我有一个交易表,由员工带来的假期填充。我需要帮助在mongodb中跟踪sql场景。
选择员工,月,年,计数(distinct(holiday_type),sum(hours)from 按员工,月,年划分的交易组
几个星期前我已经开始了mongodb。我得到的部分答案是堆栈溢出帖子Mongodb count distinct with multiple group fields,现在我想添加sum函数。任何指导都非常有用,以下是表格形式的数据样本:
Employee date holiday_type hours
1 1/1/2014 1 8
1 1/5/2014 2 7
1 2/15/2014 1 8
1 3/15/2014 3 16
11 1/1/2014 1 8
11 1/5/2014 1 6
11 2/15/2014 3 8
11 3/15/2014 3 8
答案 0 :(得分:1)
所以"小时"实际上是文档中的一个字段(属性)。因此,从前面的答案中,您只需将双重分组抽象如下:
db.transactions.aggregate([
{ "$group": {
"_id": {
"employee" : "$employee",
"Month": { "$month" : "$date" },
"Year": { "$year" : "$date" },
"holiday_type" : "$holiday_type"
},
"hours": { "$sum": "$hours" }
}},
{ "$group": {
"_id": {
"employee" : "$_id.employee",
"Month": "$_id.Month",
"Year": "$_id.Year"
},
"count": { "$sum": 1 },
"hours": { "$sum": "$hours" }
}}
], { "allowDiskUse": true }
);
所以你只是在两个阶段都使用$sum
。
此外,您应该看看官方文档中提供的SQL to Aggregation mapping chart是值得的。它有许多常见的SQL操作示例以及如何以MongoDB方式实现它们。
来自您自己的数据,但我自己也是这样插入的:
db.transactions.insert([
{ "employee": 1, "date": new Date("2014-01-01"), "holiday_type": 1, "hours": 8 },
{ "employee": 1, "date": new Date("2014-01-05"), "holiday_type": 2, "hours": 7 },
{ "employee": 1, "date": new Date("2014-02-15"), "holiday_type": 1, "hours": 8 },
{ "employee": 1, "date": new Date("2014-03-15"), "holiday_type": 3, "hours": 16 },
{ "employee": 11, "date": new Date("2014-01-01"), "holiday_type": 1, "hours": 8 },
{ "employee": 11, "date": new Date("2014-01-05"), "holiday_type": 1, "hours": 6 },
{ "employee": 11, "date": new Date("2014-02-15"), "holiday_type": 1, "hours": 8 },
{ "employee": 11, "date": new Date("2014-03-15"), "holiday_type": 3, "hours": 8 }
])
并不是最好的例子,因为所有月份实际上都是不同的,但这会得到“不同的”#34; " holiday_type"上的值如果它需要这样分组。结果是:
{
"_id" : {
"employee" : 1,
"Month" : 2,
"Year" : 2014
},
"count" : 1,
"hours" : 8
}
{
"_id" : {
"employee" : 11,
"Month" : 2,
"Year" : 2014
},
"count" : 1,
"hours" : 8
}
{
"_id" : {
"employee" : 1,
"Month" : 1,
"Year" : 2014
},
"count" : 2,
"hours" : 15
}
{
"_id" : {
"employee" : 11,
"Month" : 1,
"Year" : 2014
},
"count" : 1,
"hours" : 14
}
{
"_id" : {
"employee" : 1,
"Month" : 3,
"Year" : 2014
},
"count" : 1,
"hours" : 16
}
{
"_id" : {
"employee" : 11,
"Month" : 3,
"Year" : 2014
},
"count" : 1,
"hours" : 8
}