mongodb基礎

時間  2019-12-10
標籤 mongodb 基礎 欄目 MongoDB 简体版
原文   原文鏈接

MongoDB在MAC下的安裝

  • 安裝html

  huijundeMacBook-Pro:~ huijunzhang$ brew install mongodb
  ...
  ==> Downloading https://homebrew.bintray.com/bottles/mongodb-3.2.9.el_capitan.bottle.tar.gz
  ######################################################################## 100.0%
  ==> Pouring mongodb-3.2.9.el_capitan.bottle.tar.gz
  ==> Caveats
  To have launchd start mongodb now and restart at login:
    brew services start mongodb
  Or, if you don't want/need a background service you can just run:
    mongod --config /usr/local/etc/mongod.conf
  ==> Summary
  🍺  /usr/local/Cellar/mongodb/3.2.9: 17 files, 241.2M

 

  • 啓動MongoDB正則表達式

    上面提示的直接啓動mongo的方法sql

mongod --config /usr/local/etc/mongod.conf

 

具體操做以下：mongodb

huijundeMacBook-Pro:~ huijunzhang$ mongod --config /usr/local/etc/mongod.conf &
[1] 19869
huijundeMacBook-Pro:~ huijunzhang$ mongo
MongoDB shell version: 3.2.9
connecting to: test
Welcome to the MongoDB shell.
For interactive help, type "help".
For more comprehensive documentation, see
    http://docs.mongodb.org/
Questions? Try the support group
    http://groups.google.com/group/mongodb-user
Server has startup warnings: 
2016-08-31T09:30:34.820+0800 I CONTROL  [initandlisten] 
2016-08-31T09:30:34.820+0800 I CONTROL  [initandlisten] ** WARNING: soft rlimits too low. Number of files is 256, should be at least 1000

 

到此，mongoDB在mac下的安裝就完成了shell

1、基本操做

mongodb中的基本操做無非就是增刪改查，看下邊數據庫

insert：

> db.table_name.insert({"name":"zhj","age":20,"province":"henan"})
WriteResult({ "nInserted" : 1 })
> db.table_name.insert({"name":"zjf","age":18,"province":"beijing"})
WriteResult({ "nInserted" : 1 })
> db.table_name.insert({"name":"zg","age":22,"province":"beijing"})
WriteResult({ "nInserted" : 1 })

 

mongo不支持批量插入，若是須要批量插入，就使用for循環操做api

find：

> db.table_name.find()
{ "_id" : ObjectId("57c6364278935e710c61131b"), "name" : "zhj", "age" : 20, "province" : "henan" }
{ "_id" : ObjectId("57c6365e78935e710c61131c"), "name" : "zjf", "age" : 18, "province" : "beijing" }
{ "_id" : ObjectId("57c6366e78935e710c61131d"), "name" : "zg", "age" : 22, "province" : "beijing" }

 

  • "無關鍵字","$ne","$gt","$gte","$lt","$lte"

sql | mongo | 說明 | ---|---|---|數組

|$gt |大於 =|$gte|大於等於 < |$lt |小於 <=|$lte|小於等於 !=|$ne |不等於 ==| |等於函數

#select * from table_name where age == 20
db.table_name.find({"age":20})
#select * from table_name where age != 20
db.table_name.find({"age":{$ne:20}})
#select * from table_name where age > 20
db.table_name.find({"age":{$gt:20}})
#select * from table_name where age < 20
db.table_name.find({"age":{$lt:20}})
#select * from table_name where age >= 20
db.table_name.find({"age":{$gte:20}})
#select * from table_name where age <= 20
db.table_name.find({"age":{$lte:20}})

# 具體操做以下
> db.table_name.find({"age":20})
{ "_id" : ObjectId("57c6364278935e710c61131b"), "name" : "zhj", "age" : 20, "province" : "henan" }
> db.table_name.find({"age":{$ne:20}})
{ "_id" : ObjectId("57c6365e78935e710c61131c"), "name" : "zjf", "age" : 18, "province" : "beijing" }
{ "_id" : ObjectId("57c6366e78935e710c61131d"), "name" : "zg", "age" : 22, "province" : "beijing" }
> db.table_name.find({"age":{$gt:20}})
{ "_id" : ObjectId("57c6366e78935e710c61131d"), "name" : "zg", "age" : 22, "province" : "beijing" }
> db.table_name.find({"age":{$lt:20}})
{ "_id" : ObjectId("57c6365e78935e710c61131c"), "name" : "zjf", "age" : 18, "province" : "beijing" }
> db.table_name.find({"age":{$gte:20}})
{ "_id" : ObjectId("57c6364278935e710c61131b"), "name" : "zhj", "age" : 20, "province" : "henan" }
{ "_id" : ObjectId("57c6366e78935e710c61131d"), "name" : "zg", "age" : 22, "province" : "beijing" }
> db.table_name.find({"age":{$lte:20}})
{ "_id" : ObjectId("57c6364278935e710c61131b"), "name" : "zhj", "age" : 20, "province" : "henan" }
{ "_id" : ObjectId("57c6365e78935e710c61131c"), "name" : "zjf", "age" : 18, "province" : "beijing" }

