mongo14-----group，aggregate，mapReduce

group，aggregate，mapReduce

分组统计: group()
简单聚合: aggregate()
强大统计: mapReduce()


db.collection.group(document)
document：{
            key:{key1:1,key2:1},  //根据那几个字段分组
            cond:{},  //筛选的条件
            reduce: function(curr,result) {  //分组之后的聚合运算，curr是一行数据，result是计算后的结果
            },
            initial:{},  //初始化result里面
            finalize:function() {  //reduce一组都执行完毕后最后执行的函数
            }
          }
          
#计算每个栏目下（cat_id）的商品数 count()操作
select  cat_id,count(*) from goods group by cat_id;  //mysql操作

use shop
db.goods.group(
{
    key:{cat_id:1},   //根据哪个字段分组
    cond:{},          //所有行取出来，不加条件
    reduce:function(curr,result) {//reduce的执行过程：每一行就是一个curr,每一组共用一个result变量，
        result.cnt += 1;       //result.cnt是每组有多少行，每个组有一个result,
    },
    initial:{cnt:0}
    }
):
[
    {
        "cat_id" : 4.0,
        "cnt" : 3.0
    },
    {
        "cat_id" : 8.0,
        "cnt" : 3.0
    },
    {
        "cat_id" : null,
        "cnt" : 2.0
    }
]




#查询每个栏目下价格高于3500元的商品数量
use shop
db.goods.group(
{
    key:{cat_id:1},   //cat_id分组，并且查出car_id和shop_price字段
    cond:{shop_price:{$gt:3500}},
    reduce:function(curr,result) {
        result.cnt += 1;
    },
    initial:{cnt:0}
}
):
[
    {
        "cat_id" : 3.0,
        "shop_price" : 5999.0,
        "cnt" : 1.0
    },
    {
        "cat_id" : 5.0,
        "shop_price" : 3700.0,
        "cnt" : 1.0
    }
]




#查询每个栏目下价格大于3000元的商品个数
{
    key:{cat_id:1},
    cond:{},
    reduce: function(curr,result) {
        result.total += 1;
    },
    initial:{total:0}
}：
[
    {
        "cat_id" : 4.0,
        "total" : 3.0
    },
    {
        "cat_id" : 8.0,
        "total" : 3.0
    },    
    {
        "cat_id" : null,
        "total" : 2.0
    }
]



#计算每个栏目下的商品库存量 sum()操作
select  sum(goods_number) from goods group by cat_id;

use shop
db.goods.group(
{
    key:{cat_id:1},
    cond:{},
    reduce: function(curr,result) {
            result.total += curr.goods_number;
    },
    initial:{total:0}
}
)：
[
    {
        "cat_id" : 4.0,
        "total" : 3.0
    },
    {
        "cat_id" : 8.0,
        "total" : 61.0
    },
    {
        "cat_id" : null,
        "total" : NaN
    }
]



#查询每个栏目最贵的商品价格, max()操作
select  max(shop_price) from goods group by cat_id;

use shop
db.goods.group(
{
    key:{cat_id:1},
    cond:{},
    reduce:function(curr , result) {
        if(curr.shop_price > result.max) {
            result.max = curr.shop_price;
        }
    },
    initial:{max:0}
}
)：



#查询每个栏目下商品的平均价格
select cat_id,avg(shop_price) from goods group by cat_id;

use shop
db.goods.group(
{
    key:{cat_id:1},          //相当于group by 
    cond:{},                       //相当于where
    reduce:function(curr , result) {             //相当于sum.avg函数
        result.cnt += 1;
        result.sum += curr.shop_price;
    },
    initial:{sum:0,cnt:0},                //进这个组执行一下
    finalize:function(result) {      //出这个组执行一下，   组操作完毕后的回调函数
        result.avg = result.sum/result.cnt;
    }
}
)：
[
    {
        "cat_id" : 4.0,
        "sum" : 6891.0,
        "cnt" : 3.0,
        "avg" : 2297.0
    },
    {
        "cat_id" : 8.0,
        "sum" : 226.0,
        "cnt" : 3.0,
        "avg" : 75.3333333333333
    },
    {
        "cat_id" : null,
        "sum" : NaN,
        "cnt" : 2.0,
        "avg" : NaN
    }
]





