MongoDB在某些时候被人诟病,说字段过于灵活,数据结构不稳定,从而被排除在外。mongodb
例如,用户表,大部分状况下,都是固定格式:数据库
| id | name | age | province |
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类型是:express
| ID | CHAR | INT | VARTXT |
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若是使用MongoDB,由于是文档类型,字段增长修改灵活,这就会有一个问题,若是不当心被人insert了一个数据:json
{
name: "Jerry",
age: "18",
province: "Guangdong"
}
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你们看这个 age: "18",特别在当前NodeJS流行的环境下,WEB提交的表但都是string,就有可能出现。固然解决办法也是有的:markdown
const mongoose = require('mongoose')
var UserSchema = mongoose.Schema({
_id: false,
name: {
type: String,
required: [true, "user name is required"]
},
age: {
type: Number
},
province: {
type: String
}
});
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使用mongoose的好处是,不但能够验证,还能够转换类型,除此以外,还能够更贴合面向对象的方式使用数据,因此十分推荐引入Mongoose库。数据结构
那么问题来了,若是同一个数据库的使用这,不是NodeJS环境呢?你们都知道在微服务中,有可能使用Java来实现各类数据的处理。因此最好的方式就是像MYSQL那样在数据库里验证。koa
在MongoDB3.6后,支持jsonSchema的数据验证,经过以下方式能够配置,也能够修改。async
//建表的时候配置
db.createCollection( <collection>, { validator: { $jsonSchema: <schema> } } )
//随时修改
db.runCommand( { collMod: <collection>, validator:{ $jsonSchema: <schema> } } )
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配置的方式就是上面的2个语句,很是简单,使用的是标准JSON Schema规范。mongoose
JSON Schema规范内容,这里不铺开阐述,你们能够本身搜索。固然mongoDB也有本身的一些字段类型,这一点和Javascript有点不同。例如int,那么10是合法的,但10.1是不合法的。还有一些细则,例以下面的year。微服务
year: {
bsonType: "int",
minimum: 2017,
maximum: 3017,
description: "must be an integer in [ 2017, 3017 ] and is required"
},
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这里仅作介绍,具体能够到官网去看,也不复杂。
在设置好验证后,只要验证不经过,就会报错:
WriteResult({
"nInserted" : 0,
"writeError" : {
"code" : 121,
"errmsg" : "Document failed validation"
}
})
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在NodeJS里,能够经过代码来设置,只是若是使用mongoose,由于不提供mongodb connector内置对象暴露,须要咱们稍稍处理一下便可。
const MongoClient = require("mongodb").MongoClient;
const URL = 'mongodb://@127.0.0.1:27017/mydb'
function connect () {
return new Promise((resolve, reject) => {
MongoClient.connect(URL, { useNewUrlParser: true }, (err, database) => {
if (err) {
console.log(`Unable to connect to the databse: ${err}`);
reject(err)
} else {
console.log('Connected to the database');
resolve(database)
}
});
})
}
async function init () {
let connection = await connect()
let db = connection.db()
//这里写jsonSchema
await db.createCollection(<collection>, { validator: { $jsonSchema: <schema> } })
//这里修改jsonSchema
await db.runCommand( { collMod: <collection>, validator:{ $jsonSchema: <schema> } } )
}
init().then(() => {})
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咱们写一些测试用例:
const chai = require('chai')
const { expect } = chai
const URL = 'mongodb://@127.0.0.1:27017/mydb'
const MongoClient = require("mongodb").MongoClient;
function connect () {
return new Promise((resolve, reject) => {
MongoClient.connect(URL, { useNewUrlParser: true }, (err, database) => {
if (err) {
console.log(`Unable to connect to the databse: ${err}`);
reject(err)
} else {
console.log('Connected to the database');
resolve(database)
}
});
})
}
describe('mongoose', function () {
it('createCollection', async () => {
let connection = await connect()
let db = connection.db()
await db.createCollection('students', {
validator: {
$jsonSchema: {
required: ["name"],
properties: {
name: {
bsonType: "string",
description: "must be a string and is required"
},
age: {
bsonType: "int"
},
score: {
bsonType: "number"
},
height: {
bsonType: "double"
},
address: {
bsonType: "object",
required: ["zipcode"],
properties: {
"street": { bsonType: "string" },
"zipcode": { bsonType: "string" }
}
}
}
}
}
})
})
it('jsonSchemaMod', async () => {
let connection = await connect()
let db = connection.db()
let rs = await db.command({
collMod: 'students',
validator: {
$jsonSchema: {
required: ["name"],
properties: {
name: {
bsonType: "string",
description: "must be a string and is required"
},
age: {
bsonType: "int"
},
score: {
bsonType: "number"
},
height: {
bsonType: "double"
},
address: {
bsonType: "object",
required: ["zipcode"],
properties: {
"street": { bsonType: "string" },
"zipcode": { bsonType: "string" }
}
}
}
}
}
})
expect(rs).eql({ ok: 1 })
// console.log('rs:', rs)
})
it('jsonSchemaModLess', async () => {
let connection = await connect()
let db = connection.db()
let rs = await db.command({
collMod: 'students',
validator: {
$jsonSchema: {
properties: {
name: {
bsonType: "string",
description: "must be a string and is required"
},
address: {
bsonType: "object",
properties: {
"street": { bsonType: "string" },
"zipcode": { bsonType: "string" }
}
}
}
}
}
})
expect(rs).eql({ ok: 1 })
})
it('insert', async () => {
let connection = await connect()
let db = connection.db()
let rs = await db.collection('students').insertOne({
name: 'tom',
age: 10,// 10.1 若是非整型,会失败
score: 100, //ok
height: 180, //ok
address: {
zipcode: 'code' //zipcode empty fail
},
otherField: 'an other field'
})
expect(rs.result).include({ ok: 1 })
})
it('emptyName', async () => {
let connection = await connect()
let db = connection.db()
// 若是name是必须,则会失败
let rs = await db.collection('students').insertOne({
age: 10
})
// console.log(rs)
await expect(rs.result).include({ ok: 1 })
})
it('found', async () => {
let connection = await connect()
let db = connection.db()
let found = await db.collection('students').find().toArray()
console.log('found:', found)
expect(found).to.be.an('array')
})
})
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这样,咱们就实现了相似MYSQL的数据验证。
因此呢,之后在也不要说MongoDB数据结构不稳定啦。
官方文档传送门:docs.mongodb.com/manual/refe…