 

  • "無關鍵字" ,"$or", "$in","$nin"
sql mongo 說明
and    
or $or  
in $in  
not in $nin   
db.table_name.find({"name":"zhj","province":"henan"})
db.table_name.find({$or:[{"province":"henan"},{"province":"beijing"}]})
db.table_name.find({"province":{$in:["henan","beijing"]}})
db.table_name.find({"province":{$nin:["henan","beijing"]}})

# 具體操做以下
> db.table_name.find({"name":"zhj","province":"henan"})
{ "_id" : ObjectId("57c6364278935e710c61131b"), "name" : "zhj", "age" : 20, "province" : "henan" }
> db.table_name.find({$or:[{"province":"henan"},{"province":"beijing"}]})
{ "_id" : ObjectId("57c6364278935e710c61131b"), "name" : "zhj", "age" : 20, "province" : "henan" }
{ "_id" : ObjectId("57c6365e78935e710c61131c"), "name" : "zjf", "age" : 18, "province" : "beijing" }
{ "_id" : ObjectId("57c6366e78935e710c61131d"), "name" : "zg", "age" : 22, "province" : "beijing" }
> db.table_name.find({"province":{$in:["henan","beijing"]}})
{ "_id" : ObjectId("57c6364278935e710c61131b"), "name" : "zhj", "age" : 20, "province" : "henan" }
{ "_id" : ObjectId("57c6365e78935e710c61131c"), "name" : "zjf", "age" : 18, "province" : "beijing" }
{ "_id" : ObjectId("57c6366e78935e710c61131d"), "name" : "zg", "age" : 22, "province" : "beijing" }
> db.table_name.find({"province":{$nin:["henan","beijing"]}})
>

 

  • 正則表達式sqlserver

  匹配以'j'開頭，'e'結尾的
  db.table_name.find({"name":/^j/,"name":/e$/})

  > db.table_name.find({"name":/^j/,"name":/g$/})
  { "_id" : ObjectId("57c6366e78935e710c61131d"), "name" : "zg", "age" : 22, "province" : "beijing" }

 

  • $where

$where中的value就是咱們經常使用的js

  # find name='zhj'
  db.table_name.find({$where:function(){return this.name == 'zhj'}})

  # 具體操做以下      
  > db.table_name.find({$where:function(){return this.name == 'zhj'}})
  { "_id" : ObjectId("57c6364278935e710c61131b"), "name" : "zhj", "age" : 20, "province" : "henan" }

 

update:

db.table_name.insert({"name":"zhj"},{"name":"zhj","age":18})

 

  • 總體更新：

     var model = db.table_name.findOne({"name":"zhj"})
  model.age = 30
  db.table_name.update({"name":"zhj"},model)

  # 具體操做以下
  > var model = db.table_name.findOne({"name":"zhj"})
  > model.age = 30
  30
  > db.table_name.update({"name":"zhj"},model)
  WriteResult({ "nMatched" : 1, "nUpserted" : 0, "nModified" : 1 })
  > db.table_name.find()
  { "_id" : ObjectId("57c6364278935e710c61131b"), "name" : "zhj", "age" : 30, "province" : "henan" }
  { "_id" : ObjectId("57c6365e78935e710c61131c"), "name" : "zjf", "age" : 18, "province" : "beijing" }
  { "_id" : ObjectId("57c6366e78935e710c61131d"), "name" : "zg", "age" : 22, "province" : "beijing" }

     

  • 局部更新：

　　① $inc修改器

$inc也就是increase的縮寫，學過sqlserver的同窗應該很熟悉，好比咱們作一個在線用戶狀態記錄，每次修改會在原有的基礎上自增$inc指定的值，若是「文檔」中沒有此key，則會建立key，下面的例子一看就懂。

