索引

MongoDB 的索引是基于 B-tree 数据结构及对应算法形成的。_id默认会创建索引

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索引类型

单列索引

除了 MongoDB 定义的 _id 索引之外，MongoDB 还支持在文档的单个字段上创建用户定义的升序/降序索引。

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>db.collection.createlndex ( { source: 1 } )  //1 为升序，-1 为降序

复合索引

MongoDB 也支持复合索引，并且复合索引的规则和MySQL基本一致。复合索引中列出的字段顺序具有重要意义。例如，如果复合索引由 { userid: 1, score: -1 } 组成，则索引首先按userid正序排序，然后在每个userid的值内，再在按score倒序排序。

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>db.collection.createIndex ({ "score": -1, "userid": 1 })

多键索引

若要为包含数组的字段建立索引，MongoDB 会为数组中的每个元素创建索引键。这些多键值索引支持对数组字段的高效查询

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索引新增删除

创建索引

db.collection.createIndex( { name: -1 } )
db.user.getIndexes()
[
  { v: 2, key: { _id: 1 }, name: '_id_' },
  { v: 2, key: { name: 1 }, name: 'name_1' }
]
Atlas atlas-119lob-shard-0 [primary] test> db.user.createIndex({name: 1},{name:"idx_name"})
idx_name
Atlas atlas-119lob-shard-0 [primary] test> db.user.getIndexes()
[
  { v: 2, key: { _id: 1 }, name: '_id_' },
  { v: 2, key: { name: 1 }, name: 'idx_name' }
]

删除索引

db.user.dropIndexes("name_1")

执行计划

explain有三种模式，分别是：queryPlanner、executionStats、allPlansExecution。

queryPlanner：输出索引的候选索引，包括最优索引及其执行stage过程(winningPlan)+其他非最优候选索引及其执行stage过程
executionStats：相比queryPlanner参数，executionStats会记录查询优化器根据所选最优索引执行SQL的整个过程信息，会真正执行整个SQL。
allPlansExecution：和executionStats类似，只是多了所有候选索引的执行过程

新增10000条测试数据

for (let i = 1; i <= 500000; i++) db.item.insertOne({_id:i, item_id: "10010_" + i, item_order: "P1HNHN" + i, test:"test_"+i+"TES"})

Atlas atlas-119lob-shard-0 [primary] order> db.item.find({item_id:"10010_38976"}).explain("executionStats")
{
  explainVersion: '1',
  queryPlanner: {
    namespace: 'order.item',
    indexFilterSet: false,
    parsedQuery: { item_id: { '$eq': '10010_38976' } },
    maxIndexedOrSolutionsReached: false,
    maxIndexedAndSolutionsReached: false,
    maxScansToExplodeReached: false,
    winningPlan: {
      stage: 'COLLSCAN',
      filter: { item_id: { '$eq': '10010_38976' } },
      direction: 'forward'
    },
    rejectedPlans: []
  },
  executionStats: {
    executionSuccess: true,
    nReturned: 1,
    executionTimeMillis: 23,
    totalKeysExamined: 0,
    totalDocsExamined: 50000,
    executionStages: {
      stage: 'COLLSCAN',
      filter: { item_id: { '$eq': '10010_38976' } },
      nReturned: 1,
      executionTimeMillisEstimate: 2,
      works: 50002,
      advanced: 1,
      needTime: 50000,
      needYield: 0,
      saveState: 50,
      restoreState: 50,
      isEOF: 1,
      direction: 'forward',
      docsExamined: 50000
    }
  },
  command: { find: 'item', filter: { item_id: '10010_38976' }, '$db': 'order' },
  serverInfo: {
    host: 'cluster0-shard-00-02.fdv5c.mongodb.net',
    port: 27017,
    version: '5.0.8',
    gitVersion: 'c87e1c23421bf79614baf500fda6622bd90f674e'
  },
  serverParameters: {
    internalQueryFacetBufferSizeBytes: 104857600,
    internalQueryFacetMaxOutputDocSizeBytes: 104857600,
    internalLookupStageIntermediateDocumentMaxSizeBytes: 16793600,
    internalDocumentSourceGroupMaxMemoryBytes: 104857600,
    internalQueryMaxBlockingSortMemoryUsageBytes: 33554432,
    internalQueryProhibitBlockingMergeOnMongoS: 0,
    internalQueryMaxAddToSetBytes: 104857600,
    internalDocumentSourceSetWindowFieldsMaxMemoryBytes: 104857600
  },
  ok: 1,
  '$clusterTime': {
    clusterTime: Timestamp(1, 1651821606),
    signature: {
      hash: Binary(Buffer.from("9250e56618dba0aacb504c846045c8e534adb68f", "hex"), 0),
      keyId: Long("7066952799589761026")
    }
  },
  operationTime: Timestamp(1, 1651821606)
}

在item_id上创建索引

db.item.createIndex ({ "item_id": 1},{"name":"idx_item_id" })

