No sql MongoDb by its very nature did not support joins and promotes to embed documents, however with new version 3.2 of mongoDb they have an alternative of joins which can be used in aggregation.
For a better performing design you can keep all related data in one big document (embedded) but for some security reasons if you have to keep it separate, then normalization is good idea.
Mongodb does not allow for sub queries or joins, however that can be simulated for example you employee table and instead of embedding salary details in employee document you kept in salary collection and you want to fetch,
SQL query : select salary from salary where employee_id = (select employee_id from employee where employee name like ‘premaseem’)
# Inserted 2 records in 2 different collections for join
> db.employee.insert({eid:1,name:”premaseem”})
WriteResult({ “nInserted” : 1 })
> db.salary.insert({ eid:1, salary:6000 })
WriteResult({ “nInserted” : 1 })
# Validated data in 2 tables
> db.salary.find({ eid:1})
{ “_id” : ObjectId(“56da1a5b2253b2199c53025b”), “eid” : 1, “salary” : 6000 }
> db.salary.find({ eid: db.employee.find({eid:1}) })
> db.employee.find({name : “prem” })
{ “_id” : ObjectId(“56da19d42253b2199c53025a”), “eid” : 1, “name” : “prem” }
#simulated join to get salary for employee premaseem
> db.employee.find({name : “premaseem” }).map(function(d){
var obj = db.salary.findOne({eid : d.eid });
print(obj.salary);
return obj.salary;
} )
Output : 6000
Here is the python script to try out same
__author__ = 'premaseem'
from pymongo import Connection
c = Connection()
db = c.test
db.employee.drop()
db.employeeSalary.drop()
db.test.insert({"name":"premaseem"})
obj1 = {"eid":1,"name":"premaseem"}
obj2 = {"eid":2,"name":"sony"}
obj3 = {"eid":3,"name":"meera"}
bulk_employee_insert = [obj1,obj2,obj3]
# insert salary
db.employee.insert(bulk_employee_insert)
objs1 = {"eid":1,"salary":1000}
objs2 = {"eid":2,"salary":8000}
objs3 = {"eid":3,"salary":25}
bulk_salary_insert = [objs1,objs2,objs3]
db.employeeSalary.insert(bulk_salary_insert)
print str(db.employee.count()) + str("total employee")
print str(db.employeeSalary.count()) + str("total salary")
def find_employee() :
emp_obj = db.employee.find_one({"eid":1})
print emp_obj
def find_employee_with_joined_salary(eid) :
emp_obj = db.employee.find_one({"eid":eid})
emp_sal_obj = db.employeeSalary.find_one({"eid":eid})
emp_obj["salary"] = emp_sal_obj["salary"]
print emp_obj
find_employee_with_joined_salary(2)
MongoDB 3.2 has come up with $lookup which helps to join in aggregation. For reference follow links
Reference : MongoDB and the Shocking Case of the Missing JOIN ($lookup)
MongoDB doc : https://docs.mongodb.org/manual/reference/operator/aggregation/lookup/#example
PremAseem.me 