# 原數據的age=20，執行完下面語句，age=50，在原來的基礎上加了30
db.table_name.update({"name":"zhj"},{$inc:{"age":30}})

# 具體操做以下
> db.table_name.find()
{ "_id" : ObjectId("57c6364278935e710c61131b"), "name" : "zhj", "age" : 30, "province" : "henan" }
{ "_id" : ObjectId("57c6365e78935e710c61131c"), "name" : "zjf", "age" : 18, "province" : "beijing" }
{ "_id" : ObjectId("57c6366e78935e710c61131d"), "name" : "zg", "age" : 22, "province" : "beijing" }
> db.table_name.update({"name":"zhj"},{$inc:{"age":30}})
WriteResult({ "nMatched" : 1, "nUpserted" : 0, "nModified" : 1 })
> db.table_name.find()
{ "_id" : ObjectId("57c6364278935e710c61131b"), "name" : "zhj", "age" : 60, "province" : "henan" }
{ "_id" : ObjectId("57c6365e78935e710c61131c"), "name" : "zjf", "age" : 18, "province" : "beijing" }
{ "_id" : ObjectId("57c6366e78935e710c61131d"), "name" : "zg", "age" : 22, "province" : "beijing" }

　　② $set修改器

db.table_name.update({"name":"zhj"},{$set:{"age":30}})

# 具體操做以下
> db.table_name.update({"name":"zhj"},{$set:{"age":30}})
WriteResult({ "nMatched" : 1, "nUpserted" : 0, "nModified" : 1 })
> db.table_name.find()
{ "_id" : ObjectId("57c6364278935e710c61131b"), "name" : "zhj", "age" : 30, "province" : "henan" }
{ "_id" : ObjectId("57c6365e78935e710c61131c"), "name" : "zjf", "age" : 18, "province" : "beijing" }
{ "_id" : ObjectId("57c6366e78935e710c61131d"), "name" : "zg", "age" : 22, "province" : "beijing" }

 

  • upsert操做

這個但是mongodb創造出來的「詞」，你們還記得update方法的第一次參數是「查詢條件」嗎？，那麼這個upsert操做就是說：若是我沒有查到，我就在數據庫裏面新增一條，其實這樣也有好處，就是避免了我在數據庫裏面判斷是update仍是add操做，使用起來很簡單，將update的第三個參數設爲true便可。

db.table_name.update({"name":"zhanghj"},{$inc:{"age":30}},true)

# 具體操做以下
> db.table_name.update({"name":"zhanghj"},{$inc:{"age":30}},true)
WriteResult({
    "nMatched" : 0,
    "nUpserted" : 1,
    "nModified" : 0,
    "_id" : ObjectId("57c63ef3a34de94e98acbdd7")
})
> db.table_name.find()
{ "_id" : ObjectId("57c6364278935e710c61131b"), "name" : "zhj", "age" : 30, "province" : "henan" }
{ "_id" : ObjectId("57c6365e78935e710c61131c"), "name" : "zjf", "age" : 18, "province" : "beijing" }
{ "_id" : ObjectId("57c6366e78935e710c61131d"), "name" : "zg", "age" : 22, "province" : "beijing" }
{ "_id" : ObjectId("57c63ef3a34de94e98acbdd7"), "name" : "zhanghj", "age" : 30 }

 

  • 批量更新

在mongodb中若是匹配多條，默認的狀況下只更新第一條，那麼若是咱們有需求必須批量更新，那麼在mongodb中實現也是很簡單的，在update的第四個參數中設爲true便可。例子就不舉了。

#有第四個參數的所有更新
> db.table_name.find()
{ "_id" : ObjectId("57c6364278935e710c61131b"), "name" : "zhj", "age" : 30, "province" : "henan" }
{ "_id" : ObjectId("57c6365e78935e710c61131c"), "name" : "zjf", "age" : 18, "province" : "beijing" }
{ "_id" : ObjectId("57c6366e78935e710c61131d"), "name" : "zg", "age" : 22, "province" : "beijing" }
{ "_id" : ObjectId("57c63ef3a34de94e98acbdd7"), "name" : "zhanghj", "age" : 30 }
{ "_id" : ObjectId("57c63fa978935e710c61131e"), "name" : "zhj", "age" : 10, "province" : "hubei" }
{ "_id" : ObjectId("57c63fb678935e710c61131f"), "name" : "zhj", "age" : 10, "province" : "hebei" }
> db.table_name.update({"name":"zhj"},{$set:{"age":2}},false,true)
WriteResult({ "nMatched" : 3, "nUpserted" : 0, "nModified" : 3 })
> db.table_name.find()
{ "_id" : ObjectId("57c6364278935e710c61131b"), "name" : "zhj", "age" : 2, "province" : "henan" }
{ "_id" : ObjectId("57c6365e78935e710c61131c"), "name" : "zjf", "age" : 18, "province" : "beijing" }
{ "_id" : ObjectId("57c6366e78935e710c61131d"), "name" : "zg", "age" : 22, "province" : "beijing" }
{ "_id" : ObjectId("57c63ef3a34de94e98acbdd7"), "name" : "zhanghj", "age" : 30 }
{ "_id" : ObjectId("57c63fa978935e710c61131e"), "name" : "zhj", "age" : 2, "province" : "hubei" }
{ "_id" : ObjectId("57c63fb678935e710c61131f"), "name" : "zhj", "age" : 2, "province" : "hebei" }

