1、数据准备
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2、group参数解析
官方给出参数结构：
{
group:
{
ns: <namespace>,
key: <key>,
$reduce: <reduce function>,
$keyf: <key function>,
cond: <query>,
finalize: <finalize function>
}
}
重要参数解析：
key：作为分组的key
reduce：这些函数可以返回一个sum或count。该函数接受两个参数(curr,result)：curr(当前文档)和result(分组聚集的结果文档)。
initial：初始化聚合结果文档变量，为空时自动为每列提供初始变量。
keyf：可选。替代的key 字段。指定一个函数创建一个“key object”作为分组的key。使用keyf而是通过group by领域而不是现有的文档域键组。
cond：过滤条件
finalize：在db.collection.group()返回最终结果之前，此功能可以修改的结果文档或替换的结果文档作为一个整体。
3、执行顺序解析
1、key-->2、initial-->3、cond-->4、reduce 将本组信息存储，然后其他组循环2，3，4执行
4、执行案例
#key：表示分组的字段 #cond：分组后查询的条件 #reduce：聚合操作，其中curr表示当前文档的指针，result表示分组聚集的文档 #initial:参数初始化操作 #finalize:最终执行函数，类似java中的finally代码块 #查询每个栏目下的商品数量 { key:{cat_id:1}, cond:{}, reduce:function(curr,result) { result.cnt += 1; }, initial:{cnt:0} } #查询每个栏目下价格高于50元的商品数量 { key:{cat_id:1}, cond:{shop_price:{$gt:50}}, reduce:function(curr,res){ res.cnt +=1; }, initial:{cnt:0} } #每个栏目下的商品库存量 sum()操作 { key:{cat_id:1}, cond:{}, reduce:function(curr,res){ res.num +=curr.goods_number; }, initial:{num:0} } #查询每个栏目最贵的商品价格, max()操作 { key:{cat_id:1}, cond:{}, reduce:function(curr,res){ if(res.price<curr.shop_price){ res.price = curr.shop_price; } }, initial:{price:0} } #查询每个栏目下商品的平均价格 { key:{cat_id:1}, cond:{}, reduce:function(curr,res){ res.cnt +=1; res.sum += curr.shop_price; }, initial:{sum:0,cnt:0}, finalize:function(res){ res.avg = res.sum/res.cnt; } }
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