【Mongodb】视图 && 索引

 

准备工作

准备2个集合的数据,后面视图和索引都会用到
1个订单集合,一个收款信息集合

var orders = new Array();
var shipping = new Array();
var addresses = ["广西省玉林市", "湖南省岳阳市", "湖北省荆州市", "甘肃省兰州市", "吉林省松原市", "江西省景德镇", "辽宁省沈阳市", "福建省厦门市", "广东省广州市", "北京市朝阳区"];

for (var i = 10000; i < 20000; i++) {
    var orderNo = i + Math.random().toString().substr(2, 5);
    orders[i] = { orderNo: orderNo, userId: i, price: Math.round(Math.random() * 10000) / 100, qty: Math.floor(Math.random() * 10) + 1, orderTime: new Date(new Date().setSeconds(Math.floor(Math.random() * 10000))) };

    var address = addresses[Math.floor(Math.random() * 10)];
    shipping[i] = { orderNo: orderNo, address: address, recipienter: "Wilson", province: address.substr(0, 3), city: address.substr(3, 3) }
}
db.order.insert(orders);
db.shipping.insert(shipping);

 

视图

概述

A MongoDB view is a queryable object whose contents are defined by an aggregation pipeline on other collections or views. MongoDB does not persist the view contents to disk. A view’s content is computed on-demand when a client queries the view. MongoDB can require clients to have permission to query the view. MongoDB does not support write operations against views.

Mongodb的视图基本上和SQL的视图一样

  • 数据源(集合或视图)
  • 提供查询
  • 不实际存储硬盘
  • 客户端发起请求查询时计算而得

1. 创建视图

有两种方法创建视图

db.createCollection(
  "<viewName>",
  {
    "viewOn" : "<source>",
    "pipeline" : [<pipeline>],
    "collation" : { <collation> }
  }
)
db.createView(
  "<viewName>",
  "<source>",
  [<pipeline>],
  {
    "collation" : { <collation> }
  }
)

一般使用db.createView

viewName : 必须,视图名称

source : 必须,数据源,集合/视图

[<pipeline>] : 可选,一组管道,可见管道是Mongodb比较重要的一环

 

1.1 单个集合创建视图

假设现在查看当天最高的10笔订单视图,例如后台某个地方需要实时显示金额最高的订单

db.createView(
    "orderInfo",         //视图名称
    "order",             //数据源   
    [
        //筛选符合条件的订单,大于当天,这里要注意时区
        { $match: { "orderTime": { $gte: ISODate("2020-04-13T16:00:00.000Z") } } },
        //按金额倒序
        { $sort: { "price": -1 } },
        //限制10个文档
        { $limit: 10 },
        //选择要显示的字段
        //0: 排除字段,若字段上使用(_id除外),就不能有其他包含字段
        //1: 包含字段
        { $project: { _id: 0, orderNo: 1, price: 1, orderTime: 1 } }
    ]
)

然后就可以直接使用orderInfo这个视图查询数据

db.orderInfo.find({})

返回结果

{ "orderNo" : "1755149436", "price" : 100, "orderTime" : ISODate("2020-04-14T13:49:42.220Z") }
{ "orderNo" : "1951423853", "price" : 99.99, "orderTime" : ISODate("2020-04-14T15:08:07.240Z") }
{ "orderNo" : "1196303215", "price" : 99.99, "orderTime" : ISODate("2020-04-14T15:15:41.158Z") }
{ "orderNo" : "1580069456", "price" : 99.98, "orderTime" : ISODate("2020-04-14T13:41:07.199Z") }
{ "orderNo" : "1114480559", "price" : 99.98, "orderTime" : ISODate("2020-04-14T13:31:58.150Z") }
{ "orderNo" : "1229542817", "price" : 99.98, "orderTime" : ISODate("2020-04-14T15:15:35.162Z") }
{ "orderNo" : "1208031402", "price" : 99.94, "orderTime" : ISODate("2020-04-14T14:13:02.160Z") }
{ "orderNo" : "1680622670", "price" : 99.93, "orderTime" : ISODate("2020-04-14T15:17:25.210Z") }
{ "orderNo" : "1549824953", "price" : 99.92, "orderTime" : ISODate("2020-04-14T13:09:41.196Z") }
{ "orderNo" : "1449930147", "price" : 99.92, "orderTime" : ISODate("2020-04-14T15:16:15.187Z") }
 