#沒有第四個參數的只更新第一條
> db.table_name.find()
{ "_id" : ObjectId("57c6364278935e710c61131b"), "name" : "zhj", "age" : 2, "province" : "henan" }
{ "_id" : ObjectId("57c6365e78935e710c61131c"), "name" : "zjf", "age" : 18, "province" : "beijing" }
{ "_id" : ObjectId("57c6366e78935e710c61131d"), "name" : "zg", "age" : 22, "province" : "beijing" }
{ "_id" : ObjectId("57c63ef3a34de94e98acbdd7"), "name" : "zhanghj", "age" : 30 }
{ "_id" : ObjectId("57c63fa978935e710c61131e"), "name" : "zhj", "age" : 2, "province" : "hubei" }
{ "_id" : ObjectId("57c63fb678935e710c61131f"), "name" : "zhj", "age" : 2, "province" : "hebei" }
> db.table_name.update({"name":"zhj"},{$set:{"age":20}},false)
WriteResult({ "nMatched" : 1, "nUpserted" : 0, "nModified" : 1 })
> db.table_name.find()
{ "_id" : ObjectId("57c6364278935e710c61131b"), "name" : "zhj", "age" : 20, "province" : "henan" }
{ "_id" : ObjectId("57c6365e78935e710c61131c"), "name" : "zjf", "age" : 18, "province" : "beijing" }
{ "_id" : ObjectId("57c6366e78935e710c61131d"), "name" : "zg", "age" : 22, "province" : "beijing" }
{ "_id" : ObjectId("57c63ef3a34de94e98acbdd7"), "name" : "zhanghj", "age" : 30 }
{ "_id" : ObjectId("57c63fa978935e710c61131e"), "name" : "zhj", "age" : 2, "province" : "hubei" }
{ "_id" : ObjectId("57c63fb678935e710c61131f"), "name" : "zhj", "age" : 2, "province" : "hebei" }
>

 

remove：

db.table_name.remove()

 

2、高級操做

聚合

常見的聚合操做有：count、distinct、group、mapReduce

count

> db.table_name.find()
{ "_id" : ObjectId("57c6364278935e710c61131b"), "name" : "zhj", "age" : 20, "province" : "henan" }
{ "_id" : ObjectId("57c6365e78935e710c61131c"), "name" : "zjf", "age" : 18, "province" : "beijing" }
{ "_id" : ObjectId("57c6366e78935e710c61131d"), "name" : "zg", "age" : 22, "province" : "beijing" }
{ "_id" : ObjectId("57c63ef3a34de94e98acbdd7"), "name" : "zhanghj", "age" : 30 }
{ "_id" : ObjectId("57c63fa978935e710c61131e"), "name" : "zhj", "age" : 2, "province" : "hubei" }
{ "_id" : ObjectId("57c63fb678935e710c61131f"), "name" : "zhj", "age" : 2, "province" : "hebei" }
> db.table_name.count()
6
> db.table_name.count({"age":2})
2

 

distinct

> db.table_name.distinct("name")
[ "zhj", "zjf", "zg", "zhanghj" ]

 

group

在mongodb裏面作group操做有點小複雜，不過你們對sql server 裏面的group比較熟悉的話仍是一眼能看的明白的，其實group操做本質上造成了一種「k-v」模型，就像C#中的Dictionary，好，有了這種思惟，咱們來看看如何使用group。

下面舉的例子就是按照age進行group操做，value爲對應age的姓名。下面對這些參數介紹一下：

  • key： 這個就是分組的key，咱們這裏是對年齡分組。
  • initial: 每組都分享一個」初始化函數「，特別注意：是每一組，好比這個的age=20的value的list分享一個
  • initial函數，age=22一樣也分享一個initial函數。

