MongoDB for grouping operations

First, $group to group

1. Number of employees in each position:

Db.getcollection (' emp '). Aggregate (

[

{' $group ': {

' _id ': ' $job ',

job_count:{' $sum ': 1}

}

}

]

)

2. Total salary for each position

Db.getcollection (' emp '). Aggregate (

[

{' $group ': {

' _id ': ' $job ',

job_salaryt:{' $sum ': ' $salary '}

}

}

]

)

3. Average salary for each position

Db.getcollection (' emp '). Aggregate (

[

{' $group ': {

' _id ': ' $job ',

job_salaryt:{' $sum ': ' $salary '},

job_salary_avg:{' $avg ': ' $salary '}

}

}

]

)

4. Maximum and minimum wage for each position

Db.getcollection (' emp '). Aggregate (

[

{' $group ': {

' _id ': ' $job ',

max_salaryt:{' $max ': ' $salary '},

min_salary:{' $min ': ' $salary '}

}

}

]

)

5. Salary for each position

Db.getcollection (' emp '). Aggregate (

[

{

' $group ': {

' _id ': ' $job ',

' Salary_data ': {' $push ': ' $salary '}

}

}

]

)

6. Personnel of each position

Db.getcollection (' emp '). Aggregate (

[

{

' $group ': {

' _id ': ' $job ',

' Position_name ': {' $addToSet ': ' $name '}//addtoset, if there are duplicate names, keep a

}

}

]

)

Second, the $project the rules of data display

1. Aliases

Db.getcollection (' emp '). Aggregate (

[

{' $project ': {

' _id ': 0

' Position ': ' $job ',

' Name ': 1

}

}

]

)

2. Annual Salary

Db.getcollection (' emp '). Aggregate (

[

{

' $project ': {

' Name ': 1,

' Salary ': {' yearly salary ': {' $multiply ': [' $salary ', 12]}}

}

}

]

)

MongoDB for grouping operations