()
        }
    });
}

?? ? ???

db.users.createIndex({createdDate:1},{expireAfterSeconds:60})
'createdDate_1'

db.users.createIndex({username:1},{partialFilterExpression:{
    age:{$gt:50}
  }})
'username_1'

db.users.find({$and:[{username:"user4"},{age:60}]}).explain()
{ 
  queryPlanner: 
  { 
     ......
     winningPlan: 
     { 
        stage: 'FETCH',
        filter: { age: { '$eq': 60 } },
        inputStage: 
        { 
           stage: 'IXSCAN',
           keyPattern: { username: 1 },
           indexName: 'username_1',
           ......
           isPartial: true,
           ......
         } 
     },
     rejectedPlans: [] 
  },
  ......
  ok: 1 
}

?? ???

for(var i = 5000;i < 10000;i++){
  if(i < 9000){
    db.users.updateOne(
      {username:"user"+i},
      { $set:{email:(120000000+i)+"@qq.email"}}
    )
  }else{
    db.users.updateOne(
      {username:"user"+i},
      { $set:{email:null}}
    )
  }
}

db.users.find({email:null})
{ 
  _id: ObjectId("61bdc01ba59136670f6536fd"),
  username: 'user0',
  age: 64.41483801726282,
  sex: 0,
  phone: 18468150001,
  location: 
  { 
    type: 'Point',
    coordinates: [ 101.42490900320335, 42.2576650823515 ] 
  } 
}
......

?? ???

db.users.createIndex({email:1},{sparse:true});
'email_1'

db.users.find({email:null}).hint({email:1})
{ 
  _id: ObjectId("61bdc12ca59136670f655a25"),
  username: 'user9000',
  age: 94.18397576757012,
  sex: 0,
  phone: 18468159001,
  hobby: [ '釣魚', '乒乓球' ],
  location: 
  { 
    type: 'Point',
    coordinates: [ 101.25903151863596, 41.38450145025062 ] 
  },
  email: null 
}
......

db.blog.insertMany([
  {title:"hello world",content:"mongodb is the best database"},
  {title:"index",content:"efficient data structure"}
])

//創(chuàng)建索引
db.blog.createIndex({title:"text",content:"text"})
'title_text_content_text'
//使用文本索引查詢
db.blog.find({$text:{$search:"hello data"}})
{ 
  _id: ObjectId("61c092268c4037d17827d977"),
  title: 'index',
  content: 'efficient data structure' 
},
{ 
  _id: ObjectId("61c092268c4037d17827d976"),
  title: 'hello world',
  content: 'mongodb is the best database' 
}

//對title字段創(chuàng)建唯一索引
db.blog.createIndex({title:1},{unique:true})
'title_1'
//插入一個已經存在的title值
db.blog.insertOne({title:"hello world",content:"mongodb is the best database"})
MongoServerError: E11000 duplicate key error collection: mock.blog index: title_1 dup key: { : "hello world" }
//查看一下執(zhí)行計劃,isUnique為true
db.blog.find({"title":"index"}).explain()
{ 
  queryPlanner: 
  { 
     ......
     winningPlan: 
     { 
        stage: 'FETCH',
        inputStage: 
        { 
           stage: 'IXSCAN',
           keyPattern: { title: 1 },
           indexName: 'title_1',
           isMultiKey: false,
           multiKeyPaths: { title: [] },
           isUnique: true,
           ......
         } 
     },
     rejectedPlans: [] 
  },
  .......
  ok: 1 
}

TTL ??? Strong>

for(var i = 90000;i < 100000;i++){
    db.users.updateOne(
    {username:"user"+i},
    {
        $set:{
            createdDate:new Date()
        }
    });
}

db.users.createIndex({createdDate:1},{expireAfterSeconds:60})
'createdDate_1'

db.runCommand({
  collMod:"users",
  index:{
    keyPattern:{createdDate:1},
    expireAfterSeconds:120
  }
})

{ expireAfterSeconds_old: 60, expireAfterSeconds_new: 120, ok: 1 }

db.users.createIndex({username:1},{partialFilterExpression:{
    age:{$gt:50}
  }})
'username_1'

db.users.find({$and:[{username:"user4"},{age:60}]}).explain()
{ 
  queryPlanner: 
  { 
     ......
     winningPlan: 
     { 
        stage: 'FETCH',
        filter: { age: { '$eq': 60 } },
        inputStage: 
        { 
           stage: 'IXSCAN',
           keyPattern: { username: 1 },
           indexName: 'username_1',
           ......
           isPartial: true,
           ......
         } 
     },
     rejectedPlans: [] 
  },
  ......
  ok: 1 
}

for(var i = 5000;i < 10000;i++){
  if(i < 9000){
    db.users.updateOne(
      {username:"user"+i},
      { $set:{email:(120000000+i)+"@qq.email"}}
    )
  }else{
    db.users.updateOne(
      {username:"user"+i},
      { $set:{email:null}}
    )
  }
}

db.users.find({email:null})
{ 
  _id: ObjectId("61bdc01ba59136670f6536fd"),
  username: 'user0',
  age: 64.41483801726282,
  sex: 0,
  phone: 18468150001,
  location: 
  { 
    type: 'Point',
    coordinates: [ 101.42490900320335, 42.2576650823515 ] 
  } 
}
......

db.users.createIndex({email:1},{sparse:true});
'email_1'

db.users.find({email:null}).hint({email:1})
{ 
  _id: ObjectId("61bdc12ca59136670f655a25"),
  username: 'user9000',
  age: 94.18397576757012,
  sex: 0,
  phone: 18468159001,
  hobby: [ '釣魚', '乒乓球' ],
  location: 
  { 
    type: 'Point',
    coordinates: [ 101.25903151863596, 41.38450145025062 ] 
  },
  email: null 
}
......

db.blog.insertMany([
  {title:"hello world",content:"mongodb is the best database"},
  {title:"index",content:"efficient data structure"}
])

//創(chuàng)建索引
db.blog.createIndex({title:"text",content:"text"})
'title_text_content_text'
//使用文本索引查詢
db.blog.find({$text:{$search:"hello data"}})
{ 
  _id: ObjectId("61c092268c4037d17827d977"),
  title: 'index',
  content: 'efficient data structure' 
},
{ 
  _id: ObjectId("61c092268c4037d17827d976"),
  title: 'hello world',
  content: 'mongodb is the best database' 
}

//對title字段創(chuàng)建唯一索引
db.blog.createIndex({title:1},{unique:true})
'title_1'
//插入一個已經存在的title值
db.blog.insertOne({title:"hello world",content:"mongodb is the best database"})
MongoServerError: E11000 duplicate key error collection: mock.blog index: title_1 dup key: { : "hello world" }
//查看一下執(zhí)行計劃,isUnique為true
db.blog.find({"title":"index"}).explain()
{ 
  queryPlanner: 
  { 
     ......
     winningPlan: 
     { 
        stage: 'FETCH',
        inputStage: 
        { 
           stage: 'IXSCAN',
           keyPattern: { title: 1 },
           indexName: 'title_1',
           isMultiKey: false,
           multiKeyPaths: { title: [] },
           isUnique: true,
           ......
         } 
     },
     rejectedPlans: [] 
  },
  .......
  ok: 1 
}