  • $reduce: 這個函數的第一個參數是當前的文檔對象，第二個參數是上一次function操做的累計對象，第一次爲initial中的{」perosn「：[]}。有多少個文檔， $reduce就會調用多少次。

> db.table_name.find()
{ "_id" : ObjectId("57c6364278935e710c61131b"), "name" : "zhj", "age" : 20, "province" : "henan" }
{ "_id" : ObjectId("57c6365e78935e710c61131c"), "name" : "zjf", "age" : 18, "province" : "beijing" }
{ "_id" : ObjectId("57c6366e78935e710c61131d"), "name" : "zg", "age" : 22, "province" : "beijing" }
{ "_id" : ObjectId("57c63ef3a34de94e98acbdd7"), "name" : "zhanghj", "age" : 30 }
{ "_id" : ObjectId("57c63fa978935e710c61131e"), "name" : "zhj", "age" : 2, "province" : "hubei" }
{ "_id" : ObjectId("57c63fb678935e710c61131f"), "name" : "zhj", "age" : 2, "province" : "hebei" }
> db.table_name.group({
... "key":{"age":true},
... "initial":{"table_name":[]},
... "$reduce":function(cur,prev){
...    prev.table_name.push(cur.name);
... }
... })
[
    {
        "age" : 20,
        "table_name" : [
            "zhj"
        ]
    },
    {
        "age" : 18,
        "table_name" : [
            "zjf"
        ]
    },
    {
        "age" : 22,
        "table_name" : [
            "zg"
        ]
    },
    {
        "age" : 30,
        "table_name" : [
            "zhanghj"
        ]
    },
    {
        "age" : 2,
        "table_name" : [
            "zhj",
            "zhj"
        ]
    }
]

看到上面的結果，是否是有點感受，咱們經過age查看到了相應的name人員，不過有時咱們可能有以下的要求：

①：想過濾掉age>25一些人員。

②：有時person數組裏面的人員太多，我想加上一個count屬性標明一下。

針對上面的需求，在group裏面仍是很好辦到的，由於group有這麼兩個可選參數: condition 和 finalize。

  • condition: 這個就是過濾條件。

  • finalize:這是個函數，每一組文檔執行完後，多會觸發此方法，那麼在每組集合裏面加上count也就是它的活了。

> db.table_name.group({
... "key":{"age":true},
... "initial":{"table_name":[]},
... "$reduce":function(cur,prev){
...    prev.table_name.push(cur.name);
... },
... "finalize":function(out){
... out.count=out.table_name.length;
... },
... "condition":{"age":{$gt:18}}
... })
[
    {
        "age" : 20,
        "table_name" : [
            "zhj"
        ],
        "count" : 1
    },
    {
        "age" : 22,
        "table_name" : [
            "zg"
        ],
        "count" : 1
    },
    {
        "age" : 30,
        "table_name" : [
            "zhanghj"
        ],
        "count" : 1
    }
]

 

mapReduce

參見：http://www.cnblogs.com/huangxincheng/archive/2012/02/21/2361205.html

遊標

mongodb裏面的遊標有點相似咱們說的C#裏面延遲執行，好比：

var list=db.person.find();

針對這樣的操做，list其實並無獲取到person中的文檔，而是申明一個「查詢結構」，等咱們須要的時候經過for或者next()一次性加載過來，而後讓遊標逐行讀取，當咱們枚舉完了以後，遊標銷燬，以後咱們在經過list獲取時，

發現沒有數據返回了。

> var list = db.table_name.find()
> list.forEach(function(x){print(x.name)})
zhj
zjf
zg
zhanghj
zhj
zhj
> list
>

 

固然咱們的「查詢構造」還能夠搞的複雜點，好比分頁，排序均可以加進去。

var single=db.table_name.find().sort({"name":1}).skip(2).limit(2);

 

那麼這樣的「查詢構造」能夠在咱們須要執行的時候執行，大大提升了沒必要要的花銷。

 

sql：

db.car_db.count({
    "date_create": {
        $gte: ISODate("2016-05-23T16:00:00.000+0000"),
        $lt: ISODate("2016-05-24T16:00:00.000+0000")
    },
    'site': 'che168'
})

聚合：

db.maiche168_car_info.aggregate(
   [
     {
       $group:
         {
               _id: "$shop_id",
            company_name:{ $first: "$company_name"},
            company_address:{ $first: "$company_address"},
            province_name:{ $first: "$province_name"},
            city_name:{ $first: "$city_name"},
            seller_phone:{ $first: "$seller_phone"},
            tags:{ $first: "$tags"},
            total:{ $sum: 1},
         }
     }
   ]
)

---

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