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优化格式

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罗祥
2019-12-18 17:06:10 +08:00
parent 4255e77bcc
commit 1511e663a9
11 changed files with 517 additions and 517 deletions
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166
notes/MongoDB_聚合.md
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@@ -78,12 +78,12 @@ db.employees.aggregate([
```shell
{
"_id" : ObjectId("5d3fe6488ba16934ccce999d"),
"fullName" : "GeorgiFacello"
"_id" : ObjectId("5d3fe6488ba16934ccce999d"),
"fullName" : "GeorgiFacello"
},
{
"_id" : ObjectId("5d3fe6488ba16934ccce99a0"),
"fullName" : "ChirstianKoblick"
"_id" : ObjectId("5d3fe6488ba16934ccce99a0"),
"fullName" : "ChirstianKoblick"
}
```
@@ -158,16 +158,16 @@ db.employees.aggregate(
```json
{
"_id" : "M",
"totalAge" : 78,
"avgAge" : 39,
"count" : 2
"_id" : "M",
"totalAge" : 78,
"avgAge" : 39,
"count" : 2
},
{
"_id" : "F",
"totalAge" : 66,
"avgAge" : 33,
"count" : 2
"_id" : "F",
"totalAge" : 66,
"avgAge" : 33,
"count" : 2
}
```
@@ -188,10 +188,10 @@ db.employees.aggregate(
# 输出如下
{
"_id" : null,
"totalAge" : 144,
"avgAge" : 36,
"count" : 4
"_id" : null,
"totalAge" : 144,
"avgAge" : 36,
"count" : 4
}
```
@@ -337,11 +337,11 @@ db.employees.aggregate([
"emp_no" : 10001,
........
"emp_title" : [
{
"_id" : ObjectId("5d4011728ba16934ccce99a5"),
"emp_no" : 10001,
"title" : "Senior Engineer"
}
{
"_id" : ObjectId("5d4011728ba16934ccce99a5"),
"emp_no" : 10001,
"title" : "Senior Engineer"
}
]
},
@@ -352,16 +352,16 @@ db.employees.aggregate([
"emp_no" : 10004,
........
"emp_title" : [
{
"_id" : ObjectId("5d4011728ba16934ccce99a8"),
"emp_no" : 10004,
"title" : "Engineer"
},
{
"_id" : ObjectId("5d4011728ba16934ccce99a9"),
"emp_no" : 10004,
"title" : "Senior Engineer"
}
{
"_id" : ObjectId("5d4011728ba16934ccce99a8"),
"emp_no" : 10004,
"title" : "Engineer"
},
{
"_id" : ObjectId("5d4011728ba16934ccce99a9"),
"emp_no" : 10004,
"title" : "Senior Engineer"
}
]
}
```
@@ -412,31 +412,31 @@ db.employees.aggregate([
"emp_no" : 10001,
.......
"emps_title" : [
{
"_id" : ObjectId("5d4011728ba16934ccce99a5"),
"emp_no" : 10001,
"title" : "Senior Engineer"
},
{
"_id" : ObjectId("5d4011728ba16934ccce99a6"),
"emp_no" : 10002,
"title" : "Staff"
},
{
"_id" : ObjectId("5d4011728ba16934ccce99a7"),
"emp_no" : 10003,
"title" : "Senior Engineer"
},
{
"_id" : ObjectId("5d4011728ba16934ccce99a8"),
"emp_no" : 10004,
"title" : "Engineer"
},
{
"_id" : ObjectId("5d4011728ba16934ccce99a9"),
"emp_no" : 10004,
"title" : "Senior Engineer"
}
{
"_id" : ObjectId("5d4011728ba16934ccce99a5"),
"emp_no" : 10001,
"title" : "Senior Engineer"
},
{
"_id" : ObjectId("5d4011728ba16934ccce99a6"),
"emp_no" : 10002,
"title" : "Staff"
},
{
"_id" : ObjectId("5d4011728ba16934ccce99a7"),
"emp_no" : 10003,
"title" : "Senior Engineer"
},
{
"_id" : ObjectId("5d4011728ba16934ccce99a8"),
"emp_no" : 10004,
"title" : "Engineer"
},
{
"_id" : ObjectId("5d4011728ba16934ccce99a9"),
"emp_no" : 10004,
"title" : "Senior Engineer"
}
]
},
@@ -445,31 +445,31 @@ db.employees.aggregate([
"emp_no" : 10002,
.......
"emps_title" : [
{
"_id" : ObjectId("5d4011728ba16934ccce99a5"),
"emp_no" : 10001,
"title" : "Senior Engineer"
},
{
"_id" : ObjectId("5d4011728ba16934ccce99a6"),
"emp_no" : 10002,
"title" : "Staff"
},
{
"_id" : ObjectId("5d4011728ba16934ccce99a7"),
"emp_no" : 10003,
"title" : "Senior Engineer"
},
{
"_id" : ObjectId("5d4011728ba16934ccce99a8"),
"emp_no" : 10004,
"title" : "Engineer"
},
{
"_id" : ObjectId("5d4011728ba16934ccce99a9"),
"emp_no" : 10004,
"title" : "Senior Engineer"
}
{
"_id" : ObjectId("5d4011728ba16934ccce99a5"),
"emp_no" : 10001,
"title" : "Senior Engineer"
},
{
"_id" : ObjectId("5d4011728ba16934ccce99a6"),
"emp_no" : 10002,
"title" : "Staff"
},
{
"_id" : ObjectId("5d4011728ba16934ccce99a7"),
"emp_no" : 10003,
"title" : "Senior Engineer"
},
{
"_id" : ObjectId("5d4011728ba16934ccce99a8"),
"emp_no" : 10004,
"title" : "Engineer"
},
{
"_id" : ObjectId("5d4011728ba16934ccce99a9"),
"emp_no" : 10004,
"title" : "Senior Engineer"
}
]
},
@@ -565,10 +565,10 @@ MongoDB 的 MapReduce 在概念上与 Hadoop MapReduce 类似，MongoDB 将 *map
```shell
db.employees.mapReduce(
function(){
emit(this.gender,this.age)
emit(this.gender,this.age)
},
function(key,values){
return Array.avg(values)
return Array.avg(values)
},
{ out:"age_avg"}
)