● $eq、$gt、$gte、$lt、$lte

● $and、$or、$not、$in

● $geoWithin、$intersect

......

● 选择需要的或排除不需要的字段

● $map、$reduce、$filter

● $range

● $multiply、$divide、$substract、$add

● $year、$month、$dayOfMonth、$hour、$minute、$second

......

● $esum、$avg

● $push、$addToSet

● $first、$last、$max、$min

......

● 计算

● 分析一段时间内的销售总额、均值

● 计算一段时间内的净利润

● 分析购买人的年龄分布

● 分析学生成绩分布

● 统计员工绩效

select first_name as ‘名‘, last_name as ‘姓‘ from users
where gender=‘男‘ 
skip 100
limit 20

db.users.aggregate([
  {$match:{gender:‘男‘}},
  {$skip:100},
  {$limit:20},
  {$project:{
    ‘名‘:‘$first_name‘,
    ‘姓‘:‘$last_name‘
  }}
])

select department,count(null) as emp_qty from users
where gender=‘女‘
group by department having count(*)>10

db.users.aggregate([
  {$match:{gender:‘女‘}},
  {$group:{
    _id:‘$department‘,
    emp_qty:{$sum:1}
  }},
  {$match:{emp_qty:{$le:10}}}
])

// 现有如下数据
db.students.findOne()
{
  name:"张三",
  score:[
    {subject:‘语文‘,score:84},
    {subject:‘数学‘,score:80},
    {subject:‘英语‘,score:96},
  ]
}

db.students.aggregate([
  {$unwind:‘$score‘}
])
//结果如下
{name:‘张三‘,score:{subject:‘语文‘,score:84}}
{name:‘张三‘,score:{subject:‘数学‘,score:80}}
{name:‘张三‘,score:{subject:‘英语‘,score:96}}

//常用语电商查询，查询价格在0-10 10-20 20-30 30-40 40-max之间的商品数量
db.products.aggregate([
  {$bucket:{
    groupBy:"$price",
    boundaries:[0,10,20,30,40],
    default:"Other",
    output:{"count":{$sum:1}}
  }}
])

//常用于电商查询，多个维度进行查询商品数量
db.products.aggregate([
  {$facet:{
    price:{
      $bucket:{}
    },
    year:{
      $bucket:{}
    }
  }}
])