注意: 
1:group需要我们手写聚合函数的业务逻辑
2:group 不支持集群shard cluster, 无法分布式运算

3:分布式可以用 aggregate() (version2.2) , 
或者mapReduce() (version2.4)

GROUP BY        $group
HAVING            $match
SELECT            $project
ORDER BY        $sort
LIMIT            $limit
SUM()            $sum
COUNT()            $sum


#查询每个栏目下的商品数量
select count(*) from goods group by cat_id;

db.goods.aggregate(
[
    {
        $group:{
            _id:"$cat_id",     //根据cad_id分组
            total:{$sum:1}     //乘以1
        }
    }     
]
)：
{
    "_id" : null,
    "total" : -2.0
}
{
    "_id" : 14.0,
    "total" : -2.0
}
{
    "_id" : 2.0,
    "total" : -1.0
}
{
    "_id" : 13.0,
    "total" : -2.0
}



#查询goods下有多少条商品,select count(*) from goods
[
{$group:{_id:null,total:{$sum:1}}}
]；
{
    "_id" : null,
    "total" : 33.0
}



#查询每个栏目下 价格大于3000元的商品个数
use shop
db.goods.aggregate(
[
    {$match:{shop_price:{$gt:3000}}},
    {$group:{_id:"$cat_id",total:{$sum:1}}}
]
)：
{
    "_id" : 5.0,
    "total" : 1.0
}
{
    "_id" : 3.0,
    "total" : 2.0
}




#查询每个栏目下 价格大于50元的商品个数
#并筛选出"满足条件的商品个数" 大于等于3的栏目 
select cat_id,count(*) as cnt from goods where shop_price>3000 group by cat_id having cnt>=2


use shop
db.goods.aggregate(
[
    {$match:{shop_price:{$gt:3000}}},    //放在group之前是where
    {$group:{_id:"$cat_id",total:{$sum:1}}},
    {$match:{total:{$gte:2}}}             //放在group之后是having
]
):
{
    "_id" : 3.0,
    "total" : 2.0
}





#查询每个栏目下的库存量
use shop
db.goods.aggregate(
[
    {$group:{_id:"$cat_id" , total:{$sum:"$goods_number"}}},   //cat_id分组，goods_number求和，
]
)：
{
    "_id" : 5.0,
    "total" : 8.0
}
{
    "_id" : 15.0,
    "total" : 2.0
}




#查询每个栏目下的库存量,并按库存量排序
use shop
db.goods.aggregate(
[
{$group:{_id:"$cat_id" , total:{$sum:"$goods_number"}}},
{$sort:{total:1}}         //1是升序
]
)



#查询每个栏目下的库存量,并按库存量排序
use shop
db.goods.aggregate(
[
    {$group:{_id:"$cat_id" , total:{$sum:"$goods_number"}}},
    {$sort:{total:1}},
    {$limit:3}       //取前3个
]
)：
{
    "_id" : null,
    "total" : 0
}
{
    "_id" : 2.0,
    "total" : 0.0
}
{
    "_id" : 15.0,
    "total" : 2.0
}



#查询每个栏目的商品平均价格,并按平均价格由高到低排序
select cat_id ，avg(shop_price) as pj from goods group by cat_id order by pj desc limit 3

use shop
db.goods.aggregate(
[
    {$group:{_id:"$cat_id" , avg:{$avg:"$shop_price"}}},     //car_id排序，shop_price求平均，
    {$sort:{avg:-1}},
    {$limit:3}       
]
):
{
    "_id" : 5.0,
    "avg" : 3700.0
}
{
    "_id" : 4.0,
    "avg" : 2297.0
}
{
    "_id" : 3.0,
    "avg" : 1746.06666666667
}