Atlas atlas-119lob-shard-0 [primary] order> db.item.find({item_id:"10010_38976"}).explain("executionStats")
{
  explainVersion: '1',
  queryPlanner: {
    namespace: 'order.item',
    indexFilterSet: false,
    parsedQuery: { item_id: { '$eq': '10010_38976' } },
    maxIndexedOrSolutionsReached: false,
    maxIndexedAndSolutionsReached: false,
    maxScansToExplodeReached: false,
    winningPlan: {
      stage: 'FETCH',
      inputStage: {
        stage: 'IXSCAN',
        keyPattern: { item_id: 1 },
        indexName: 'idx_item_id',
        isMultiKey: false,
        multiKeyPaths: { item_id: [] },
        isUnique: false,
        isSparse: false,
        isPartial: false,
        indexVersion: 2,
        direction: 'forward',
        indexBounds: { item_id: [ '["10010_38976", "10010_38976"]' ] }
      }
    },
    rejectedPlans: []
  },
  executionStats: {
    executionSuccess: true,
    nReturned: 1,
    executionTimeMillis: 0,
    totalKeysExamined: 1,
    totalDocsExamined: 1,
    executionStages: {
      stage: 'FETCH',
      nReturned: 1,
      executionTimeMillisEstimate: 0,
      works: 2,
      advanced: 1,
      needTime: 0,
      needYield: 0,
      saveState: 0,
      restoreState: 0,
      isEOF: 1,
      docsExamined: 1,
      alreadyHasObj: 0,
      inputStage: {
        stage: 'IXSCAN',
        nReturned: 1,
        executionTimeMillisEstimate: 0,
        works: 2,
        advanced: 1,
        needTime: 0,
        needYield: 0,
        saveState: 0,
        restoreState: 0,
        isEOF: 1,
        keyPattern: { item_id: 1 },
        indexName: 'idx_item_id',
        isMultiKey: false,
        multiKeyPaths: { item_id: [] },
        isUnique: false,
        isSparse: false,
        isPartial: false,
        indexVersion: 2,
        direction: 'forward',
        indexBounds: { item_id: [ '["10010_38976", "10010_38976"]' ] },
        keysExamined: 1,
        seeks: 1,
        dupsTested: 0,
        dupsDropped: 0
      }
    }
  },
  command: { find: 'item', filter: { item_id: '10010_38976' }, '$db': 'order' },
  serverInfo: {
    host: 'cluster0-shard-00-02.fdv5c.mongodb.net',
    port: 27017,
    version: '5.0.8',
    gitVersion: 'c87e1c23421bf79614baf500fda6622bd90f674e'
  },
  serverParameters: {
    internalQueryFacetBufferSizeBytes: 104857600,
    internalQueryFacetMaxOutputDocSizeBytes: 104857600,
    internalLookupStageIntermediateDocumentMaxSizeBytes: 16793600,
    internalDocumentSourceGroupMaxMemoryBytes: 104857600,
    internalQueryMaxBlockingSortMemoryUsageBytes: 33554432,
    internalQueryProhibitBlockingMergeOnMongoS: 0,
    internalQueryMaxAddToSetBytes: 104857600,
    internalDocumentSourceSetWindowFieldsMaxMemoryBytes: 104857600
  },
  ok: 1,
  '$clusterTime': {
    clusterTime: Timestamp(2, 1651821695),
    signature: {
      hash: Binary(Buffer.from("035c24b6cc83e5d1d5bca97befb43a2c2fc30605", "hex"), 0),
      keyId: Long("7066952799589761026")
    }
  },
  operationTime: Timestamp(2, 1651821695)
}

事务

什么是writeConcern？

writeConcern 决定一个写操作落到多少个节点上才算成功。writeConcern 的取值包括：

0：发起写操作，不关心是否成功；
1~集群最大数据节点数：写操作需要被复制到指定节点数才算成功；
majority：写操作需要被复制到大多数节点上才算成功。

发起写操作的程序将阻塞到写操作到达指定的节点数为止

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majority

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副本集

MongoDB的副本集主要用于实现服务的高可用。

数据写入时将数据迅速复制到其他节点上
在Primary节点出现故障后自动选举一个Secondary节点作为Primary

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Golang操作MongoDB

var client *mongo.Client
type Item struct {
  ItemId string `bson:"item_id"`
  ItemOrder string `bson:"item_order"`
  Test string `bson:"test"`
  UpdateTime string `bson:"update_time"`
}
func main() {
  initDB()
  collection := client.Database("order").Collection("item")
  result, err := collection.InsertOne(context.TODO(), &Item{
    ItemId:     "test_item_id",
    ItemOrder:  "test_item_order",
    Test:       "test_test",
    UpdateTime: time.Now().Format("2006-01-02 15:04:05"),
  })
  if err != nil{
    log.Fatal(err)
  }
  fmt.Println(result.InsertedID)
  // find()
}
func find(){
  initDB()
  collection := client.Database("order").Collection("item")
  cursor, err := collection.Find(context.TODO(), bson.D{{"itemid", "test_item_id"}})
  if err != nil {
    log.Fatal(err)
  }
  defer cursor.Close(context.TODO())
  for cursor.Next(context.TODO()) {
    item := &Item{}
    err := cursor.Decode(item)
    if err != nil {
      log.Fatal(err)
    }
    fmt.Println(item)
  }
}
func initDB() {
  clientOptions := options.Client().ApplyURI(url)
  ctx, cancel := context.WithTimeout(context.Background(), 10*time.Second)
  defer cancel()
  c, err := mongo.Connect(ctx, clientOptions)
  if err != nil {
    log.Fatal(err)
  }
  err3 := c.Ping(ctx, nil)
  if err3 != nil {
    log.Fatal(err3)
  }
  fmt.Println("mongodb connected")
  client = c
}

【Mongo DB】万字详解，Mongo DB的简介到实战使用（下）

索引

索引类型

单列索引

复合索引

多键索引

索引新增删除

执行计划

事务

副本集

Golang操作MongoDB

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