Aggregate usage of MongoDB

Construct some data with a Python script and then show how to use the

#coding =utf-8 ' Created on 2015-12-28 @author: kwsy ' ' Import pymongo client = Pymongo. Mongoclient ("localhost", 27017) db = client.testaggregate coll = db.teacher t1 = {' name ': ' Li ', ' Level ': 3, ' salary ': 10000, ' Stus ': [{' Name ': ' LiA ', ' class ': ' Language ', ' Socre ':}, {' name ': ' LiA ', ' class ': '
                                                   Math ', ' socre ': +}, {' name ': ' LiB ', ' class ': ' Language ', ' Socre ': 95},
                                                   {' name ': ' LiB ', ' class ': ' Math ', ' Socre ': 99}
                                                   ]} t2 = {' name ': ' Liu ', ' Level ': 2, ' salary ': 15000, ' stus ': [{' Name ': ' Liua ', ' class ': ' Language ', ' Socre ': 80},
                                                   {' name ': ' Liua ', ' class ': ' Math ', ' Socre ': 60}, {' name ': ' Liub ', ' class ': ' Language ', ' socre ': ' {' name ': ' Liub ', ' class ': ' Mathematics ', '
                                             Socre ': 90}      ]} t3 = {' name ': ' He ', ' Level ': 5, ' salary ': 20000, ' stus ': [{' Name ': ' HeA ', ' class ': ' Language ', ' Socre ': 96}, {' name ': ' HeA ', ' class ': ' Math ', ' socre ': 80}, { ' Name ': ' Heb ', ' class ': ' Chinese ', ' socre ': ' I ', {' name ': ' Heb ', ' class ': ' Math ', ' SOCR E ': $}]} T4 = {' name ': ' Black ', ' Level ': 5, ' salary ': 25000, ' stus ': [{' Name ': ' Blacka ', ' class ': ' Chinese ', ' socre ': ' {' name ': ' Blacka ', ' class ': ' Math ', ' Soc
                                                   Re ': i}, {' name ': ' blackb ', ' class ': ' Language ', ' Socre ': 66},
                                                   {' name ': ' blackb ', ' class ': ' Math ', ' socre ': 80} ]} coll.insert_one (t1) coll.insert_one (T2) Coll.insert_one (T3) coll.insert_one (T4)

The following script demonstrates how to use the

#coding =utf-8 ' Created on 2015-12-28 It is not a good idea to put students ' scores in the teacher's information document as embedded documents in this script, just for the sake of a more vivid explanation of the functions and effects of aggregation @author: Kwsy ' im Port Pymongo client = Pymongo. Mongoclient ("localhost", 27017) db = client.testaggregate coll = db.teacher #统计所有老师的工资总和, statistics are for teachers, so _id for empty print (U ' Statistic all teachers The sum of the wages ') data = Coll.aggregate ([{' $group ': {' _id '], ' ' count ': {' $sum ': 1}, ' Total_salary ': {' $sum ': ' $salary '}, ' avg ': ' $ Avg ': ' $salary '}}]) data = list (data) print (data[0]) #按照老师的级别统计工资和, with teacher-level statistics, _id is assigned to $level print (U ' statistics different levels of wages and ') data = List (coll.aggregate {' $group ': {' _id ': ' $level ', ' count ': {' $sum ': 1}, ' Total_salary ': {' $sum ': ' $salary '}, ' avg ': ' $ Avg ': ' $salary '}}])) for T in Data:print (t) #下面的语句等效于 find ({' name ': ' Black '}) pipeline = [{' $match ': {' name ': ' Black '}}] data = List (Coll.aggregate (pipeline)) print (data[0]) #使用了 $unwind enable inline documents to be upgraded to the previous level pipeline = [{' $match ': {' name ': ' Black '}},{' $unwind ': ' $stus '}] data = List (Coll.aggregate (pipeline)) for T in Data:print (t) # Upgrade after a match filter, filter only the score Embedded document in 80 pipeline = [{' $match': {' name ': ' Black '}},{' $unwind ': ' $stus '},{' $match ': {' stus.socre ': {' $gt ': {}}}] data = List (Coll.aggregate pipeline ) for T in Data:print (t) #保持原来的内嵌形式不变 print (U ' keep original inline form unchanged ') pipeline = [{' $match ': {' name ': ' Black '}},{' $unwind ': ' $ Stus '}, {' $match ': {' stus.socre ': {' $gt ': 80}}},{' $group ': {' _id ': ' $_id ', ' level ': {' $first ': ' $level '}, ' Stus ': {' $pus  H ': ' $stus '}}] data = List (Coll.aggregate (pipeline)) for T in Data:print (t) #所有学生的语文成绩 print (U ' language scores for all students ') pipeline

= [{' $unwind ': ' $stus '},{' $match ': {' stus.class ': ' Language '}}] data = List (Coll.aggregate (pipeline)) for T in Data:print (t) #所有学生的语文成绩排序取前三个 Print (U ' The first three of all students ' language scores pipeline = [{' $unwind ': ' $stus '},{' $match ': {' stus.class ': ' Language '}},{' $sort ') : {' stus.socre ': -1}},{' $limit ': 3}] data = List (Coll.aggregate (pipeline)) for T in Data:print (t) #某个老师的学生中语文成 Performance Max Print (U ' The maximum of Chinese performance in a teacher's student ") pipeline = [{' $match ': {' name ': ' Black '}},{' $unwind ': ' $stus '}, {' $match ': {' stus.c Lass ': ' Language '}},{' $sort ': {' stus.socre ':-1}}, {' $limit ': 1}] data = List (Coll.aggregate (pipeline)) for T in Data:print (t)