1.2 多个集合创建视图

其实跟单个是集合是一样,只是多了$lookup连接操作符,视图根据管道最终结果显示,所以可以关联多个集合(若出现这种情况就要考虑集合设计是否合理,mongodb本来就是文档型数据库)

db.orderDetail.drop()
db.createView(
    "orderDetail",
    "order",
    [
        { $lookup: { from: "shipping", localField: "orderNo", foreignField: "orderNo", as: "shipping" } },
        { $project: { "orderNo": 1, "price": 1, "shipping.address": 1 } }
    ]
)

查询视图,得到如下结果

{ "_id" : ObjectId("5e95af8c4ef6faf974b4a6c3"), "orderNo" : "1000039782", "price" : 85.94, "shipping" : [ { "address" : "北京市朝阳区" } ] }
{ "_id" : ObjectId("5e95af8c4ef6faf974b4a6c4"), "orderNo" : "1000102128", "price" : 29.04, "shipping" : [ { "address" : "吉林省松原市" } ] }
{ "_id" : ObjectId("5e95af8c4ef6faf974b4a6c5"), "orderNo" : "1000214514", "price" : 90.69, "shipping" : [ { "address" : "湖南省岳阳市" } ] }
{ "_id" : ObjectId("5e95af8c4ef6faf974b4a6c6"), "orderNo" : "1000337987", "price" : 75.05, "shipping" : [ { "address" : "辽宁省沈阳市" } ] }
{ "_id" : ObjectId("5e95af8c4ef6faf974b4a6c7"), "orderNo" : "1000468969", "price" : 76.84, "shipping" : [ { "address" : "江西省景德镇" } ] }
{ "_id" : ObjectId("5e95af8c4ef6faf974b4a6c8"), "orderNo" : "1000572219", "price" : 60.25, "shipping" : [ { "address" : "江西省景德镇" } ] }
{ "_id" : ObjectId("5e95af8c4ef6faf974b4a6c9"), "orderNo" : "1000611743", "price" : 19.14, "shipping" : [ { "address" : "广东省广州市" } ] }
{ "_id" : ObjectId("5e95af8c4ef6faf974b4a6ca"), "orderNo" : "1000773917", "price" : 31.5, "shipping" : [ { "address" : "北京市朝阳区" } ] }
{ "_id" : ObjectId("5e95af8c4ef6faf974b4a6cb"), "orderNo" : "1000879146", "price" : 76.16, "shipping" : [ { "address" : "吉林省松原市" } ] }
{ "_id" : ObjectId("5e95af8c4ef6faf974b4a6cc"), "orderNo" : "1000945977", "price" : 93.98, "shipping" : [ { "address" : "辽宁省沈阳市" } ] }

可以看到,mongodb不是像SQL那样把连接的表当成列列出,而是把连接结果放在数组里面,这很符合Mongodb文档型结构。

 

2. 修改视图

假设现在需要增加一个数量的字段

db.runCommand({
    collMod: "orderInfo",
    viewOn: "order",
    pipeline: [
        { $match: { "orderTime": { $gte: ISODate("2020-04-13T16:00:00.000Z") } } },
        { $sort: { "price": -1 } },
        { $limit: 10 },
        //增加qty
        { $project: { _id: 0, orderNo: 1, price: 1, qty: 1, orderTime: 1 } }
    ]
})

当然,也可以删除视图,重新用db.createView()创建视图

 

3. 删除视图

db.orderInfo.drop();

 

索引

概述

Indexes support the efficient execution of queries in MongoDB. Without indexes, MongoDB must perform a collection scan, i.e. scan every document in a collection, to select those documents that match the query statement. If an appropriate index exists for a query, MongoDB can use the index to limit the number of documents it must inspect.

索引能提供高效的查询,没有索引的查询,mongole执行集合扫描,相当于SQL SERVER的全表扫描,扫描每一个文档。

数据存在存储介质上,大多数情况是为了查询,查询的快慢直接影响用户体验,mongodb索引也是空间换时间,添加索引,CUD操作都会导致索引重新生成,影响速度。

 

1. 准备工作

1.1 准备200W条数据

var orderNo = 100 * 10000;
for (var i = 0; i < 100; i++) {
    //分批次插入,每次20000条
    var orders = new Array();
    for (var j = 0; j < 20000; j++) {
        var orderNo = orderNo++;
        orders[j] = { orderNo: orderNo, userId: i + j, price: Math.round(Math.random() * 10000) / 100, qty: Math.floor(Math.random() * 10) + 1, orderTime: new Date(new Date().setSeconds(Math.floor(Math.random() * 10000))) };
    }
    //不需写入确认
    db.order.insert(orders, { writeConcern: { w: 0 } });
}

 

1.2 mongodb的查询计划

db.collection.explain().<method(...)>

 

一般使用执行统计模式,例如

db.order.explain("executionStats").find({orderNo:1000000})

返回的executionStats对象字段说明

部分字段说明

字段说明
executionSuccess 是否执行成功
nReturned 返回匹配文档数量
executionTimeMillis 执行时间,单位:毫秒
totalKeysExamined 索引检索数目
totalDocsExamined 文档检索数目

查看未加索引前查询计划

db.order.explain("executionStats").find({orderNo:1000000})

截取部分返回结果,可以看出

  • executionTimeMillis : 用时1437毫秒
  • totalDocsExamined : 扫描文档200W
  • executionStages.stage : 集合扫描
"executionStats" : {
    "executionSuccess" : true,
    "nReturned" : 1,
    "executionTimeMillis" : 1437,
    "totalKeysExamined" : 0,
    "totalDocsExamined" : 2000000,
    "executionStages" : {
            "stage" : "COLLSCAN",

 

1.3 查看当前集合统计信息

db.order.stats()

截取部分信息,可以看出现在存储文件大小大概为72M

{
        "ns" : "mongo.order",
        "size" : 204000000,
        "count" : 2000000,
        "avgObjSize" : 102,
        "storageSize" : 74473472,

 

2. 创建索引

db.order.createIndex({ orderNo: 1 }, { name: "ix_orderNo" })

索引名称不是必须,若不指定,按 字段名称_排序类型组合自动生成,索引名称一旦创建不能修改,若要修改,只能删除索引重新生成索引,建议还是建索引的时候就把索引名称设置好。

 

2.1 执行查询计划

db.order.explain("executionStats").find({orderNo:1000000})

截取部分结果,直观就可以感觉查询速度有了质的提升,再看查询计划更加惊讶

  • nReturned : 匹配到1个文档
  • executionTimeMillis : 0,呃。。
  • totalKeysExamined : 总共检索了1个索引
  • totalDocsExamined : 总共检索了1个文档
  • executionStages.stage : FETCH,根据索引去检索指定文档,像SQL的Index Seek
 "executionStats" : {
                "executionSuccess" : true,
                "nReturned" : 1,
                "executionTimeMillis" : 0,
                "totalKeysExamined" : 1,
                "totalDocsExamined" : 1,
                "executionStages" : {
                        "stage" : "FETCH"

 

这里只介绍最简单的单个字段索引,mongodb还有很多索引

  • 复合索引(Compound Indexes):对多个字段做索引
  • 多键索引(Multikey Indexes): 一个字段多个值做索引,通常是数组
  • 全文索引(Text Indexes): 对文本检索,可以对字段设置不同权重
  • 通配符索引(Wildcard Indexes):可以将对象的所有/指定的值做索引
  • 更多
 

 

posted @ 2020-04-15 13:20  WilsonPan  阅读(3156)  评论(0编辑  收藏  举报